biology definition for control experiment

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Biology archive

Course: biology archive > unit 1.

The scientific method

Controlled experiments

The scientific method and experimental design

Introduction

How are hypotheses tested.

One pot of seeds gets watered every afternoon.
The other pot of seeds doesn't get any water at all.

Control and experimental groups

Independent and dependent variables, independent variables, dependent variables, variability and repetition, controlled experiment case study: co 2 ‍ and coral bleaching.

What your control and experimental groups would be
What your independent and dependent variables would be
What results you would predict in each group

Experimental setup

Some corals were grown in tanks of normal seawater, which is not very acidic ( pH ‍ around 8.2 ‍ ). The corals in these tanks served as the control group .
Other corals were grown in tanks of seawater that were more acidic than usual due to addition of CO 2 ‍ . One set of tanks was medium-acidity ( pH ‍ about 7.9 ‍ ), while another set was high-acidity ( pH ‍ about 7.65 ‍ ). Both the medium-acidity and high-acidity groups were experimental groups .
In this experiment, the independent variable was the acidity ( pH ‍ ) of the seawater. The dependent variable was the degree of bleaching of the corals.
The researchers used a large sample size and repeated their experiment. Each tank held 5 ‍ fragments of coral, and there were 5 ‍ identical tanks for each group (control, medium-acidity, and high-acidity). Note: None of these tanks was "acidic" on an absolute scale. That is, the pH ‍ values were all above the neutral pH ‍ of 7.0 ‍ . However, the two groups of experimental tanks were moderately and highly acidic to the corals , that is, relative to their natural habitat of plain seawater.

Analyzing the results

Non-experimental hypothesis tests, case study: coral bleaching and temperature, attribution:, works cited:.

Hoegh-Guldberg, O. (1999). Climate change, coral bleaching, and the future of the world's coral reefs. Mar. Freshwater Res. , 50 , 839-866. Retrieved from www.reef.edu.au/climate/Hoegh-Guldberg%201999.pdf.
Anthony, K. R. N., Kline, D. I., Diaz-Pulido, G., Dove, S., and Hoegh-Guldberg, O. (2008). Ocean acidification causes bleaching and productivity loss in coral reef builders. PNAS , 105 (45), 17442-17446. http://dx.doi.org/10.1073/pnas.0804478105 .
University of California Museum of Paleontology. (2016). Misconceptions about science. In Understanding science . Retrieved from http://undsci.berkeley.edu/teaching/misconceptions.php .
Hoegh-Guldberg, O. and Smith, G. J. (1989). The effect of sudden changes in temperature, light and salinity on the density and export of zooxanthellae from the reef corals Stylophora pistillata (Esper, 1797) and Seriatopora hystrix (Dana, 1846). J. Exp. Mar. Biol. Ecol. , 129 , 279-303. Retrieved from http://www.reef.edu.au/ohg/res-pic/HG%20papers/HG%20and%20Smith%201989%20BLEACH.pdf .

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Microbe Notes

Controlled Experiments: Definition, Steps, Results, Uses

Controlled experiments ensure valid and reliable results by minimizing biases and controlling variables effectively.

Rigorous planning, ethical considerations, and precise data analysis are vital for successful experiment execution and meaningful conclusions.

Real-world applications demonstrate the practical impact of controlled experiments, guiding informed decision-making in diverse domains.

Controlled experiments are the systematic research method where variables are intentionally manipulated and controlled to observe the effects of a particular phenomenon. It aims to isolate and measure the impact of specific variables, ensuring a more accurate causality assessment.

Table of Contents

Interesting Science Videos

Importance of controlled experiments in various fields

Controlled experiments are significant across diverse fields, including science, psychology, economics, healthcare, and technology.

They provide a systematic approach to test hypotheses, establish cause-and-effect relationships, and validate the effectiveness of interventions or solutions.

Why Controlled Experiments Matter?

Validity and reliability of results.

Controlled experiments uphold the gold standard for scientific validity and reliability. By meticulously controlling variables and conditions, researchers can attribute observed outcomes accurately to the independent variable being tested. This precision ensures that the findings can be replicated and are trustworthy.

Minimizing Biases and Confounding Variables

One of the core benefits of controlled experiments lies in their ability to minimize biases and confounding variables. Extraneous factors that could distort results are mitigated through careful control and randomization. This enables researchers to isolate the effects of the independent variable, leading to a more accurate understanding of causality.

Achieving Causal Inference

Controlled experiments provide a strong foundation for establishing causal relationships between variables. Researchers can confidently infer causation by manipulating specific variables and observing resulting changes. The capability informs decision-making, policy formulation, and advancements across various fields.

Planning a Controlled Experiment

Formulating research questions and hypotheses.

Formulating clear research questions and hypotheses is paramount at the outset of a controlled experiment. These inquiries guide the direction of the study, defining the variables of interest and setting the stage for structured experimentation.

Well-defined questions and hypotheses contribute to focused research and facilitate meaningful data collection.

Identifying Variables and Control Groups

Identifying and defining independent, dependent, and control variables is fundamental to experimental planning.

Precise identification ensures that the experiment is designed to isolate the effect of the independent variable while controlling for other influential factors. Establishing control groups allows for meaningful comparisons and robust analysis of the experimental outcomes.

Designing Experimental Procedures and Protocols

Careful design of experimental procedures and protocols is essential for a successful controlled experiment. The step involves outlining the methodology, data collection techniques, and the sequence of activities in the experiment.

A well-designed experiment is structured to maintain consistency, control, and accuracy throughout the study, thereby enhancing the validity and credibility of the results.

Conducting a Controlled Experiment

Randomization and participant selection.

Randomization is a critical step in ensuring the fairness and validity of a controlled experiment. It involves assigning participants to different experimental conditions in a random and unbiased manner.

The selection of participants should accurately represent the target population, enhancing the results’ generalizability.

Data Collection Methods and Instruments

Selecting appropriate data collection methods and instruments is pivotal in gathering accurate and relevant data. Researchers often employ surveys, observations, interviews, or specialized tools to record and measure the variables of interest.

The chosen methods should align with the experiment’s objectives and provide reliable data for analysis.

Monitoring and Maintaining Experimental Conditions

Maintaining consistent and controlled experimental conditions throughout the study is essential. Regular monitoring helps ensure that variables remain constant and uncontaminated, reducing the risk of confounding factors.

Rigorous monitoring protocols and timely adjustments are crucial for the accuracy and reliability of the experiment.

Analysing Results and Drawing Conclusions

Data analysis techniques.

Data analysis involves employing appropriate statistical and analytical techniques to process the collected data. This step helps derive meaningful insights, identify patterns, and draw valid conclusions.

Common techniques include regression analysis, t-tests , ANOVA , and more, tailored to the research design and data type .

Interpretation of Results

Interpreting the results entails understanding the statistical outcomes and their implications for the research objectives.

Researchers analyze patterns, trends, and relationships revealed by the data analysis to infer the experiment’s impact on the variables under study. Clear and accurate interpretation is crucial for deriving actionable insights.

Implications and Potential Applications

Identifying the broader implications and potential applications of the experiment’s results is fundamental. Researchers consider how the findings can inform decision-making, policy development, or further research.

Understanding the practical implications helps bridge the gap between theoretical insights and real-world application.

Common Challenges and Solutions

Addressing ethical considerations.

Ethical challenges in controlled experiments include ensuring informed consent, protecting participants’ privacy, and minimizing harm.

Solutions involve thorough ethics reviews, transparent communication with participants, and implementing safeguards to uphold ethical standards throughout the experiment.

Dealing with Sample Size and Statistical Power

The sample size is crucial for achieving statistically significant results. Adequate sample sizes enhance the experiment’s power to detect meaningful effects accurately.

Statistical power analysis guides researchers in determining the optimal sample size for the experiment, minimizing the risk of type I and II errors .

Mitigating Unforeseen Variables

Unforeseen variables can introduce bias and affect the experiment’s validity. Researchers employ meticulous planning and robust control measures to minimize the impact of unforeseen variables.

Pre-testing and pilot studies help identify potential confounders, allowing researchers to adapt the experiment accordingly.

A controlled experiment involves meticulous planning, precise execution, and insightful analysis. Adhering to ethical standards, optimizing sample size, and adapting to unforeseen variables are key challenges that require thoughtful solutions.

Real-world applications showcase the transformative potential of controlled experiments across varied domains, emphasizing their indispensable role in evidence-based decision-making and progress.

https://www.khanacademy.org/science/biology/intro-to-biology/science-of-biology/a/experiments-and-observations
https://www.scribbr.com/methodology/controlled-experiment/
https://link.springer.com/10.1007/978-1-4899-7687-1_891
http://ai.stanford.edu/~ronnyk/GuideControlledExperiments.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776925/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/
https://www.merriam-webster.com/dictionary/controlled%20experiment

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What Is a Controlled Experiment? | Definitions & Examples

What Is a Controlled Experiment? | Definitions & Examples

Published on April 19, 2021 by Pritha Bhandari . Revised on June 22, 2023.

In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.

Controlling variables can involve:

holding variables at a constant or restricted level (e.g., keeping room temperature fixed).
measuring variables to statistically control for them in your analyses.
balancing variables across your experiment through randomization (e.g., using a random order of tasks).

Why does control matter in experiments, methods of control, problems with controlled experiments, other interesting articles, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables. Strong validity also helps you avoid research biases , particularly ones related to issues with generalizability (like sampling bias and selection bias .)

Your independent variable is the color used in advertising.
Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.

Design and description of the meal,
Study environment (e.g., temperature or lighting),
Participant’s frequency of buying fast food,
Participant’s familiarity with the specific fast food brand,
Participant’s socioeconomic status.

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biology definition for control experiment

You can control some variables by standardizing your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., ad color) should be systematically changed between groups.

Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with color blindness).

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment (e.g., a placebo to control for a placebo effect ), and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

To test the effect of colors in advertising, each participant is placed in one of two groups:

A control group that’s presented with red advertisements for a fast food meal.
An experimental group that’s presented with green advertisements for the same fast food meal.

Random assignment

To avoid systematic differences and selection bias between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a “true experiment”—it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers—or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs and is critical for avoiding several types of research bias .

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses , leading to observer bias . In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses. These are called demand characteristics . If participants behave a particular way due to awareness of being observed (called a Hawthorne effect ), your results could be invalidated.

Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.

You use an online survey form to present the advertisements to participants, and you leave the room while each participant completes the survey on the computer so that you can’t tell which condition each participant was in.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity —the extent to which your results can be generalized to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritize control or generalizability in your experiment.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Student’s t -distribution
Normal distribution
Null and Alternative Hypotheses
Chi square tests
Confidence interval
Quartiles & Quantiles
Cluster sampling
Stratified sampling
Data cleansing
Reproducibility vs Replicability
Peer review
Prospective cohort study

Research bias

Implicit bias
Cognitive bias
Placebo effect
Hawthorne effect
Hindsight bias
Affect heuristic
Social desirability bias

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

A control group that receives a standard treatment, a fake treatment, or no treatment.
Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

A testable hypothesis
At least one independent variable that can be precisely manipulated
At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

How you will manipulate the variable(s)
How you will control for any potential confounding variables
How many subjects or samples will be included in the study
How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

Cite this Scribbr article

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Bhandari, P. (2023, June 22). What Is a Controlled Experiment? | Definitions & Examples. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/methodology/controlled-experiment/

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Methodology
Controlled Experiments | Methods & Examples of Control

Controlled Experiments | Methods & Examples of Control

Published on 19 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

Controlling variables can involve:

Holding variables at a constant or restricted level (e.g., keeping room temperature fixed)
Measuring variables to statistically control for them in your analyses
Balancing variables across your experiment through randomisation (e.g., using a random order of tasks)

Why does control matter in experiments, methods of control, problems with controlled experiments, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables.

Your independent variable is the colour used in advertising.
Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Design and description of the meal
Study environment (e.g., temperature or lighting)
Participant’s frequency of buying fast food
Participant’s familiarity with the specific fast food brand
Participant’s socioeconomic status

Prevent plagiarism, run a free check.

You can control some variables by standardising your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., advert colour) should be systematically changed between groups.

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment, and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

A control group that’s presented with red advertisements for a fast food meal
An experimental group that’s presented with green advertisements for the same fast food meal

Random assignment

To avoid systematic differences between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a ‘true experiment’ – it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers – or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs.

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses. In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity – the extent to which your results can be generalised to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritise control or generalisability in your experiment.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

A testable hypothesis
One or more independent variables that you will manipulate
One or more dependent variables that you will measure

When designing the experiment, first decide:

How your variable(s) will be manipulated
How you will control for any potential confounding or lurking variables
How many subjects you will include
How you will assign treatments to your subjects

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Bhandari, P. (2022, October 10). Controlled Experiments | Methods & Examples of Control. Scribbr. Retrieved 21 August 2024, from https://www.scribbr.co.uk/research-methods/controlled-experiments/

Is this article helpful?

Pritha Bhandari

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v.20(10); 2019 Oct 4

Why control an experiment?

John s torday.

1 Department of Pediatrics, Harbor‐UCLA Medical Center, Torrance, CA, USA

František Baluška

2 IZMB, University of Bonn, Bonn, Germany

Empirical research is based on observation and experimentation. Yet, experimental controls are essential for overcoming our sensory limits and generating reliable, unbiased and objective results.

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Object name is EMBR-20-e49110-g001.jpg

We made a deliberate decision to become scientists and not philosophers, because science offers the opportunity to test ideas using the scientific method. And once we began our formal training as scientists, the greatest challenge beyond formulating a testable or refutable hypothesis was designing appropriate controls for an experiment. In theory, this seems trivial, but in practice, it is often difficult. But where and when did this concept of controlling an experiment start? It is largely attributed to Roger Bacon, who emphasized the use of artificial experiments to provide additional evidence for observations in his Novum Organum Scientiarum in 1620. Other philosophers took up the concept of empirical research: in 1877, Charles Peirce redefined the scientific method in The Fixation of Belief as the most efficient and reliable way to prove a hypothesis. In the 1930s, Karl Popper emphasized the necessity of refuting hypotheses in The Logic of Scientific Discoveries . While these influential works do not explicitly discuss controls as an integral part of experiments, their importance for generating solid and reliable results is nonetheless implicit.

… once we began our formal training as scientists, the greatest challenge beyond formulating a testable or refutable hypothesis was designing appropriate controls for an experiment.

But the scientific method based on experimentation and observation has come under criticism of late in light of the ever more complex problems faced in physics and biology. Chris Anderson, the editor of Wired Magazine, proposed that we should turn to statistical analysis, machine learning, and pattern recognition instead of creating and testing hypotheses, based on the Informatics credo that if you cannot answer the question, you need more data. However, this attitude subsumes that we already have enough data and that we just cannot make sense of it. This assumption is in direct conflict with David Bohm's thesis that there are two “Orders”, the Explicate and Implicate 1 . The Explicate Order is the way in which our subjective sensory systems perceive the world 2 . In contrast, Bohm's Implicate Order would represent the objective reality beyond our perception. This view—that we have only a subjective understanding of reality—dates back to Galileo Galilei who, in 1623, criticized the Aristotelian concept of absolute and objective qualities of our sensory perceptions 3 and to Plato's cave allegory that reality is only what our senses allow us to see.

The only way for systematically overcoming the limits of our sensory apparatus and to get a glimpse of the Implicate Order is through the scientific method, through hypothesis‐testing, controlled experimentation. Beyond the methodology, controlling an experiment is critically important to ensure that the observed results are not just random events; they help scientists to distinguish between the “signal” and the background “noise” that are inherent in natural and living systems. For example, the detection method for the recent discovery of gravitational waves used four‐dimensional reference points to factor out the background noise of the Cosmos. Controls also help to account for errors and variability in the experimental setup and measuring tools: The negative control of an enzyme assay, for instance, tests for any unrelated background signals from the assay or measurement. In short, controls are essential for the unbiased, objective observation and measurement of the dependent variable in response to the experimental setup.

The only way for systematically overcoming the limits of our sensory apparatus […] is through the Scientific Method, through hypothesis‐testing, controlled experimentation.

Nominally, both positive and negative controls are material and procedural; that is, they control for variability of the experimental materials and the procedure itself. But beyond the practical issues to avoid procedural and material artifacts, there is an underlying philosophical question. The need for experimental controls is a subliminal recognition of the relative and subjective nature of the Explicate Order. It requires controls as “reference points” in order to transcend it, and to approximate the Implicate Order.

This is similar to Peter Rowlands’ 4 dictum that everything in the Universe adds up to zero, the universal attractor in mathematics. Prior to the introduction of zero, mathematics lacked an absolute reference point similar to a negative or positive control in an experiment. The same is true of biology, where the cell is the reference point owing to its negative entropy: It appears as an attractor for the energy of its environment. Hence, there is a need for careful controls in biology: The homeostatic balance that is inherent to life varies during the course of an experiment and therefore must be precisely controlled to distinguish noise from signal and approximate the Implicate Order of life.

P < 0.05 tacitly acknowledges the explicate order

Another example of the “subjectivity” of our perception is the level of accuracy we accept for differences between groups. For example, when we use statistical methods to determine if an observed difference between control and experimental groups is a random occurrence or a specific effect, we conventionally consider a p value of less than or equal to 5% as statistically significant; that is, there is a less than 0.05 probability that the effect is random. The efficacy of this arbitrary convention has been debated for decades; suffice to say that despite questioning the validity of that convention, a P value of < 0.05 reflects our acceptance of the subjectivity of our perception of reality.

… controls are essential for the unbiased, objective observation and measurement of the dependent variable in response to the experimental setup.

Thus, if we do away with hypothesis‐testing science in favor of informatics based on data and statistics—referring to Anderson's suggestion—it reflects our acceptance of the noise in the system. However, mere data analysis without any underlying hypothesis is tantamount to “garbage in‐garbage out”, in contrast to well‐controlled imaginative experiments to separate the wheat from the chaff. Albert Einstein was quoted as saying that imagination was more important than knowledge.

The ultimate purpose of the scientific method is to understand ourselves and our place in Nature. Conventionally, we subscribe to the Anthropic Principle, that we are “in” this Universe, whereas the Endosymbiosis Theory, advocated by Lynn Margulis, stipulates that we are “of” this Universe as a result of the assimilation of the physical environment. According to this theory, the organism endogenizes external factors to make them physiologically “useful”, such as iron as the core of the hemoglobin molecule, or ancient bacteria as mitochondria.

… there is a fundamental difference between knowing via believing and knowing based on empirical research.

By applying the developmental mechanism of cell–cell communication to phylogeny, we have revealed the interrelationships between cells and explained evolution from its origin as the unicellular state to multicellularity via cell–cell communication. The ultimate outcome of this research is that consciousness is the product of cellular processes and cell–cell communication in order to react to the environment and better anticipate future events 5 , 6 . Consciousness is an essential prerequisite for transcending the Explicate Order toward the Implicate Order via cellular sensory and cognitive systems that feed an ever‐expanding organismal knowledge about both the environment and itself.

It is here where the empirical approach to understanding nature comes in with its emphasis that knowledge comes only from sensual experience rather than innate ideas or traditions. In the context of the cell or higher systems, knowledge about the environment can only be gained by sensing and analyzing the environment. Empiricism is similar to an equation in which the variables and terms form a product, or a chemical reaction, or a biological process where the substrates, aka sensory data, form products, that is, knowledge. However, it requires another step—imagination, according to Albert Einstein—to transcend the Explicate Order in order to gain insight into the Implicate Order. Take for instance, Dmitri Ivanovich Mendeleev's Periodic Table of Elements: his brilliant insight was not just to use Atomic Number to organize it, but also to consider the chemical reactivities of the Elements by sorting them into columns. By introducing chemical reactivity to the Periodic Table, Mendeleev provided something like the “fourth wall” in Drama, which gives the audience an omniscient, god‐like perspective on what is happening on stage.

The capacity to transcend the subjective Explicate Order to approximate the objective Implicate Order is not unlike Eastern philosophies like Buddhism or Taoism, which were practiced long before the scientific method. An Indian philosopher once pointed out that the Hindus have known for 30,000 years that the Earth revolves around the sun, while the Europeans only realized this a few hundred years ago based on the work of Copernicus, Brahe, and Galileo. However, there is a fundamental difference between knowing via believing and knowing based on empirical research. A similar example is Aristotle's refusal to test whether a large stone would fall faster than a small one, as he knew the answer already 7 . Galileo eventually performed the experiment from the Leaning Tower in Pisa to demonstrate that the fall time of two objects is independent of their mass—which disproved Aristotle's theory of gravity that stipulated that objects fall at a speed proportional to their mass. Again, it demonstrates the power of empiricism and experimentation as formulated by Francis Bacon, John Locke, and others, over intuition and rationalizing.

Even if our scientific instruments provide us with objective data, we still need to apply our consciousness to evaluate and interpret such data.

Following the evolution from the unicellular state to multicellular organisms—and reverse‐engineering it to a minimal‐cell state—reveals that biologic diversity is an artifact of the Explicate Order. Indeed, the unicell seems to be the primary level of selection in the Implicate Order, as it remains proximate to the First Principles of Physiology, namely negative entropy (negentropy), chemiosmosis, and homeostasis. The first two principles are necessary for growth and proliferation, whereas the last reflects Newton's Third Law of Motion that every action has an equal and opposite reaction so as to maintain homeostasis.

All organisms interact with their surroundings and assimilate their experience as epigenetic marks. Such marks extend to the DNA of germ cells and thus change the phenotypic expression of the offspring. The offspring, in turn, interacts with the environment in response to such epigenetic modifications, giving rise to the concept of the phenotype as an agent that actively and purposefully interacts with its environment in order to adapt and survive. This concept of phenotype based on agency linked to the Explicate Order fundamentally differs from its conventional description as a mere set of biologic characteristics. Organisms’ capacities to anticipate future stress situations from past memories are obvious in simple animals such as nematodes, as well as in plants and bacteria 8 , suggesting that the subjective Explicate Order controls both organismal behavior and trans‐generational evolution.

That perspective offers insight to the nature of consciousness: not as a “mind” that is separate from a “body”, but as an endogenization of physical matter, which complies with the Laws of Nature. In other words, consciousness is the physiologic manifestation of endogenized physical surroundings, compartmentalized, and made essential for all organisms by forming the basis for their physiology. Endocytosis and endocytic/synaptic vesicles contribute to endogenization of cellular surroundings, allowing eukaryotic organisms to gain knowledge about the environment. This is true not only for neurons in brains, but also for all eukaryotic cells 5 .

Such a view of consciousness offers insight to our awareness of our physical surroundings as the basis for self‐referential self‐organization. But this is predicated on our capacity to “experiment” with our environment. The burgeoning idea that we are entering the Anthropocene, a man‐made world founded on subjective senses instead of Natural Laws, is a dangerous step away from our innate evolutionary arc. Relying on just our senses and emotions, without experimentation and controls to understand the Implicate Order behind reality, is not just an abandonment of the principles of the Enlightenment, but also endangers the planet and its diversity of life.

Acknowledgements

John Torday has been a recipient of NIH Grant HL055268. František Baluška is thankful to numerous colleagues for very stimulating discussions on topics analyzed in this article.

EMBO Reports (2019) 20 : e49110 [ PMC free article ] [ PubMed ] [ Google Scholar ]

Contributor Information

John S Torday, Email: ude.alcu@yadrotj .

František Baluška, Email: ed.nnob-inu@aksulab .

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Understanding Controlled Experiments

1. introduction: the scientific method.

The scientific method is typically taught as a step-by-step sequence. Drag the steps below, listed in alphabetical order, into an order that matches the steps described in the table.

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[h] Steps of the Scientific Method


	This is where it begins: Sensing the world, and noticing patterns and relationships
	This stage involves making an educated guess that includes a prediction,
	This phase involves a structured form of observation that allows you to examine one thing at a time.
	This last stage involves answering questions such as 1) Was the hypothesis correct? 2) Are there other lines of evidence that point in the same direction?

[l] Drawing conclusions

[f*] Correct!

[fx] No. Please try again.

[l] Formulating hypotheses

[l] Making observations

[f*] Excellent!

[fx] No, that’s not correct. Please try again.

[l] Performing experiments

[f*] Great!

2. Interactive Reading: A Case Study: The link between cancer and smoking. Initial observations

To learn about the scientific method and experimentation, we’ll look at a very simplified history of the discovery of the link between smoking tobacco and cancer. 1

1 For a detailed view of this story, follow the links to tobaccocontrol.bmj.com at the end of this tutorial. Much of the information below comes from that site.

[qwiz qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments 1: Cancer and Smoking 1″]

[h]Interactive Reading: The Link between Cancer and Smoking

[i]Carefully read what follows, dragging in the words on top to the right place.

[q labels = “top”]

It hasn’t always been known that smoking tobacco caused lung cancer. In the 1500s, tobacco was praised for its supposed health benefits. Lung cancer itself was once extremely _______ . But mechanical production of cigarettes, free distribution of cigarettes to soldiers, and mass marketing caused a global lung cancer ____________ that began in the 1900s and continues today.

The first observations of the connection started around 1900. The key observation was the rise in _______ cancer rates. Among the first to notice this connection was a German medical student, Hermann Rottman, who noticed higher rates of lung cancer among German __________ workers. Rottman suspected that exposure to tobacco dust was causing cancer.

[l] epidemic

[l] tobacco

By the 1920s, the increasing rate of lung cancer began to be linked with _________ , but other possible causes for increased lung cancer rates were also considered. These included exposure to poison gas suffered by soldiers during World War One and exposure to the tar that was increasingly used on roads as driving became more common.

In the 1930s, population studies in German hospitals led to the discovery that lung cancer patients were far ___________ to have smoked than patients who didn’t have cancer. By the 1950s, American doctors were able to calculate that “smokers of 35 cigarettes per day increased their odds of ________ from lung cancer by a factor of 40.” (tobaccocontrol.bmj.com).

So, by that point there was a clear __________ : if someone smokes, then they have a higher chance of developing lung cancer. Now let’s look at how experiments could be designed to confirm that hypothesis.

[l] hypothesis

[l] more likely

[l] smoking

3. Controlled Experiments: General Features

For the sake of simplicity (and learning), the experiment described below is somewhat different from the actual animal experiments that were performed to help establish the link between tobacco smoke and cancer.

Let’s start by reviewing what an experiment is: it’s a controlled form of observation that lets you observe one thing at a time. As you read what follows, refer to the diagram below.

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[h]Quiz: Controlled Experiments, General Features

[q] Experiments try to test the effect of ONE thing at a time. The thing that you test is called the independent variable.

In relationship to our hypothesis ( if someone smokes, they have a higher chance of developing lung cancer) , what’s the independent variable?

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[q]Because we’re testing a harmful substance, we’re not going to test humans, but animals related to humans (like mice or rats). Keep that in mind when we talk about “groups” and “individuals” below.

the standard for comparison.
not exposed to the independent variable.
The second group is the experimental group . This group gets exposed to the independent variable.

In relationship to our hypothesis about smoking and cancer, what will be our control group?

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[q] What’s the experimental group?

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[q]An experiment is going to have some observable outcome. That outcome is called the dependent variable. In relationship to our hypothesis ( if someone smokes, they have a higher chance of developing lung cancer) , what’s the dependent variable?

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4. Scientific Method and Experimental Design Flashcards

To make sure you understand the key terms we’ve used in this lesson, work through these flashcards. Flashcards can feel very difficult, but they’re incredibly effective in helping you to remember what you’ve learned. Be very honest with yourself as you use these cards. It’s much better to study a card twice than to rush through without learning the material.

Click here to start flashcard deck [qdeck style=”width: 528px; border: 2px solid black; ” qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments Flashcards”]

[h] Flashcards: The Scientific Method and Controlled Experiments

[i] Instructions.

Click ‘Flip’ to see the answer to each card.
If you know it, click ‘Got it.”
If you don’t know it as well as you’d like, click ‘Need more practice,’ and that card will go to the bottom of the deck so you can practice it again.
‘Shuffle’ lets you shuffle the deck.

[!]Card 1++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q] The step in the scientific method that involves sensing the world, and noticing patterns and relationships is [textentry]

[a]The step in the scientific method that involves sensing the world, and noticing patterns and relationships is observation.

[!] CARD 2++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]An educated guess that includes a prediction is a _______________

[textentry] [a]An educated guess that includes a prediction is a hypothesis .

[!] CARD 3++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A structured form of observation that allows you to examine one thing at a time is a(n) _______________

[textentry] [a]A structured form of observation that allows you to examine one thing at a time is a(n) experiment

[!] CARD 5++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]An experiment tests the validity (or correctness) of a(n) _______________

[textentry] [a]An experiment tests the validity of a hypothesis .

[!] CARD 6++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A well-formulated hypothesis includes a __________

[textentry] [a]A well-formulated hypothesis includes a prediction

[!] CARD 7++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]The thing you test in an experiment is the _________

[textentry] [a]The thing you test in an experiment is the independent variable

[!] CARD 8++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]The measured or observed result of the independent variable is the ___________

[textentry] [a]The measured or observed result of the independent variable is the dependent variable.

[!] CARD 9++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A student performs an experiment to test the effect of red light on plant growth. The independent variable is ________

[textentry]

[a]A student performs an experiment to test the effect of red light on plant growth. The independent variable is red light

[!] CARD 10++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. What would be a logical control group?

[a]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. A logical control group would be plants exposed to normal light.

[!] CARD 11++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[a]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. A logical experimental group would be plants exposed to red light.

If you want more practice, please press the restart button below. Otherwise, follow the links below. [restart] [/qdeck]

5. A controlled experiment to test the smoking/cancer connection

So, how would this work in the case of an animal experiment to test the hypothesis that tobacco smoke causes cancer?

Well, if it’s an animal experiment, we need an animal.

Like humans, rats are mammals. Their internal organs, including their lungs, look very much like miniature versions of those in humans. In terms of body chemistry, they’re also very much like us: many of the chemical reactions occurring in our cells are identical. So the reasoning (which is widely accepted in biology) is that if something causes cancer in a rat, it is likely to cause cancer in a human being.

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[h]Using the Scientific method

[q]So here’s our experiment. We’re going to have two rats. In one group, we’ll have a rat that smokes. In the second group, we’ll have a rat that’s exposed to exactly the same conditions (the same food, temperature, etc.). The only difference is that the second rat won’t smoke.


a non-smoking rat	a smoking rat

What’s the problem with this experiment?

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[q]So, here’s what we’re going to do: We’re going to use two groups of rats, each with enough individuals to show the effect of the independent variable. One group will be exposed to tobacco smoke. A second group will be kept under identical conditions, except for the fact that it won’t be exposed to tobacco smoke. We’re going to measure the rate of cancer in each group, and see if there’s a difference.

If there is a difference, we can be pretty sure that it’s a result of the presence of the independent variable (tobacco smoke). This difference, because it depends on the effect of the independent variable, is called the dependent variable.

What’s the control group in this experiment?

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What’s the experimental group in this experiment?

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What’s the dependent variable in this experiment?

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[q]What’s the independent variable in this experiment?

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[f]Tm8uIFRoZSByYXRlIG9mIGx1bmcgY2FuY2VywqBpcyB0aGUgZGVwZW5kZW50wqB2YXJpYWJsZS7CoFRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZSBpc8KgdGhlIHRoaW5nIHRoYXQgd2UmIzgyMTc7cmUgdGVzdGluZy4gV2hhdCBhcmUgd2UgdGVzdGluZyBpbiB0aGlzIGV4cGVyaW1lbnQ/[Qq]

6. What Happened Next

Animal studies like the one described above confirmed the hypothesis that rats exposed to tobacco smoke will have higher rates of cancer. In fact, this had been known since the 1930s, when controlled experiments showed that elements of tobacco smoke, when put into liquid form, could cause tumors to form on the skin of rabbits.

Throughout the 1900s, several lines of evidence confirmed the tobacco/cancer link. These lines of evidence included

Chemical analysis of tobacco to identify cancer-causing agents,
Studies of how cells in lung tissue were affected by smoking, and
Public health studies showing that people who smoked were more likely to develop lung cancer.

However, through much of the 1900s, smoking continued to increase among many populations around the world. This was largely caused by tobacco companies, which continued to market cigarettes, and which devoted significant amounts of resources to denying the scientific evidence about the danger of smoking. You can read the entire story by following the links at the bottom of this tutorial.

7. Checking Understanding Quiz

In this tutorial, we’ve learned about

Hypothesize
Draw conclusions
independent variable
dependent variable
control group
experimental group
It tests only one thing (the independent variable)
It uses large enough groups to avoid random results based on individual differences.

To make sure you’ve mastered this material, take the quiz below.

[qwiz style = “border: 3px solid black; ” qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments: Checking Understanding”]

[h]Quiz: The Scientific Method and Designing Experiments [i] Here’s how the quiz works:

Each question is multiple-choice, but the entire quiz is like a series of flashcards.
If you get the question right, it comes off the deck.
If you get the question wrong, it goes to the bottom of the deck, so you can try it again.

[q] Noticing patterns in the world around you is best classified as

[c]bWFraW5nIGFuIG 9ic2VydmF0aW9u[Qq]

[c]YXNraW5nIGEgcXVlc3Rpb24=[Qq]

[c]Zm9ybXVsYXRpbmcgYSBoeXBvdGhlc2lz[Qq]

[c]cGVyZm9ybWluZyBhbiBleHBlcmltZW50[Qq]

[f]IFllcy7CoE5vdGljaW5nIHBhdHRlcm5zIGluIHRoZSB3b3JsZCBhcm91bmQgeW91IGlzIGJlc3QgY2xhc3NpZmllZCBhc8Kg bWFraW5nIGFuIG9ic2VydmF0aW9uLg== [Qq] [f]IE5vLsKgTm90aWNpbmcgcGF0dGVybnMgaXMgdGhlIGZpcnN0IHN0ZXAgaW4gdGhlIHNjaWVudGlmaWMgbWV0aG9kLCBldmVuIGJlZm9yZSBhc2tpbmcgcXVlc3Rpb25zLg==[Qq] [f]wqBOby4gTm90aWNpbmcgcGF0dGVybnMgaXMgdGhlIGZpcnN0IHN0ZXAgaW4gdGhlIHNjaWVudGlmaWMgbWV0aG9kLiBXaGF0IGlzIHRoYXQgZmlyc3Qgc3RlcD8=[Qq] [f]wqBOby7CoE5vdGljaW5nIHBhdHRlcm5zIGlzIHRoZSBmaXJzdCBzdGVwIGluIHRoZSBzY2llbnRpZmljIG1ldGhvZC4gV2hhdCBpcyB0aGF0IGZpcnN0IHN0ZXA/

[q] An educated guess that includes a prediction is a(n)

[c]IG9ic2VydmF0aW9u[Qq]

[c]wqBoeXBv dGhlc2lz[Qq]

[c]IGV4cGVyaW1lbnQ=[Qq]

[f]wqBOby7CoE9ic2VydmF0aW9ucyBsZWFkIHRvIHF1ZXN0aW9ucy4gQWZ0ZXIgcXVlc3Rpb25zLCB3ZSBmb3JtdWxhdGUgZWR1Y2F0ZWQgZ3Vlc3Nlcy4gV2hhdCBhcmUgdGhlc2UgY2FsbGVkPw==[Qq] [f]IEV4Y2VsbGVudCHCoEFuIGVkdWNhdGVkIGd1ZXNzIHRoYXQgaW5jbHVkZXMgYSBwcmVkaWN0aW9uIGlzIGHCoA== aHlwb3RoZXNpcy4= [Qq] [f]wqBOby4gRXhwZXJpbWVudHMgYXJlIHBlcmZvcm1lZCBpbiBvcmRlciB0byBwcm92ZSBhIF9fX19fX19fX19fX19fLg==

[q] A structured form of observation that allows you to observe one thing at a time is a(n)

[c]wqBoeXBvdGhlc2lz[Qq]

[c]IGV4cGVy aW1lbnQ=[Qq]

[f]wqBOby7CoEFuIG9ic2VydmF0aW9uIGlzIHNpbXBseSBzZW5zaW5nIHRoZSB3b3JsZC4gVGhlIHNwZWNpYWwga2luZCBvZiBvYnNlcnZhdGlvbiBkZXNjcmliZWQgYWJvdmUgd291bGQgZm9sbG93IGZvcm11bGF0aW9uIG9mIGEgaHlwb3RoZXNpcy4gV2hhdCBmb2xsb3dzwqBhIGh5cG90aGVzaXM/[Qq] [f]wqBOby4gQSBoeXBvdGhlc2lzIGlzIGFuIGVkdWNhdGVkIGd1ZXNzIHRoYXQgaW5jbHVkZXMgYSBwcmVkaWN0aW9uLiBZb3UmIzgyMTc7cmUgbG9va2luZyBmb3IgdGhlIGFjdGl2aXR5IHRoZSBpcyB1c2VkIHRvIGNvbmZpcm0gYSBoeXBvdGhlc2lzLg==[Qq] [f]IE5pY2UuwqBBIHN0cnVjdHVyZWQgZm9ybSBvZiBvYnNlcnZhdGlvbiB0aGF0IGFsbG93cyB5b3UgdG8gb2JzZXJ2ZSBvbmUgdGhpbmcgYXQgYSB0aW1lIGlzIGFuIA== ZXhwZXJpbWVudC4=

[q] This includes a prediction, and is best put in an “if…then…” format

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[q] This part of the scientific method involves testing whether a hypothesis is correct.

[c]b2JzZXJ2YXRpb24=[Qq]

[c]ZHJhd2luZyBhIGNvbmNsdXNpb24=[Qq]

[c]ZXhwZXJp bWVudA==[Qq]

[f]Tm8uwqBBbiBvYnNlcnZhdGlvbsKgY29tZXMgYmVmb3JlIGZvcm11bGF0aW5nIGEgaHlwb3RoZXNpcyAobXVjaCBsZXNzIHRlc3RpbmcgaXQpLg==[Qq] [f]Tm8uwqBZb3UgY2FuJiM4MjE3O3QgZHJhdyBhIGNvbmNsdXNpb24gdW50aWwgeW91JiM4MjE3O3ZlIGNvbmZpcm1lZCBhIGh5cG90aGVzaXMuIEhvdyBkbyB5b3UgY29uZmlybSBhIGh5cG90aGVzaXM/[Qq] [f]WWVzLsKgQW4gZXhwZXJpbWVudCBpcyBkZXNpZ25lZCB0byBjb25maXJtIHdoZXRoZXIgYSBoeXBvdGhlc2lzIGlzIGNvcnJlY3Qgb3Igbm90

[q]In an experiment, the thing you’re testing is the

[c]aW5kZXBlbmRlbn QgdmFyaWFibGU=[Qq]

[c]ZGVwZW5kZW50IHZhcmlhYmxl[Qq]

[c]Y29udHJvbCBncm91cA==[Qq]

[c]ZXhwZXJpbWVudGFsIGdyb3Vw[Qq]

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[f]Tm8uIFRoZSBleHBlcmltZW50YWwgZ3JvdXAgaXMgdGhlIGdyb3VwIHRoYXQgaXMgZXhwb3NlZCB0byB0aGUgaW5kZXBlbmRlbnQgdmFyaWFibGUuwqBBbmQgaWYgeW91IGxvb2sgY2xvc2VseSwgeW91JiM4MjE3O2xsIHNlZSB0aGF0IEkganVzdCBnYXZlIGF3YXkgdGhlIGFuc3dlciB0byB0aGlzIHF1ZXN0aW9uLg==

[q]In an experiment, the measured result is the

[c]aW5kZXBlbmRlbnQgdmFyaWFibGU=[Qq]

[c]ZGVwZW5kZW50 IHZhcmlhYmxl[Qq]

[f]Tm8uwqBJbiBhbiBleHBlcmltZW50LCB0aGUgaW5kZXBlbmRlbnQgdmFyaWFibGUgaXMgdGhlIHRoaW5nIHlvdSYjODIxNztyZSB0ZXN0aW5nLg==[Qq] [f]WWVzLsKgVGhlIGRlcGVuZGVudCB2YXJpYWJsZSBpcyB0aGUgcmVzdWx0IHlvdSBnZXQu[Qq] [f]Tm8uIFRoZSBjb250cm9sIGdyb3VwIGlzIHRoZSBncm91cCB0aGF0IGlzIE5PVCBleHBvc2VkIHRvIHRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZS4gVGhpcyBxdWVzdGlvbiBpcyBhc2tpbmcgeW91IGFib3V0IHJlc3VsdHMu

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[q]The part of the experiment that serves as a standard for comparison, and which shows you what the result would be without the independent variable, is the

[c]aHlwb3RoZXNpcw==[Qq]

[c]Y29udHJvbC Bncm91cA==[Qq]

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[q]Two students have designed an experiment to test the effect of loud bass notes on reproduction rates in guppies (a small aquarium fish). They divide the guppies into two groups of 15, each group in its own 20-gallon aquarium tank. One tank is exposed to the loud bass notes, and one is not.

In this experiment, which of the following is the independent variable?

[c]dGhlIGd1cHBpZXMgZXhwb3NlZCB0byB0aGUgbG93wqBiYXNzIG5vdGVzLg==[Qq]

[c]dGhlIGd1cHBpZXMgTk9UwqBleHBvc2VkIHRvIHRoZSBsb3fCoGJhc3Mgbm90ZXMu[Qq]

[c]dGhlIGxvd8KgYm FzcyBub3Rlcy4=[Qq]

[c]dGhlIHJhdGUgb2YgcmVwcm9kdWN0aW9u[Qq]

[f]Tm8uwqBUaGUgaW5kZXBlbmRlbnQgdmFyaWFibGUgaXMgdGhlIHRoaW5nIHlvdSYjODIxNztyZSB0ZXN0aW5nLiBXaGF0JiM4MjE3O3MgYmVpbmcgdGVzdGVkPw==[Qq] [f]Tm8uwqBUaGUgaW5kZXBlbmRlbnQgdmFyaWFibGUgaXMgdGhlIHRoaW5nIHlvdSYjODIxNztyZSB0ZXN0aW5nLiBXaGF0JiM4MjE3O3MgYmVpbmcgdGVzdGVkPw==[Qq] [f]WWVzLiBUaGUgaW5kZXBlbmRlbnQgdmFyaWFibGUgaXMgdGhlIHRoaW5nIHlvdSYjODIxNztyZSB0ZXN0aW5nLiBXaGF0JiM4MjE3O3MgYmVpbmcgdGVzdGVkIGhlcmUgaXMgdGhlIGxvdy1mcmVxdWVuY3kgc291bmQu

[f]Tm8uIFRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZSBpcyB0aGUgdGhpbmcgeW91JiM4MjE3O3JlIHRlc3RpbmcuIFdoYXQmIzgyMTc7cyBiZWluZyB0ZXN0ZWQ/

[q]Two students have designed an experiment to test the effect of low bass notes on reproduction rates in guppies (a small aquarium fish). They divide the guppies into two groups of 15, each group in its own 20-gallon aquarium tank. One tank is exposed to the low bass notes, and one is not.

In this experiment, which of the following is the dependent variable?

[c]dGhlIGd1cHBpZXMgZXhwb3NlZCB0byB0aGUgbG93wqBiYXNzIG5vdGVz[Qq]

[c]dGhlIGd1cHBpZXMgTk9UwqBleHBvc2VkIHRvIHRoZSBsb3fCoGJhc3Mgbm90ZXM=[Qq]

[c]dGhlIGxvd8KgYmFzcyBub3Rlcw==[Qq]

[c]dGhlIHJhdGUgb2Yg cmVwcm9kdWN0aW9u[Qq]

[f]Tm8uwqBUaGUgZGVwZW5kZW50IHZhcmlhYmxlIGlzIHRoZSByZXN1bHQgeW91IGdldC4gVGhlc2UgZXhwZXJpbWVudGVycyB3YW50IHRvIHNlZSBpZiBsb3cgYmFzcyBub3Rlc8KgYWZmZWN0IHNvbWV0aGluZy4gV2hhdCBpcyB0aGF0IHNvbWV0aGluZz8=[Qq] [f]Tm8uwqBUaGUgZGVwZW5kZW50IHZhcmlhYmxlIGlzIHRoZSByZXN1bHQgeW91IGdldC4gVGhlc2UgZXhwZXJpbWVudGVycyB3YW50IHRvIHNlZSBpZiBsb3cgYmFzcyBub3Rlc8KgYWZmZWN0IHNvbWV0aGluZy4gV2hhdCBpcyB0aGF0IHNvbWV0aGluZz8=[Qq] [f]Tm8uwqBUaGUgZGVwZW5kZW50IHZhcmlhYmxlIGlzIHRoZSByZXN1bHQgeW91IGdldC4gVGhlc2UgZXhwZXJpbWVudGVycyB3YW50IHRvIHNlZSBpZiBsb3cgYmFzZSBub3RlcyBhZmZlY3Qgc29tZXRoaW5nLiBXaGF0IGlzIHRoYXQgc29tZXRoaW5nPw==

[f]WWVzLsKgVGhlIGRlcGVuZGVudCB2YXJpYWJsZSBpcyB0aGUgcmVzdWx0IHlvdSBnZXQuIFRoZXNlIGV4cGVyaW1lbnRlcnMgd2FudCB0byBzZWUgaWYgbG93IGJhc3PCoG5vdGVzIGFmZmVjdCByZXByb2R1Y3Rpb24gcmF0ZXMuIFRoZXJlZm9yZSByZXByb2R1Y3Rpb24gcmF0ZXMgYXJlIHRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZS4=

In this experiment, which of the following is the control group ?

[c]dGhlIGd1cHBpZXMgZXhwb3NlZCB0byB0aGUgbG93IGJhc3Mgbm90ZXM=[Qq]

[c]dGhlIGd1cHBpZXMgTk9UwqBleHBvc2Vk IHRvIHRoZSBsb3cgYmFzcyBub3Rlcw==[Qq]

[c]dGhlIGxvdyBiYXNzIG5vdGVz[Qq]

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In this experiment, which of the following is the experimental group ?

[c]dGhlIGd1cHBpZXMgZXhwb3NlZCB0 byB0aGUgbG93IGJhc3Mgbm90ZXM=[Qq]

[f]WWVzLiBUaGUgZXhwZXJpbWVudGFswqBncm91cCBpcyB0aGUgZ3JvdXAgdGhhdCA= aXPCoGV4cG9zZWQgdG8gdGhlIGluZGVwZW5kZW50IHZhcmlhYmxlLsKg SW4gdGhpcyBleHBlcmltZW50LCB0aGUgaW5kZXBlbmRlbnQgdmFyaWFibGUgaXMgdGhlIGxvd8KgYmFzcyBub3RlcywgYW5kIHRoZSBndXBwaWVzIGV4cG9zZWQgdG8gdGhpcyBzb3VuZCBtYWtlIHVwIHRoZSBleHBlcmltZW50YWwgZ3JvdXAu[Qq] [f]Tm8uIFRoZSBleHBlcmltZW50YWzCoGdyb3VwIGlzIHRoZSBncm91cCB0aGF0IA== aXMgZXhwb3NlZCB0byB0aGUgaW5kZXBlbmRlbnQgdmFyaWFibGUuIEp1c3QgZmlndXJlIG91dCB3aGF0IHRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZSBpcyAoaXQmIzgyMTc7cyB3aGF0IHlvdSYjODIxNztyZSB0ZXN0aW5nKSwgYW5kIHlvdSYjODIxNztsbCBoYXZlIHlvdXIgYW5zd2VyLsKg [Qq] [f]Tm8uIFRoZSBleHBlcmltZW50YWzCoGdyb3VwIGlzIHRoZSBncm91cCB0aGF0IA== aXMgZXhwb3NlZCB0byB0aGUgaW5kZXBlbmRlbnQgdmFyaWFibGUuIEp1c3QgZmlndXJlIG91dCB3aGF0IHRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZSBpcyAoaXQmIzgyMTc7cyB3aGF0IHlvdSYjODIxNztyZSB0ZXN0aW5nKSwgYW5kIHlvdSYjODIxNztsbCBoYXZlIHlvdXIgYW5zd2VyLg==

[f]Tm8uIFRoZSBleHBlcmltZW50YWzCoGdyb3VwIGlzIHRoZSBncm91cCB0aGF0IA== aXMgZXhwb3NlZCB0byB0aGUgaW5kZXBlbmRlbnQgdmFyaWFibGUuIEp1c3QgZmlndXJlIG91dCB3aGF0IHRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZSBpcyAoaXQmIzgyMTc7cyB3aGF0IHlvdSYjODIxNztyZSB0ZXN0aW5nKSwgYW5kIHlvdSYjODIxNztsbCBoYXZlIHlvdXIgYW5zd2VyLg==

[q]Bob wants to test whether lemon juice can keep dandelion weeds from growing in his garden. He creates several solutions of lemon juice. He then takes dandelion seeds and sprouts them on paper towels. Each day, he sprays the same amount of each solution on the seeds. The data are shown above.

Solution	Number of Seeds	Percentage of seedlings that sprout
10% lemon juice	15	42%
30% lemon juice	15	44%
50% lemon juice	15	41%

Based on the data, what’s the problem with the design of Bob’s experiment

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[c]SGUgaGFzIG1vcmUgdGhhbiBvbmXCoGluZGVwZW5kZW50IHZhcmlhYmxl[Qq]

[c]SGUgaGFkIG5vIGNv bnRyb2wgZ3JvdXA=[Qq]

[c]dGhlIHNhbXBsZSBzaXplIGlzIHRvbyBzbWFsbA==[Qq]

[f]Tm8uwqBUaGXCoGRlcGVuZGVudCB2YXJpYWJsZSBpcyB0aGUgb3V0Y29tZSwgYW5kIEJvYiYjODIxNztzIGV4cGVyaW1lbnQgaGFzIGEgY2xlYXIgb3V0Y29tZSAodGhlIHBlcmNlbnRhZ2Ugb2Ygc2VlZHMgc3Byb3V0aW5nKQ==[Qq] [f]Tm8uIEhlJiM4MjE3O3MgdGVzdGluZyB2YXJpb3VzIGNvbmNlbnRyYXRpb25zIG9mIHRoZSBzYW1lIHRoaW5nLCB3aGljaCBpcyBhIGZpbmUgcHJvY2VkdXJlLg==[Qq] [f]WWVzLsKgVGhlcmUmIzgyMTc7cyBubyBjb250cm9sIGdyb3VwLiBXaXRob3V0IGEgY29udHJvbCBncm91cCwgaXQmIzgyMTc7cyBpbXBvc3NpYmxlIHRvIGtub3cgd2hldGhlciBoYXZpbmcgYWJvdXQgNDAlIG9mIHNlZWRsaW5ncyBzcHJvdXRpbmcgaXMgYSByZXN1bHQgb2YgdGhlIGxlbW9uIGp1aWNlLCBvciB3aGV0aGVyIHRoYXQmIzgyMTc7cyBub3JtYWwgZm9yIGRhbmRlbGlvbiBzZWVkcy4=

[f]Tm8gKGJ1dCB0aGF0JiM4MjE3O3MgYSBzbWFydCByZXNwb25zZSkuIEl0IHRha2VzIGEgbG90IG9mIHN0YXRpc3RpY2FsIGtub3dsZWRnZSB0byBkZXRlcm1pbmUgdGhlIHJpZ2h0IHNhbXBsZSBzaXplLiAxNSBtaWdodCBiZSBva2F5LiBCdXQsIHRoZXJlJiM4MjE3O3MgYSBtdWNoIGJpZ2dlciBwcm9ibGVtIHdpdGggdGhpcyBleHBlcmltZW50Lg==

[q]Clara is testing whether iron pills will help skinny dogs gain weight. For her experiment, she takes three dogs, a poodle, a boxer, and a collie. She adds iron to their food for two weeks and then records their weight. Here are her results

Dog Breed	Number of 5-gram iron pills	Weight gain (kilograms)
Poodle	1	4
Boxer	3	2
Collie	5	6

Based on the data, what’s the problem with the design of her experiment

[c]U2hlIGhhZCBubyBkZXBlbmRlbnQgdmFyaWFibGU=[Qq]

[c]U2hlIGhhcyBtb3JlIHRoYW4gb25lwq BpbmRlcGVuZGVudCB2YXJpYWJsZQ==[Qq]

[c]U2hlIGhhcyBhIGNsZWFyIGJpYXMgdG93YXJkIENvbGxpZXMu[Qq]

[f]Tm8uwqBUaGXCoGRlcGVuZGVudCB2YXJpYWJsZSBpcyB0aGUgb3V0Y29tZSwgYW5kIENsYXJhJiM4MjE3O3PCoGV4cGVyaW1lbnQgaGFzIGEgY2xlYXIgb3V0Y29tZSAod2VpZ2h0IGdhaW4pLiBUaGluayBhYm91dCBob3cgbWFueSB0aGluZ3Mgc2hlJiM4MjE3O3MgdGVzdGluZy4=[Qq] [f]WWVzLiBTaGUmIzgyMTc7cyB1c2luZyBkb2dzIG9mIGEgZGlmZmVyZW50IGJyZWVkIGFuZCBnaXZpbmcgdGhlbSBhIGRpZmZlcmVudCBudW1iZXIgb2YgcGlsbHMsIHdoaWNoIG1lYW5zIHRoYXQgc2hlJiM4MjE3O3MgdGVzdGluZyBhdCBsZWFzdCB0d28gdGhpbmdzLg==[Qq] [f]Tm8uIFRoZXJlJiM4MjE3O3Mgbm8gZXZpZGVuY2XCoGZvciBjbGFpbWluZyB0aGF0IHNoZSYjODIxNztzIGJpYXNlZC4gQnV0IHRoaW5rIGFib3V0IGhvdyBtYW55IHRoaW5ncyBzaGUmIzgyMTc7cyB0ZXN0aW5nJiM4MjMwOw==

If you want to take this quiz again, click the button below

[/qwiz] If you need more practice, please scroll up to the top and work through this tutorial again. Otherwise, follow the links below:

8. The Scientific Method Song: Interactive Lyrics

This is an interactive reading of the lyrics to the Scientific Method Song . If you’re completing this tutorial on your own, and you want to watch the video, then click here (the link will open in a new tab). But if you’re in class, please check with your teacher first!

[qwiz qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments: Scientific Method Song, Interactive Lyrics”]

[h]Interactive Lyrics, Scientific Method Song

[q labels=”top”]

Science always begins with a ___________ Inspired by an ___________ , Next step, as you might surmise, Is to take your question and hypothesize,

A _____________ should include a prediction, An educated guess in a form of “if … then” Like if science rapping is a memory aid Then better retention will be displayed.

Now hypothesis set, you’re ready for next step Performance of an experiment, The independent variable’s what you __________ _____________ variable’s the result you get

[l] dependent

[l] observation

[l] question

[l] experiment

[l] hypothesize

[l] observe

Now science well-done’s about taking __________

Because clear results, that’s your ultimate goal.

To see if what you’re testing is the _______ of an effect,

Your design has to be perfect.

Use two groups: __________ and experimental: Experimental gets your independent variable Control group’s the same except for one move: The independent ____________ gets ______________ .

Like to prove tobacco smoke is a cause of cancer, A good experiment will bring you the answer, Take two groups of guinea pigs or rats to test And make the groups ______ , that’s statistically best

[l] control

[l] removed

[l] variable

You gotta make ’em big, cause there’s always random stuff, So a small group of ____________ is never enough! You can get cancer even though you’ve never smoked But a single __________ , well that’s just an anecdote.

So set up two cages exactly the same, Controlling variables is the name of the game, Experimental group to smoke gets exposed, Cause that’s the _______________ variable you proposed.

[l] independent

[l] subjects

[q] BRIDGE : But I’m not saying science is always the way to get to the _______ It won’t tell you whom to ______ or what path to pursue But amidst all this superstition and deceit It gives you a path to consult To cut through all the lies and confusion, And help you to come to your own __________

[l] conclusion

[l] difference

[l] examine

And sure it was second-hand smoke that you tested, So maybe your results will be ____________ . This happens to scientists all of the time, Whenever there’s a __________ in their design.

Last step: try to publish in a scientific ________________ , As you try to win science fame eternal. It’s a never-ending process, and it’s awfully demanding. But that’s how we build scientific ___________________

[l] contested

[l] journal

[l] understanding

9. Next steps (reading about “The Shameful Past…”)

Click the following link to read The Shameful Past: The history of the discovery of the cigarette-cancer link . ” This is the reading on page 3 of the student learning guide that goes with this module.
Return to the menu for Module 1: Biology, Core Concepts
Use the menu choices above to choose another module.

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Control Group

Reviewed by: BD Editors

Control Group Definition

In scientific experiments, the control group is the group of subject that receive no treatment or a standardized treatment. Without the control group, there would be nothing to compare the treatment group to. When statistics refer to something being “X times more likely to happen” they are referring to the difference in the measurement between the treatment and control group. The control group provides a baseline in the experiment. The variable that is being studied in the experiment is not changed or is limited to zero in the control group. This insures that the effects of the variable are being studied. Most experiments try to add the variable back in increments to different treatment groups, to really begin to discern the effects of the variable in the system.

Ideally, the control group is subject to the same exact conditions as the treatment groups. This insures that only the effects produced by the variable are being measured. In a study of plants, for instance, all the plants would ideally be in the same room, with the same light and air conditions. In biological studies, it is also important that the organisms in the treatment and control groups come from the same population. Ideally, the organisms would all be clones of each other, to reduce genetic differences. This is the case in many artificially selected lab species, which have been selected to be very similar to each other. This ensures that the results obtained are valid.

Examples of Control Group

Testing enzyme strength.

In a simple biological lab experiment, students can test the effects of different concentrations of enzyme. The student can prepare a stock solution of enzyme by spitting into a beaker. Human spit contains the enzyme amylase, which breaks down starches. The concentration of enzyme can be varied by dividing the stock solution and adding in various amounts of water. Once various solutions of different strength enzyme have been produced, the experiment can begin.

In several treatment beakers are placed the following ingredients: starch, iodine, and the different solutions of enzyme. In the control group, a beaker is filled with starch and iodine, but no enzyme. When iodine is in the presence of starch, it turns black. As the enzyme depletes the starch in each beaker, the solution clears up and is a lighter yellow or brown color. In this way, the student can tell how long the enzymes in each beaker take to completely process the same amount of substrate. The control group is important because it will tell the student if the starch breaks down without the enzyme, which it will, given enough time.

Testing Drugs and the Placebo Effect

When drugs are tested on humans, control groups are also used. Although control groups were just considered good science, they have found an interesting phenomena in drug trials. Oftentimes, control groups in drug trials consist of people who also have the disease or ailment, but who don’t receive the medicine being tested. Instead, to keep the control group the same as the treatment groups, the patients in the control group are also given a pill. This is a sugar pill usually and contains no medicine. This practice of having a control group is important for drug trial, because it validates the results obtained. However, the control groups have also demonstrated an interesting effect, known as the placebo effect

In some drug trials, where the control group is given a fake medicine, patients start to see results. Scientists call this the placebo effect, and as of yet it is mostly unexplained. Some scientists have suggested that people get better simply because they believed they were going to get better, but this theory remains untested. Other scientists claim that unknown variables in the experiment caused the patients to get better. This theory remains unproven, as well.

Related Biology Terms

Treatment Group – The group that receives the variable, or altered amounts of the variable.
Variable – The part of the experiment being studied which is changed, or altered, throughout the experiment.
Scientific Method – The steps scientist follow to ensure their results are valid and reproducible.
Placebo Effect – A phenomenon when patients in the control group experience the same effects as those in the treatment group, though no treatment was given.

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Controlled Experiment

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

This is when a hypothesis is scientifically tested.

In a controlled experiment, an independent variable (the cause) is systematically manipulated, and the dependent variable (the effect) is measured; any extraneous variables are controlled.

The researcher can operationalize (i.e., define) the studied variables so they can be objectively measured. The quantitative data can be analyzed to see if there is a difference between the experimental and control groups.

What is the control group?

In experiments scientists compare a control group and an experimental group that are identical in all respects, except for one difference – experimental manipulation.

Unlike the experimental group, the control group is not exposed to the independent variable under investigation and so provides a baseline against which any changes in the experimental group can be compared.

Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

Randomly allocating participants to independent variable groups means that all participants should have an equal chance of participating in each condition.

The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.

What are extraneous variables?

The researcher wants to ensure that the manipulation of the independent variable has changed the changes in the dependent variable.

Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.

Extraneous variables should be controlled were possible, as they might be important enough to provide alternative explanations for the effects.

controlled experiment extraneous variables

In practice, it would be difficult to control all the variables in a child’s educational achievement. For example, it would be difficult to control variables that have happened in the past.

A researcher can only control the current environment of participants, such as time of day and noise levels.

Why conduct controlled experiments?

Scientists use controlled experiments because they allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.

Controlled experiments also follow a standardized step-by-step procedure. This makes it easy for another researcher to replicate the study.

Key Terminology

Experimental group.

The group being treated or otherwise manipulated for the sake of the experiment.

Control Group

They receive no treatment and are used as a comparison group.

Ecological validity

The degree to which an investigation represents real-life experiences.

Experimenter effects

These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.

Demand characteristics

The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).

Independent variable (IV)

The variable the experimenter manipulates (i.e., changes) – is assumed to have a direct effect on the dependent variable.

Dependent variable (DV)

Variable the experimenter measures. This is the outcome (i.e., the result) of a study.

Extraneous variables (EV)

All variables that are not independent variables but could affect the results (DV) of the experiment. Extraneous variables should be controlled where possible.

Confounding variables

Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.

Random Allocation

Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.

Order effects

Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:

(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;

(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.

What is the control in an experiment?

In an experiment , the control is a standard or baseline group not exposed to the experimental treatment or manipulation. It serves as a comparison group to the experimental group, which does receive the treatment or manipulation.

The control group helps to account for other variables that might influence the outcome, allowing researchers to attribute differences in results more confidently to the experimental treatment.

Establishing a cause-and-effect relationship between the manipulated variable (independent variable) and the outcome (dependent variable) is critical in establishing a cause-and-effect relationship between the manipulated variable.

What is the purpose of controlling the environment when testing a hypothesis?

Controlling the environment when testing a hypothesis aims to eliminate or minimize the influence of extraneous variables. These variables other than the independent variable might affect the dependent variable, potentially confounding the results.

By controlling the environment, researchers can ensure that any observed changes in the dependent variable are likely due to the manipulation of the independent variable, not other factors.

This enhances the experiment’s validity, allowing for more accurate conclusions about cause-and-effect relationships.

It also improves the experiment’s replicability, meaning other researchers can repeat the experiment under the same conditions to verify the results.

Why are hypotheses important to controlled experiments?

Hypotheses are crucial to controlled experiments because they provide a clear focus and direction for the research. A hypothesis is a testable prediction about the relationship between variables.

It guides the design of the experiment, including what variables to manipulate (independent variables) and what outcomes to measure (dependent variables).

The experiment is then conducted to test the validity of the hypothesis. If the results align with the hypothesis, they provide evidence supporting it.

The hypothesis may be revised or rejected if the results do not align. Thus, hypotheses are central to the scientific method, driving the iterative inquiry, experimentation, and knowledge advancement process.

What is the experimental method?

The experimental method is a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.

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Control Group Definition and Examples

The control group is the set of subjects that does not receive the treatment in a study. In other words, it is the group where the independent variable is held constant. This is important because the control group is a baseline for measuring the effects of a treatment in an experiment or study. A controlled experiment is one which includes one or more control groups.

The experimental group experiences a treatment or change in the independent variable. In contrast, the independent variable is constant in the control group.
A control group is important because it allows meaningful comparison. The researcher compares the experimental group to it to assess whether or not there is a relationship between the independent and dependent variable and the magnitude of the effect.
There are different types of control groups. A controlled experiment has one more control group.

Control Group vs Experimental Group

The only difference between the control group and experimental group is that subjects in the experimental group receive the treatment being studied, while participants in the control group do not. Otherwise, all other variables between the two groups are the same.

Control Group vs Control Variable

A control group is not the same thing as a control variable. A control variable or controlled variable is any factor that is held constant during an experiment. Examples of common control variables include temperature, duration, and sample size. The control variables are the same for both the control and experimental groups.

Types of Control Groups

There are different types of control groups:

Placebo group : A placebo group receives a placebo , which is a fake treatment that resembles the treatment in every respect except for the active ingredient. Both the placebo and treatment may contain inactive ingredients that produce side effects. Without a placebo group, these effects might be attributed to the treatment.
Positive control group : A positive control group has conditions that guarantee a positive test result. The positive control group demonstrates an experiment is capable of producing a positive result. Positive controls help researchers identify problems with an experiment.
Negative control group : A negative control group consists of subjects that are not exposed to a treatment. For example, in an experiment looking at the effect of fertilizer on plant growth, the negative control group receives no fertilizer.
Natural control group : A natural control group usually is a set of subjects who naturally differ from the experimental group. For example, if you compare the effects of a treatment on women who have had children, the natural control group includes women who have not had children. Non-smokers are a natural control group in comparison to smokers.
Randomized control group : The subjects in a randomized control group are randomly selected from a larger pool of subjects. Often, subjects are randomly assigned to either the control or experimental group. Randomization reduces bias in an experiment. There are different methods of randomly assigning test subjects.

Control Group Examples

Here are some examples of different control groups in action:

Negative Control and Placebo Group

For example, consider a study of a new cancer drug. The experimental group receives the drug. The placebo group receives a placebo, which contains the same ingredients as the drug formulation, minus the active ingredient. The negative control group receives no treatment. The reason for including the negative group is because the placebo group experiences some level of placebo effect, which is a response to experiencing some form of false treatment.

Positive and Negative Controls

For example, consider an experiment looking at whether a new drug kills bacteria. The experimental group exposes bacterial cultures to the drug. If the group survives, the drug is ineffective. If the group dies, the drug is effective.

The positive control group has a culture of bacteria that carry a drug resistance gene. If the bacteria survive drug exposure (as intended), then it shows the growth medium and conditions allow bacterial growth. If the positive control group dies, it indicates a problem with the experimental conditions. A negative control group of bacteria lacking drug resistance should die. If the negative control group survives, something is wrong with the experimental conditions.

Bailey, R. A. (2008). Design of Comparative Experiments . Cambridge University Press. ISBN 978-0-521-68357-9.
Chaplin, S. (2006). “The placebo response: an important part of treatment”. Prescriber . 17 (5): 16–22. doi: 10.1002/psb.344
Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
Pithon, M.M. (2013). “Importance of the control group in scientific research.” Dental Press J Orthod . 18 (6):13-14. doi: 10.1590/s2176-94512013000600003
Stigler, Stephen M. (1992). “A Historical View of Statistical Concepts in Psychology and Educational Research”. American Journal of Education . 101 (1): 60–70. doi: 10.1086/444032

What Is A Controlled Experiment? Aren’t All Experiments Controlled?

Why should you experiment, how should you experiment, key parameters of a controlled experiment, is there such a thing as an uncontrolled experiment.

A procedure that helps you understand the influence of various factors that affect a result and the extent of their effect in a controlled environment.

Have you ever done science experiments that have numerous parameters you need to take care of to get an accurate result?

If so, I know exactly how that feels!

Most of the time, you won’t get a perfect value, but rather a value that is nearly correct. It can be so frustrating at times, as you need to take care of the amount of catalyst, the temperature, pressure and a million other things!

I wonder who found out that you need precisely ‘this’ thing in exactly ‘this’ amount to get ‘that’ thing! Well, over time, I’ve realized just how much important these parameters are. These values help us set up a controlled environment where the experiment can occur.

And while many people loathe doing lengthy experiments, scientists have performed these exact same experiments a million times to find the perfect mix of parameters that give a predictable result! Now that’s perseverance!!

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Independent/Dependent Variables

Definitions of Control, Constant, Independent and Dependent Variables in a Science Experiment

Why Should You Only Test for One Variable at a Time in an Experiment?

The point of an experiment is to help define the cause and effect relationships between components of a natural process or reaction. The factors that can change value during an experiment or between experiments, such as water temperature, are called scientific variables, while those that stay the same, such as acceleration due to gravity at a certain location, are called constants.

The scientific method includes three main types of variables: constants, independent, and dependent variables. In a science experiment, each of these variables define a different measured or constrained aspect of the system.

Constant Variables

Experimental constants are values that should not change either during or between experiments. Many natural forces and properties, such as the speed of light and the atomic weight of gold, are experimental constants. In some cases, a property can be considered constant for the purposes of an experiment even though it technically could change under certain circumstances. The boiling point of water changes with altitude and acceleration due to gravity decreases with distance from the earth, but for experiments in one location these can also be considered constants.

Sometimes also called a controlled variable. A constant is a variable that could change, but that the experimenter intentionally keeps constant in order to more clearly isolate the relationship between the independent variable and the dependent variable.

If extraneous variables are not properly constrained, they are referred to as confounding variables, as they interfere with the interpretation of the results of the experiment.

Some examples of control variables might be found with an experiment examining the relationship between the amount of sunlight plants receive (independent variable) and subsequent plant growth (dependent variable). The experiment should control the amount of water the plants receive and when, what type of soil they are planted in, the type of plant, and as many other different variables as possible. This way, only the amount of light is being changed between trials, and the outcome of the experiment can be directly applied to understanding only this relationship.

Independent Variable

The independent variable in an experiment is the variable whose value the scientist systematically changes in order to see what effect the changes have. A well-designed experiment has only one independent variable in order to maintain a fair test. If the experimenter were to change two or more variables, it would be harder to explain what caused the changes in the experimental results. For example, someone trying to find how quickly water boils could alter the volume of water or the heating temperature, but not both.

Dependent Variable

A dependent variable – sometimes called a responding variable – is what the experimenter observes to find the effect of systematically varying the independent variable. While an experiment may have multiple dependent variables, it is often wisest to focus the experiment on one dependent variable so that the relationship between it and the independent variable can be clearly isolated. For example, an experiment could examine how much sugar can dissolve in a set volume of water at various temperatures. The experimenter systematically alters temperature (independent variable) to see its effect on the quantity of dissolved sugar (dependent variable).

Control Groups

In some experiment designs, there might be one effect or manipulated variable that is being measured. Sometimes there might be one collection of measurements or subjects completely separated from this variable called the control group. These control groups are held as a standard to measure the results of a scientific experiment.

An example of such a situation might be a study regarding the effectiveness of a certain medication. There might be multiple experimental groups that receive the medication in varying doses and applications, and there would likely be a control group that does not receive the medication at all.

Representing Results

Identifying which variables are independent, dependent, and controlled helps to collect data, perform useful experiments, and accurately communicate results. When graphing or displaying data, it is crucial to represent data accurately and understandably. Typically, the independent variable goes on the x-axis, and the dependent variable goes on the y-axis.

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A control group in a scientific experiment is a group separated from the rest of the experiment, where the independent variable being tested cannot influence the results. This isolates the independent variable 's effects on the experiment and can help rule out alternative explanations of the experimental results. Control groups can also be separated into two other types: positive or negative. Positive control groups are groups where the conditions of the experiment are set to guarantee a positive result. A positive control group can show the experiment is functioning properly as planned. Negative control groups are groups where the conditions of the experiment are set to cause a negative outcome. Control groups are not necessary for all scientific experiments. Controls are extremely useful where the experimental conditions are complex and difficult to isolate.

Example of a Negative Control Group

Negative control groups are particularly common in science fair experiments , to teach students how to identify the independent variable. A simple example of a control group can be seen in an experiment in which the researcher tests whether or not a new fertilizer has an effect on plant growth. The negative control group would be the set of plants grown without the fertilizer, but under the exact same conditions as the experimental group. The only difference between the experimental group would be whether or not the fertilizer was used.

There could be several experimental groups, differing in the concentration of fertilizer used, its method of application, etc. The null hypothesis would be that the fertilizer has no effect on plant growth. Then, if a difference is seen in the growth rate of the plants or the height of plants over time, a strong correlation between the fertilizer and growth would be established. Note the fertilizer could have a negative impact on growth rather than a positive impact. Or, for some reason, the plants might not grow at all. The negative control group helps establish that the experimental variable is the cause of atypical growth, rather than some other (possibly unforeseen) variable.

Example of a Positive Control Group

A positive control demonstrates an experiment is capable of producing a positive result. For example, let's say you are examining bacterial susceptibility to a drug. You might use a positive control to make sure the growth medium is capable of supporting any bacteria. You could culture bacteria known to carry the drug resistance marker, so they should be capable of surviving on a drug-treated medium. If these bacteria grow, you have a positive control that shows other drug-resistance bacteria should be capable of surviving the test.

The experiment could also include a negative control. You could plate bacteria known not to carry a drug resistance marker. These bacteria should be unable to grow on the drug-laced medium. If they do grow, you know there is a problem with the experiment.

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control experiment

Definition of control experiment

Examples of control experiment in a sentence.

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'control experiment.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

1848, in the meaning defined above

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“Control experiment.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/control%20experiment. Accessed 20 Aug. 2024.

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Positive Control vs Negative Control: Differences & Examples

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positive control vs negative control, explained below

A positive control is designed to confirm a known response in an experimental design , while a negative control ensures there’s no effect, serving as a baseline for comparison.

The two terms are defined as below:

Positive control refers to a group in an experiment that receives a procedure or treatment known to produce a positive result. It serves the purpose of affirming the experiment’s capability to produce a positive outcome.
Negative control refers to a group that does not receive the procedure or treatment and is expected not to yield a positive result. Its role is to ensure that a positive result in the experiment is due to the treatment or procedure.

The experimental group is then compared to these control groups, which can help demonstrate efficacy of the experimental treatment in comparison to the positive and negative controls.

Positive Control vs Negative Control: Key Terms

Control groups.

A control group serves as a benchmark in an experiment. Typically, it is a subset of participants, subjects, or samples that do not receive the experimental treatment (as in negative control).

This could mean assigning a placebo to a human subject or leaving a sample unaltered in chemical experiments. By comparing the results obtained from the experimental group to the control, you can ascertain whether any differences are due to the treatment or random variability.

A well-configured experimental control is critical for drawing valid conclusions from an experiment. Correct use of control groups permits specificity of findings, ensuring the integrity of experimental data.

See More: Control Variables Examples

The Negative Control

Negative control is a group or condition in an experiment that ought to show no effect from the treatment.

It is useful in ensuring that the outcome isn’t accidental or influenced by an external cause. Imagine a medical test, for instance. You use distilled water, anticipating no reaction, as a negative control.

If a significant result occurs, it warns you of a possible contamination or malfunction during the testing. Failure of negative controls to stay ‘negative’ risks misinterpretation of the experiment’s result, and could undermine the validity of the findings.

The Positive Control

A positive control, on the other hand, affirms an experiment’s functionality by demonstrating a known reaction.

This might be a group or condition where the expected output is known to occur, which you include to ensure that the experiment can produce positive results when they are present. For instance, in testing an antibiotic, a well-known pathogen, susceptible to the medicine, could be the positive control.

Positive controls affirm that under appropriate conditions your experiment can produce a result. Without this reference, experiments could fail to detect true positive results, leading to false negatives. These two controls, used judiciously, are backbones of effective experimental practice.

Experimental Groups

Experimental groups are primarily characterized by their exposure to the examined variable.

That is, these are the test subjects that receive the treatment or intervention under investigation. The performance of the experimental group is then compared against the well-established markers – our positive and negative controls.

For example, an experimental group may consist of rats undergoing a pharmaceutical testing regime, or students learning under a new educational method. Fundamentally, this unit bears the brunt of the investigation and their response powers the outcomes.

However, without positive and negative controls, gauging the results of the experimental group could become erratic. Both control groups exist to highlight what outcomes are expected with and without the application of the variable in question. By comparing results, a clearer connection between the experiment variables and the observed changes surfaces, creating robust and indicative scientific conclusions.

Positive and Negative Control Examples

1. a comparative study of old and new pesticides’ effectiveness.

This hypothetical study aims to evaluate the effectiveness of a new pesticide by comparing its pest-killing potential with old pesticides and an untreated set. The investigation involves three groups: an untouched space (negative control), another treated with an established pesticide believed to kill pests (positive control), and a third area sprayed with the new pesticide (experimental group).

Negative Control: This group consists of a plot of land infested by pests and not subjected to any pesticide treatment. It acts as the negative control. You expect no decline in pest populations in this area. Any unexpected decrease could signal external influences (i.e. confounding variables ) on the pests unrelated to pesticides, affecting the experiment’s validity.
Positive Control: Another similar plot, this time treated with a well-established pesticide known to reduce pest populations, constitutes the positive control. A significant reduction in pests in this area would affirm that the experimental conditions are conducive to detect pest-killing effects when a pesticide is applied.
Experimental Group: This group consists of the third plot impregnated with the new pesticide. Carefully monitoring the pest level in this research area against the backdrop of the control groups will reveal whether the new pesticide is effective or not. Through comparison with the other groups, any difference observed can be attributed to the new pesticide.

2. Evaluating the Effectiveness of a Newly Developed Weight Loss Pill

In this hypothetical study, the effectiveness of a newly formulated weight loss pill is scrutinized. The study involves three groups: a negative control group given a placebo with no weight-reducing effect, a positive control group provided with an approved weight loss pill known to cause a decrease in weight, and an experimental group given the newly developed pill.

Negative Control: The negative control is comprised of participants who receive a placebo with no known weight loss effect. A significant reduction in weight in this group would indicate confounding factors such as dietary changes or increased physical activity, which may invalidate the study’s results.
Positive Control: Participants in the positive control group receive an FDA-approved weight loss pill, anticipated to induce weight loss. The success of this control would prove that the experiment conditions are apt to detect the effects of weight loss pills.
Experimental Group: This group contains individuals receiving the newly developed weight loss pill. Comparing the weight change in this group against both the positive and negative control, any difference observed would offer evidence about the effectiveness of the new pill.

3. Testing the Efficiency of a New Solar Panel Design

This hypothetical study focuses on assessing the efficiency of a new solar panel design. The study involves three sets of panels: a set that is shaded to yield no solar energy (negative control), a set with traditional solar panels that are known to produce an expected level of solar energy (positive control), and a set fitted with the new solar panel design (experimental group).

Negative Control: The negative control involves a set of solar panels that are deliberately shaded, thus expecting no solar energy output. Any unexpected energy output from this group could point towards measurement errors, needed to be rectified for a valid experiment.
Positive Control: The positive control set up involves traditional solar panels known to produce a specific amount of energy. If these panels produce the expected energy, it validates that the experiment conditions are capable of measuring solar energy effectively.
Experimental Group: The experimental group features the new solar panel design. By comparing the energy output from this group against both the controls, any significant output variation would indicate the efficiency of the new design.

4. Investigating the Efficacy of a New Fertilizer on Plant Growth

This hypothetical study investigates the efficacy of a newly formulated fertilizer on plant growth. The study involves three sets of plants: a set without any fertilizer (negative control), a set treated with an established fertilizer known to promote plant growth (positive control), and a third set fed with the new fertilizer (experimental group).

Negative Control: The negative control involves a set of plants not receiving any fertilizer. Lack of significant growth in this group will confirm that any observed growth in other groups is due to the applied fertilizer rather than other uncontrolled factors.
Positive Control: The positive control involves another set of plants treated with a well-known fertilizer, expected to promote plant growth. Adequate growth in these plants will validate that the experimental conditions are suitable to detect the influence of a good fertilizer on plant growth.
Experimental Group: The experimental group consists of the plants subjected to the newly formulated fertilizer. Investigating the growth in this group against the growth in the control groups will provide ascertained evidence whether the new fertilizer is efficient or not.

5. Evaluating the Impact of a New Teaching Method on Student Performance

This hypothetical study aims to evaluate the impact of a new teaching method on students’ performance. This study involves three groups, a group of students taught through traditional methods (negative control), another group taught through an established effective teaching strategy (positive control), and one more group of students taught through the new teaching method (experimental group).

Negative Control: The negative control comprises students taught by standard teaching methods, where you expect satisfactory but not top-performing results. Any unexpected high results in this group could signal external factors such as private tutoring or independent study, which in turn may distort the experimental outcome.
Positive Control: The positive control consists of students taught by a known efficient teaching strategy. High performance in this group would prove that the experimental conditions are competent to detect the efficiency of a teaching method.
Experimental Group: This group consists of students receiving instruction via the new teaching method. By analyzing their performance against both control groups, any difference in results could be attributed to the new teaching method, determining its efficacy.

Table Summary

Aspect	Positive Control	Negative Control
	To confirm that the experiment is working properly and that results can be detected.	To ensure that there is no effect when there shouldn’t be, and to provide a baseline for comparison.
	A known effect or change.	No effect or change.
	Used to demonstrate that the experimental setup can produce a positive result.	Used to demonstrate that any observed effects are due to the experimental treatment and not other factors.
	Plants given known amounts of sunlight to ensure they grow.	Plants given no sunlight to ensure they don’t grow.
	A substrate known to be acted upon by the enzyme.	A substrate that the enzyme doesn’t act upon.
	A medium known to support bacterial growth.	A medium that doesn’t support bacterial growth (sterile medium).
	Validates that the experimental system is sensitive and can detect changes if they occur.	Validates that observed effects are due to the variable being tested and not due to external or unknown factors.
	If the positive control doesn’t produce the expected result, the experimental setup or procedure may be flawed.	If the negative control shows an effect, there may be contamination or other unexpected variables influencing the results.

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The effect of extended cold storage and the use of extenders on motility and swimming kinematics of shortnose sturgeon sperm

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Shortnose sturgeon are listed as a species of special concern in Canada and as endangered in the US. Increasing knowledge about this species, particularly in the area of reproductive biology, will better the management of wild populations and aid in the development of assisted reproduction protocols. However, access to wild sperm is limited, so short-term and long-term storage of sperm from sturgeon is crucial for reproductive studies. Here we report on testing and development of a short-term storage protocol for shortnose sturgeon. Milt samples were collected from wild shortnose sturgeon caught in the Wolastoq River. Subsets of semen were mixed with different extenders with or without oxygen; control treatments without extenders were also run. We used computer-assisted sperm analysis (CASA) to determine sperm motility and swimming kinematics for the different treatments. All groups were examined immediately after collection and treatment application, and then 1, 2, and 7 days after storage in a fridge (4°C) for experiment 1, and days 1, 3, 7, 10, 14, 17, 21, and 24 for experiment 2. The response variables motility, curvilinear velocity (VCL), linearity (LIN), and wobble (WOB) showed an overall decrease over time with differences between extender treatments. While untreated milt maintained some motility up to day 21, the addition of an extender reduced decline in motility and improved longevity up to day 24. Milt treated with the Park and Chapman extender had the slowest motility decline of extenders used, and milt treated with the modified Tsvetkova extender showed less potential for contamination.

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Shortnose sturgeon are listed as a species of special concern in Canada and as endangered in the US. Increasing knowledge about this species, particularly in the area of reproductive biology, will better the management of wild populations and aid in the development of assisted reproduction protocols. However, access to wild sperm is limited, so short-term and long-term storage of sperm from ...

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Controlled experiments

Introduction

Control and experimental groups

Experimental setup

Analyzing the results

Additional references:

Controlled Experiments: Definition, Steps, Results, Uses

Importance of controlled experiments in various fields

Why Controlled Experiments Matter?

Minimizing Biases and Confounding Variables

Achieving Causal Inference

Planning a Controlled Experiment

Identifying Variables and Control Groups

Designing Experimental Procedures and Protocols

Conducting a Controlled Experiment

Data Collection Methods and Instruments

Monitoring and Maintaining Experimental Conditions

Analysing Results and Drawing Conclusions

Interpretation of Results

Implications and Potential Applications

Common Challenges and Solutions

Dealing with Sample Size and Statistical Power

Mitigating Unforeseen Variables

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