origin hypothesis biology definition

• Introduction to Ecology; Major patterns in Earth’s climate
• Behavioral Ecology
• Population Ecology 1
• Population Ecology 2
• Community Ecology 1
• Community Ecology 2
• Ecosystems 1
• Ecosystems 2
• Strong Inference
• What is life?

What is evolution?

• Evolution by Natural Selection
• Other Mechanisms of Evolution
• Population Genetics: the Hardy-Weinberg Principle
• Phylogenetic Trees
• Earth History and History of Life on Earth
• Origin of Life on Earth
• Gene expression: DNA to protein
• Gene regulation
• Cell division: mitosis and meiosis
• Mendelian Genetics
• Chromosome theory of inheritance
• Patterns of inheritance
• Chemical context for biology: origin of life and chemical evolution
• Biological molecules
• Membranes and Transport
• Energy and enzymes
• Respiration, chemiosmosis and oxidative phosphorylation
• Oxidative pathways: electrons from food to electron carriers
• Fermentation, mitochondria and regulation
• Why are plants green, and how did chlorophyll take over the world? (Converting light energy into chemical energy)
• Carbon fixation
• Recombinant DNA
• Cloning and Stem Cells
• Adaptive Immunity
• Human evolution and adaptation

Learning Objectives

• Recall the common features of life on earth
• List the conditions that cause populations of living organisms to evolve
• Distinguish biological evolution of populations from changes to individual organisms over a lifetime.
• Cite evidence that all life on earth has a common origin
• Explain how a scientific “theory” differs from hypothesis or conjecture
• Distinguish between homologous and analogous structures
• Identify common misconceptions about evolution

Life on Earth

Recall from the beginning of this course the five generally agreed upon criteria for life:

• Need for energy
• Organization in membrane-bound cells
• Genetic information
• Ability to replicate
• Change over time

Evolution as an emergent property of life

A key part of any definition of life is that living organisms reproduce. Let’s now add a couple of observations:

• The process of reproduction, while mostly accurate, is imperfect. When cells divide, they have to replicate their DNA. Although DNA replication is highly accurate, it still makes about 1 mistake in 10 million nucleotides. Over generations, the population will contain lots of heritable variation.
• The population of a given type of organism will tend to grow exponentially, but will reach a limit, where the individuals have to compete with each other for the limiting resource (food, space, mates, sunlight, etc.)

Suppose some heritable variations (speed, strength, sharper claws, bigger teeth) make some individuals more competitive for the limiting resource—what will happen? The individuals with superior variants will acquire more resources, and have more progeny. If the superior variants are heritable, then their progeny will have the same superior variants. Over generations, then, a larger and larger proportion of the population will consist of individuals with the superior heritable variants. This is biological evolution.

Biological evolution is defined as change in the heritable characteristics of a population over succeeding generations. In more technical terms, evolution is defined as change in the gene pool of a population, measurable as changes in allele frequencies in a population.

Suppose there is heritable variation in a population, and the heritable variation makes a difference in the survival and reproduction of individual organisms. If these conditions exist, and they do for all natural populations of living organisms, evolution must occur. Life evolves!

Charles Darwin called this process natural selection. He and Alfred Wallace were the first to propose that evolution by natural selection could explain the origin of all the multitudes of species on Earth and how they appear so well-adapted in form and function to their particular environments. Moreover, Darwin proposed that all of life on Earth descended from a common ancestor, via slow, incremental accumulation of heritable (genetic) changes.

Evolution is a theory, not just a hypothesis

Darwin published his theory of evolution in the Origin of Species (1859), with carefully reasoned evidence to support this theory that all life on earth evolved from a common ancestor. This theory has been tested in numerous ways by the work of many thousands of scientists. Every test has produced results that are consistent with the theory. Evolutionary biologists conduct research to elaborate or refine the theory and understand the mechanisms at work in specific populations. Evolutionary theory now forms a framework for biological thinking, so that one famous evolutionary biologist wrote that “ Nothing in Biology Makes Sense Except in the Light of Evolution ” (Dobzhansky, 1973).

The scientific use of the word theory is very different from the casual, every-day use.  A scientific theory is an overarching, unifying explanation of phenomena that is well supported by multiple, independent lines of evidence—i.e., composed of hundreds or thousands of independent, well-supported hypotheses.  For example, germ theory is the theory that explains how microorganisms cause disease, and cell theory explains how cells function as the basic unit of life.

Title page of Darwin’s The Origin of Species, 1859 from Wikipedia

A few key lines of supporting evidence:

• geological and fossil record, showing that the Earth is about 4.5 billion years old, and sequential changes in the kinds and forms of living organisms over geological time scales
• homologies in body plans, structures, and DNA sequences indicative of common ancestry
• a common biochemistry for all life on Earth – the same amino acids, the same biological building blocks, the same genetic code
• inference of evolutionary relationships from gene sequence comparisons largely agree with the fossil record, and are consistent with a common origin for all extant life on Earth.

The video below highlights some of this key supporting evidence in the context of the evolution of whales:

Homologous or Analogous?

In comparing characteristics of organisms, we have to keep in mind that organisms may have similar characteristics either because they inherited the characteristic from a common ancestor, or because they both independently evolved similar characteristics. For example, the tail fins of dolphins, orcas and whales are similar in shape, and they were inherited from a common ancestor of these marine mammals. Their tail fins are homologous,  meaning their similarity is due to inheritance from a common ancestor. On the other hand, the tail fins of orcas and sharks are not homologous, because the common ancestor of all mammals did not have tail fins. They are analogous structures, that evolved independently in sharks and marine mammals. When scientists analyze evolutionary relationships between groups of organisms, they have to be careful to distinguish whether observed similarities between the groups are homologous or analogous.

Common misconceptions about evolution

Here are corrections to some common misconceptions about evolution by natural selection:

• The individual undergoing natural selection does not evolve–it just lives or dies! Instead, the population of organisms evolves. Recall that evolution is the change in allele frequencies, and only populations have allele frequencies. Individuals just have alleles.
• Evolution is not a directed process with a fixed end point, or a best phenotype. Rather, the environment serves as a selective agent . No amount of planning on the part of the organism can predict whether an organism will be a good fit for the environment it finds itself in. An individual cannot “try” to evolve or “anticipate” the types of mutations it should have for future environmental change.
• Organisms, and the genes they contain, do not behave for the ‘good of the species.’ Rather, each individual lives and reproduces, which increases its representation in the gene pool, or it dies or fails to reproduce and is not represented in the gene pool. Those most represented after encountering a selective agent are considered the “most fit” for that environment, in that time and place.
• Selection doesn’t always result in the best possible fit of an organism to its environment because of constraints and trade-offs . Sometimes the same genes that code for a trait also cause a second, suboptimal trait to occur.
• Mutations are not caused or induced as a result of environmental change. Variation is already present in the population. When the environment changes, those individuals that already have some beneficial variation (mutations) that is well suited to the new environment are more likely to survive and reproduce; organisms do not develop new mutations in response to the environmental change.  (And if there is no variation present in the population such that some individuals survive and reproduce, then the population is likely to go extinct).

At its simplest, evolution distills down to the idea that as long as there is variation in a population, as long as that variation is heritable, and as long as there is differential reproductive success (not everyone reproduces equally), then the next generation will be genetically different from the previous generation. We will explore the mechanisms that contribute to evolution over the next class sessions.

For thought and discussion:

Think of some ways that evolution can be or has been tested. What testable predictions arise from evolutionary theory? How does the work of many geologists or some physicists test evolutionary theory? What are some common misconceptions about evolution?

Evolution Resources:

Evolution 101 University of California Berkeley evolution site, a complete resource for learning and teaching about evolution. Engaging, well-illustrated, accurate. How did feathers evolve? Carl Zimmer’s TED-Ed video, 3 1/2 minutes. Evolution animation by Tyler Rhodes, produced from drawings made by children copying a drawing of a salamander-like animal with successive generations of variation, mass extinction and selection. The process is described in this Scientific American blog post  http://blogs.scientificamerican.com/psi-vid/2012/02/29/an-evolution-animation-unlike-any-youve-seen-before/ and Tyler Rhodes blog http://evolutionanimation.wordpress.com/ describes both the drawing “game” and his animation process. His “ wheel of life ” is an amazing phylogenetic tree of the drawings. Newly found: the world’s oldest fossils A post in the Why Evolution Is True blog by Jerry Coyne, explaining the paper by Wacey, D.,M. R. Kilburn, M. Saudners, J. Cliff, and M. D. Wacey et al. 2011.  Microfossils of sulphur-metabolizing cells in 3.4-billion-year-old rocks of Western Australia .  Nature Geoscience online: doi:10.1038/ngeo1238 Darryl Cunningham Investigates: Evolution A lucid, inviting comic-strip presentation of basic evolutionary theory and evidence. Aimed at beginning learners. Nothing in Biology Makes Sense Except in the Light of Evolution Dobzhansky’s 1973 essay in The American Biology Teacher 35:125-129, just as relevant today as then.

UN Sustainable Development Goal (SDG) 14 Life Below Water and SDG 15: Life on Land – Everything evolves! Understanding the common features of life on Earth is crucial for the conservation and protection of Earth’s biodiversity, and potentially for understanding life we may one day find elsewhere!

One Response to What is evolution?

This cell is having quite the existential crisis! Via Beatrice the Biologist pic.twitter.com/C2kRGRzag6 — Carin Anne Bondar (@carinbondar) December 9, 2015

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7 theories on the origin of life

The answer to the origin of life remains unknown, but here are scientists best bets

• An electric spark

Molecules of life met on clay

• Deep-sea vents
• Born from ice
• Understanding DNA
• Simple beginnings
• Life came from space

Additional resources

Bibliography.

The origin of life on Earth began more than 3 billion years ago, evolving from the most basic of microbes into a dazzling array of complexity over time. But how did the first organisms on the only known home to life in the universe develop from the primordial soup?

Science remains undecided and conflicted as to the exact origin of life, also known as abiogenesis. Even the very definition of life is contested and rewritten, with one study published in the J ournal of Biomolecular Structure and Dynamics , suggesting uncovering 123 different published definitions. 

Although science still seems unsure, here are  some of the many different scientific theories on the origin of life on Earth.

It started with an electric spark

Lightning may have provided the spark needed for life to begin.Electric sparks can generate amino acids and sugars from an atmosphere loaded with water, methane, ammonia and hydrogen , as was shown in the famous Miller-Urey experiment  in 1952, according to Scientific American . The experiment's findings  suggested that lightning might have helped create the key building blocks of life on Earth in its early days. Over millions of years, larger and more complex molecules could form. 

Although research since then has revealed the early atmosphere of Earth was actually hydrogen-poor, scientists have suggested that volcanic clouds in the early atmosphere might have held methane, ammonia and hydrogen and been filled with lightning as well, according to the University of California

The first molecules of life might have met on clay, according to an idea elaborated by organic chemist Alexander Graham Cairns-Smith at the University of Glasgow in Scotland. Cairns-Smith proposed in his 1985 controversial book “ Seven Clues to the Origin of Life'' , that clay crystals preserve their structure as they grow and stick together to form areas exposed to different environments and trap other molecules along the way and organise them into patterns much like our genes do now.

– What is the difference between prokaryotic and eukaryotic cells?

– What is biology?

– What are bacteria?

– What is an amoeba?

– Is there water on Mars?

The main role of DNA is to store information on how other molecules should be arranged. Genetic sequences in DNA are essentially instructions on how amino acids should be arranged in proteins. Cairns-Smith suggests that mineral crystals in clay could have arranged organic molecules into organized patterns. After a while, organic molecules took over this job and organized themselves.

Although Cairns-Smith's theory certainly gave scientists food for thought in the 1980s, it has still not been widely accepted by the scientific community.

Life began at deep-sea vents

The deep-sea vent theory suggests that life may have begun at submarine hydrothermal vents spewing elements key to life, such as carbon and hydrogen-, according to the journal Nature Reviews Microbiology .

Hydrothermal vents can be found in the darkest depths of the ocean floors, typically on diverging continental plates, according to the Natural History Museum . These vents erupt fluid which is superheated by the Earth’s core as it passes up through the crust, before being ejected at the vets. During its journey through the crust it collects dissolved gases and minerals, such as carbon and hydrogen. 

Their rocky nooks could then have concentrated these molecules together and provided mineral catalysts for critical reactions. Even now, these vents, rich in chemical and thermal energy, sustain vibrant ecosystems.

Abiogenesis by way of hydrothermal vents continues to be investigated as a plausible cause of life on Earth. In 2019, scientists at University College London , successfully created protocells (non-living structures that help scientists understand the origins of life) under similar hot, alkaline environmental conditions to hydrothermal vents.

Life had a chilly start

Ice might have covered the oceans 3 billion years ago and facilitated the birth of life. "Key organic compounds thought to be important in the origin of life are more stable at lower temperatures,” Jeffrey Bada at the University of California, told New Scientist . At normal temperatures these compounds, such as simple sets of amino acids, are sparsely populated in water, but when frozen become concentrated and facilitate the emergence of life, according to Bada’s work published in the journal I carus .  

Ice also might have protected fragile organic compounds in the water below from ultraviolet light and destruction from cosmic impacts. The cold might have also helped these molecules to survive longer, enabling key reactions to happen. 

The answer lies in understanding DNA formation

Nowadays DNA needs proteins in order to form, and proteins require DNA to form, so how could these have formed without each other? The answer may be RNA , which can store information like DNA, serve as an enzyme like proteins, and help create both DNA and proteins, according to the journal Molecular Biology of the Cell . Later DNA and proteins succeeded this "RNA world," because they are more efficient.

RNA still exists and performs several functions in organisms, including acting as an on-off switch for some genes. The question still remains how RNA got here in the first place. Some scientists think the molecule could have spontaneously arisen on Earth, while others say that was very unlikely to have happened. 

Life had simple beginnings

Instead of developing from complex molecules such as RNA, life might have begun with smaller molecules interacting with each other in cycles of reactions. These might have been contained in simple capsules akin to cell membranes, and over time more complex molecules that performed these reactions better than the smaller ones could have evolved, scenarios dubbed "metabolism-first" models, as opposed to the "gene-first" model of the "RNA world" hypothesis.

Life was brought here from elsewhere in space

Perhaps life did not begin on Earth at all, but was brought here from elsewhere in space, a notion known as panspermia, according to NASA . For instance, rocks regularly get blasted off Mars by cosmic impacts, and a number of Martian meteorites have been found on Earth that some researchers have controversially suggested brought microbes over here, potentially making us all Martians originally. Other scientists have even suggested that life might have hitchhiked on comets from other star systems. However, even if this concept were true, the question of how life began on Earth would then only change to how life began elsewhere in space.

For more information into the theories of life’s origins check out “ The Stairway To Life: An Origin-Of-Life Reality Check ” by Change Laura Tan and “ The Mystery of Life's Origin ” by Charles B. Thaxton, et al. 

Matthew Levy et al, “Prebiotic Synthesis of Adenine and Amino Acids Under Europa-like Conditions”, Icarus, Volume 145, June 2000, https://doi.org/10.1006/icar.2000.6365

William Martin, “Hydrothermal vents and the origin of life”, Nature Reviews Microbiology, Volume 6, September 2008, https://doi.org/10.1038/nrmicro1991  

K. A. Dill and L. Agozzino, “Driving forces in the origins of life”, Open biology, Volume 11, February 2021, ttps://doi.org/10.1098/rsob.200324 

Ben K. D. Pearce et al, “Origin of the RNA world: The fate of nucleobases in warm little ponds”, PNAS, Volume 114, October 2017, https://doi.org/10.1073/pnas.1710339114

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2.3: The Origin of Species

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• Page ID 108052

• Tara Jo Holmberg
• Northwestern Connecticut Community College

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Learning Objectives

• Define species and describe how scientists identify species as different
• Describe genetic variables that lead to speciation
• Identify prezygotic and postzygotic reproductive barriers
• Explain allopatric and sympatric speciation
• Describe adaptive radiation
• Explain the two major theories on rates of speciation
• 2.3.1: Species Defined A biological species is defined as a group of individuals that, in nature, are able to mate and produce viable, fertile offspring. There are other definitions of species but, according to the biological definition, one species is distinguished from another when, in nature, it is not possible for matings between individuals from each species to produce fertile, living offspring.
• 2.3.2: Speciation Speciation is an event in which a single species may branch to form two or more new species.
• 2.3.3: Rates of Speciation and Extinction Scientists around the world study speciation, documenting observations both of living organisms and those found in the fossil record. As their ideas take shape and as research reveals new details about how life evolves, they develop models to help explain rates of speciation. In terms of how quickly speciation occurs, two patterns are currently observed: the gradual speciation model and the punctuated equilibrium model.

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Biology archive

Course: biology archive   >   unit 1, the scientific method.

• Controlled experiments
• The scientific method and experimental design

Introduction

• Make an observation.
• Ask a question.
• Form a hypothesis , or testable explanation.
• Make a prediction based on the hypothesis.
• Test the prediction.
• Iterate: use the results to make new hypotheses or predictions.

Scientific method example: Failure to toast

1. make an observation., 2. ask a question., 3. propose a hypothesis., 4. make predictions., 5. test the predictions..

• If the toaster does toast, then the hypothesis is supported—likely correct.
• If the toaster doesn't toast, then the hypothesis is not supported—likely wrong.

Logical possibility

Practical possibility, building a body of evidence, 6. iterate..

• If the hypothesis was supported, we might do additional tests to confirm it, or revise it to be more specific. For instance, we might investigate why the outlet is broken.
• If the hypothesis was not supported, we would come up with a new hypothesis. For instance, the next hypothesis might be that there's a broken wire in the toaster.

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The origin of life: what we know, what we can know and what we will never know

1 Department of Chemistry, Ben-Gurion University of the Negev, Be'er Sheva, 84105, Israel

Robert Pascal

2 Institut des Biomolécules Max Mousseron (UMR 5247, CNRS, Universités Montpellier 1 and Montpellier 2), Université Montpellier 2, Place E. Bataillon 34095, Montpellier Cedex 05, France

The origin of life (OOL) problem remains one of the more challenging scientific questions of all time. In this essay, we propose that following recent experimental and theoretical advances in systems chemistry, the underlying principle governing the emergence of life on the Earth can in its broadest sense be specified, and may be stated as follows: all stable (persistent) replicating systems will tend to evolve over time towards systems of greater stability. The stability kind referred to, however, is dynamic kinetic stability, and quite distinct from the traditional thermodynamic stability which conventionally dominates physical and chemical thinking. Significantly, that stability kind is generally found to be enhanced by increasing complexification, since added features in the replicating system that improve replication efficiency will be reproduced, thereby offering an explanation for the emergence of life's extraordinary complexity. On the basis of that simple principle, a fundamental reassessment of the underlying chemistry–biology relationship is possible, one with broad ramifications. In the context of the OOL question, this novel perspective can assist in clarifying central ahistoric aspects of abiogenesis, as opposed to the many historic aspects that have probably been forever lost in the mists of time.

2. Introduction

The origin of life (OOL) problem continues to be one of the most intriguing and challenging questions in science (for recent reviews on the OOL, see [ 1 – 6 ]). Its resolution would not only satisfy man's curiosity regarding this central existential issue, but would also shed light on a directly related topic—the precise nature of the physico-chemical relationship linking animate and inanimate matter. As one of us (A.P.) has noted previously [ 1 , 7 , 8 ], until the principles governing the process by which life on the Earth emerged can be uncovered, an understanding of life's essence, the basis for its striking characteristics, and outlining a feasible strategy for the synthesis of what could be classified as a simple life form will probably remain out of reach. In this essay, we will argue that recent developments in systems chemistry [ 9 – 11 ] have dramatically changed our ability to deal with the OOL problem by enabling the chemistry–biology connection to be clarified, at least in broad outline. The realization that abiogenesis—the chemical process by which simplest life emerged from inanimate beginnings—and biological evolution may actually be one single continuous physico-chemical process with an identifiable driving force opens up new avenues towards resolution of the OOL problem [ 1 , 7 , 12 , 13 ]. In fact that unification actually enables the basic elements of abiogenesis to be outlined, in much the same way that Darwin's biological theory outlined the basic mechanism for biological evolution. The goal of this commentary therefore is to discuss what aspects of the OOL problem can now be considered as resolved, what aspects require further study and what aspects may, in all probability, never be known.

3. Is the origin of life problem soluble in principle?

In addressing the OOL question, it first needs to be emphasized that the question has two distinct facets—historic and ahistoric, and the ability to uncover each of these two facets is quite different. Uncovering the historic facet is the more problematic one. Uncovering that facet would require specifying the original chemical system from which the process of abiogenesis began, together with the chemical pathway from that initiating system right through the extensive array of intermediate structures leading to simplest life. Regretfully, however, much of that historic information will probably never be known. Evolutionary processes are contingent, suggesting that any number of feasible pathways could have led from inanimate matter to earliest life, provided, of course, that those pathways were consistent with the underlying laws of physics and chemistry. The difficulty arises because historic events, once they have taken place, can only be revealed if their occurrence was recorded in some manner. Indeed, it is this historic facet of abiogenesis that makes the OOL problem so much more intractable than the parallel question of biological evolution. Biological evolution also has its historic and ahistoric facets. But whereas for biological evolution the historic record is to a degree accessible through palaeobiologic and phylogenetic studies, for the process of abiogenesis those methodologies have proved uninformative; there is no known geological record pertaining to prebiotic systems, and phylogenetic studies become less informative the further back one goes in attempting to trace out ancestral lineages. Phylogenetic studies presume the existence of organismal individuality and the genealogical (vertical) transfer of genetic information. However, the possibility that earliest life may have been communal [ 14 ] and dominated by horizontal gene transfer [ 15 – 17 ] suggests that information regarding the evolutionary stages that preceded the last universal common ancestor [ 18 ] would have to be considered highly speculative. Accordingly, the significance of such studies to the characterization of early life, let alone prebiotic systems, becomes highly uncertain.

The conclusion seems clear: speculation regarding the precise historic path from animate to inanimate—the identity of specific materials that were available at particular physical locations on the prebiotic Earth, together with the chemical structures of possible intermediate stages along the long road to life—may lead to propositions that are, though thought-provoking and of undeniable interest, effectively unfalsifiable, and therefore of limited scientific value.

Given that awkward reality, the focus of OOL research needs to remain on the ahistoric aspects—the principles that would explain the remarkable transformation of inanimate matter to simple life. There is good reason to think that the emergence of life on the Earth did not just involve a long string of random chemical events that fortuitously led to a simple living system. If life had emerged in such an arbitrary way, then the mechanistic question of abiogenesis would be fundamentally without explanation—a stupendously improbable chemical outcome whose likelihood of repetition would be virtually zero. However, the general view, now strongly supported by recent studies in systems chemistry, is that the process of abiogenesis was governed by underlying physico-chemical principles, and the central goal of OOL studies should therefore be to delineate those principles. Significantly, even if the underlying principles governing the transformation of inanimate to animate were to be revealed, that would still not mean that the precise historic path could be specified. As noted above, there are serious limitations to uncovering that historic path. The point however is that if the principles underlying life's emergence on the Earth could be more clearly delineated, then the mystery of abiogenesis would be dramatically transformed. No longer would the problem of abiogenesis be one of essence , but rather one of detail . The major mystery at the heart of the OOL debate would be broadly resolved and the central issue would effectively be replaced by a variety of chemical questions that deal with the particular mechanisms by which those underlying principles could have been expressed. Issues such as identifying historic transitions, the definition of life, would become to some extent arbitrary and ruled by scientific conventions, rather than by matters of principle.

4. The role of autocatalysis during abiogenesis

In the context of the OOL debate, there is one single and central historic fact on which there is broad agreement—that life's emergence was initiated by some autocatalytic chemical system. The two competing narratives within the OOL's long-standing debate—‘replication first’ or ‘metabolism first’—though differing in key elements, both build on that autocatalytic character (see [ 1 ] and references therein). The ‘replication first’ school of thought stresses the role of oligomeric compounds, which express that autocatalytic capability through their ability to self-replicate, an idea that can be traced back almost a century to the work of Troland [ 19 ], while the ‘metabolism first’ school of thought emphasizes the emergence of cyclic networks, as articulated by Kauffman [ 20 ] in the 1980s and reminiscent of the metabolic cycles found in all extant life. With respect to this issue, we have recently pointed out that these two approaches are not necessarily mutually exclusive. It could well be that both oligomeric entities and cyclic networks were crucial elements during life's emergence, thereby offering a novel perspective on this long-standing question [ 1 , 7 ]. However, once it is accepted that autocatalysis is a central element in the process of abiogenesis, it follows that the study of autocatalytic systems in general may help uncover the principles that govern their chemical behaviour, regardless of their chemical detail. Indeed, as we will now describe, the generally accepted supposition that life's origins emerged from some prebiotic autocatalytic process can be shown to lead to broad insights into the chemistry–biology connection and to the surprising revelation that the processes of abiogenesis and biological evolution are directly related to one another. Once established, that connection will enable the underlying principles that governed the emergence of life on the Earth to be uncovered without undue reliance on speculative historic suppositions regarding the precise nature of those prebiotic systems.

5. A previously unrecognized stability kind: dynamic kinetic stability

The realization that the autocatalytic character of the replication reaction can lead to exponential growth and is unsustainable has been long appreciated, going back at least to Thomas Malthus's classic treatise ‘An essay on the principle of population’, published in 1798 [ 21 ]. But the chemical consequences of that long-recognized powerful kinetic character, although described by Lotka already a century ago [ 22 ], do not seem to have been adequately appreciated. Recently, one of us (A.P.) has described a new stability kind in nature, seemingly overlooked in modern scientific thought, which we have termed dynamic kinetic stability ( DKS ) [ 1 , 7 , 23 , 24 ] . That stability kind, applicable solely to persistent replicating systems, whether chemical or biological, derives directly from the powerful kinetic character and the inherent unsustainability of the replication process. However, for the replication reaction to be kinetically unsustainable, the reverse reaction, in which the replicating system reverts back to its component building blocks, must be very slow when compared with the forward reaction; the replication reaction must be effectively irreversible. That condition, in turn, means the system must be maintained in a far-from-equilibrium state [ 25 ], and that continuing requirement is satisfied through the replicating system being open and continually fed activated component building blocks. Note that the above description is consistent with Prigogine's non-equilibrium thermodynamic approach, which stipulates that self-organized behaviour is associated with irreversible processes within the nonlinear regime [ 26 ]. From the above, it follows that the DKS term would not be applicable to an equilibrium mixture of some oligomeric replicating entity together with its interconverting component building blocks.

Given the above discussion, it is apparent that the DKS concept is quite distinct from the conventional stability kind in nature, thermodynamic stability. A key feature of DKS is that it characterizes populations of replicators , rather than the individual replicators which make up those populations. Individual replicating entities are inherently unstable , as reflected in their continual turnover, whereas a population of replicators can be remarkably stable, as expressed by the persistence of some replicating populations. Certain life forms (e.g. cyanobacteria) express this stability kind in dramatic fashion, having been able to maintain a conserved function and a readily recognized morphology over billions of years. Indeed, within the world of replicators, there is theoretical and empirical evidence for a selection rule that in some respects parallels the second law of thermodynamics in that less stable replicating systems tend to become transformed into more stable ones [ 1 , 8 ]. This stability kind, which is applicable to all persistent replicating systems, whether chemical or biological, is then able to place biological systems within a more general physico-chemical framework, thereby enabling a physico-chemical merging of replicating chemical systems with biological ones. Studies in systems chemistry in recent years have provided empirical support for such a view by demonstrating that chemical and biological replicators show remarkably similar reactivity patterns, thereby reaffirming the existence of a common underlying framework linking chemistry to biology [ 1 , 7 ].

6. Extending Darwinian theory to inanimate chemical systems

The recognition that a distinctly different stability kind, DKS, is applicable to both chemical and biological replicators, together with the fact that both replicator kinds express similar reaction characteristics, leads to the profound conclusion that the so-called chemical phase leading to simplest life and the biological phase appear to be one continuous physico-chemical process, as illustrated in scheme 1 .

Unification of abiogenesis and biological evolution into a single continuous process governed by the drive toward greater DKS.

That revelation is valuable as it offers insights into abiogenesis from studies in biological evolution and, vice versa, it can provide new insights into the process of biological evolution from systems chemistry studies of simple replicating systems. A single continuous process necessarily means one set of governing principles, which in turn means that the two seemingly distinct processes of abiogenesis and evolution can be combined and addressed in concert. Significantly, that merging of chemistry and biology suggests that a general theory of evolution, expressed in physico-chemical terms rather than biological ones and applicable to both chemical and biological systems, may be formulated. Its essence may be expressed as follows: All stable ( persistent ) replicating systems will tend to evolve over time towards systems of greater DKS. As we have described in some detail in previous publications, there are both empirical and theoretical grounds for believing that oligomeric replicating systems which are less stable (less persistent) will tend to be transformed into more stable (more persistent) forms [ 1 , 7 , 8 , 24 ]. In fact that selection rule is just a particular application of the more general law of nature, almost axiomatic in character, that systems of all kinds tend from less stable to more stable. That law is inherent in the very definition of the term ‘stability’. So within the global selection rule in nature, normally articulated by the second law of thermodynamics, we can articulate a formulation specific to replicative systems, both chemical and biological— from DKS less stable to DKS more stable . A moment's thought then suggests that the Darwinian concept of ‘fitness maximization’ (i.e. less fit to more fit) is just a more specific expression of that general replicative rule as applied specifically to biological replicators. Whereas, in Darwinian terms, we say that living systems evolve to maximize fitness, the general theory is expressed in physico-chemical terms and stipulates that stable replicating systems, whether chemical or biological, tend to evolve so as to increase their stability, their DKS. Of course such a formulation implies that DKS is quantifiable. As we have previously discussed, quantification is possible, but only for related replicators competing for common resources, for example, a set of structurally related replicating molecules, or a set of genetically related bacterial life forms [ 1 , 7 ]. More generally, when assessing the DKS of replicating systems in a wider sense, one frequently must make do with qualitative or, at best, semi-quantitative measures.

Note that the general theory should not be considered as just one of changing terminology—‘DKS’ replacing ‘fitness’, ‘kinetic selection’ replacing ‘natural selection’. The physico-chemical description offers new insights as it allows the characterization of both the driving force and the mechanisms of evolution in more fundamental terms. The driving force is the drive of replicating systems towards greater stability, but the stability kind that is applicable in the replicative world. In fact that driving force can be thought of as a kind of second law analogue, though, as noted, the open character of replicating systems makes its quantification more difficult. And the mechanisms by which that drive is expressed can now be specified. These are complexification and selection , the former being largely overlooked in the traditional Darwinian view, while the latter is, of course, central to that view. A striking insight from this approach to abiogenesis follows directly: just as Darwinian theory broadly explained biological evolution, so an extended theory of evolution encompassing both chemical and biological replicators can be considered as broadly explaining abiogenesis. Thus, life on the Earth appears to have emerged through the spontaneous emergence of a simple (unidentified) replicating system, initially fragile, which complexified and evolved towards complex replicating systems exhibiting greater DKS. In fact, we would claim that in the very broadest of terms, the physico-chemical basis of abiogenesis can be considered explained.

But does that simplistic explanation for abiogenesis imply that the OOL problem can be considered resolved? Far from it. Let us now consider why.

7. What is still to be learned?

While Darwin's revolutionary theory changed our understanding of how biological systems relate to one another through the simple concept of natural selection, the Darwinian view has undergone considerable refinement and elaboration since its proposal over 150 years ago. First the genomic revolution, which provided Darwin's ideas with a molecular basis through the first decades of the twentieth century, transformed the subject and led to the neo-Darwinian synthesis, an amalgamation of classic Darwinism with population genetics and then with molecular genetics. But in more recent years, there is a growing realization that a molecular approach to understanding evolutionary dynamics is insufficient, that evolutionary biology's more fundamental challenge is to address the unresolved problem of complexity. How did biological complexity come about, and how can that complexity and its dynamic nature be understood? Our point is that Darwin's monumental thesis, with natural selection at its core, was just the beginning of a long process of refinement and elaboration, which has continued unabated to the present day.

Precisely the same process will need to operate with respect to the OOL problem. The DKS concept, simple in essence, does outline in the broadest terms the physico-chemical basis for abiogenesis. But that broad outline needs to be elaborated on through experimental investigation, so that the detailed mechanisms by which the DKS of simple chemical replicating systems could increase would be clarified. Already at this early stage, central elements of those mechanisms are becoming evident. Thus, there are preliminary indications that the process of abiogenesis was one of DKS enhancement through complexification [ 1 , 7 ]. More complex replicating systems, presenting a diversity of features and functions, appear to be able to replicate more effectively than simpler ones, and so are likely to be more stable in DKS terms (though this should not be interpreted to mean that any form of complexification will necessarily lead to enhanced DKS). The pertinent question is then: how does that process of complexification manifest itself? And this is where systems chemistry enters the scene [ 9 – 11 ]. By studying the dynamics of simple replicating molecular systems and the networks they establish, studies in system chemistry are beginning to offer insights into that process of replicative complexification. Following on from earlier work by Sievers & von Kiedrowski [ 27 ] and Lee et al . [ 28 ], more recent studies on RNA replicating systems by Lincoln & Joyce [ 29 ] and most recently by Vaidya et al . [ 30 ] suggest that network formation is crucial. Thus, Lincoln & Joyce [ 28 ] observed that a molecular network based on two cross-catalysing RNAs replicated rapidly and could be sustained indefinitely. By contrast, the most effective single molecule RNA replicator replicated slowly and was not sustainable. But in a more recent landmark experiment, Vaidya et al . [ 30 ] demonstrated that a cooperative cycle made up of three self-replicating RNAs could out-compete those same RNAs acting as individual replicators. The conclusion seems clear: molecular networks are more effective in establishing self-sustainable autocatalytic systems than single molecule replicators, just as was postulated by Eigen & Schuster [ 25 ] some 40 years ago.

Many key questions remain unanswered, however. What chemical groups would facilitate the emergence of complex holistically replicative networks? Are nucleic acids essential for the establishment of such networks, or could other chemical groups also express this capability? Is template binding the main mechanism by which molecular autocatalysis can take place, or can holistically autocatalytic sets be established through cycle closure without a reliance on template binding? How would the emergence of individual self-replicating entities within a larger holistically replicative network contribute to the stability of the network as a whole? How do kinetic and thermodynamic factors inter-relate in facilitating the maintenance of dynamically stable, but thermodynamically unstable, replicating systems [ 12 , 13 ]? As these questions suggest, our understanding of central issues remains rudimentary, and the road to discovery will probably be long and arduous. However, the key point of this essay has been to note that just as Darwin's simple concept of natural selection was able to provide a basis for an ongoing research programme in evolution, one that has been central to biological research for over 150 years, so the DKS concept may be able to offer a basis for ongoing studies in systems chemistry, one that may offer new insights into the rules governing evolutionary dynamics in simple replicating systems and, subsequently, for replicating systems of all kinds. Such a research programme, we believe, promises to further clarify the underlying relationship linking chemical and biological replicators.

In conclusion, it seems probably that we will never know the precise historic path by which life on the Earth emerged, but, very much in the Darwinian tradition, it seems we can now specify the essence of the ahistoric principles by which that process came about. Just as Darwin, in the very simplest of terms, pointed out how natural selection enabled simple life to evolve into complex life, so the recently proposed general theory of evolution [ 1 , 7 ] points out in simplest terms how simple, but fragile, replicating systems could have complexified into the intricate chemical systems of life. But, as discussed earlier, a detailed understanding of that process will have to wait until ongoing studies in systems chemistry reveal both the classes of chemical materials and the kinds of chemical pathways that simple replicating systems are able to follow in their drive towards greater complexity and replicative stability.

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What Is a Theory?

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Part of the Darwin exhibition.

But for scientists, a theory has nearly the opposite meaning. A theory is a well-substantiated explanation of an aspect of the natural world that can incorporate laws, hypotheses and facts. The theory of gravitation, for instance, explains why apples fall from trees and astronauts float in space. Similarly, the theory of evolution explains why so many plants and animals—some very similar and some very different—exist on Earth now and in the past, as revealed by the fossil record.

A theory not only explains known facts; it also allows scientists to make predictions of what they should observe if a theory is true. Scientific theories are testable. New evidence should be compatible with a theory. If it isn't, the theory is refined or rejected. The longer the central elements of a theory hold—the more observations it predicts, the more tests it passes, the more facts it explains—the stronger the theory.

Many advances in science—the development of genetics after Darwin's death, for example—have greatly enhanced evolutionary thinking. Yet even with these new advances, the theory of evolution still persists today, much as Darwin first described it, and is universally accepted by scientists.

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Abiogenesis

Reviewed by: BD Editors

Abiogenesis Definition

Abiogenesis is the creation of organic molecules by forces other than living organisms. While organisms can create carbon-carbon bonds relatively easily thanks to enzymes, to do so otherwise requires large inputs of energy. Early in the history of science, this fact was used to dispute evolution, as it could not be conceived how organic molecules could be produced from non-organic sources. The theory of abiogenesis as an evolutionary theory was given much credit when Stanley Miller conducted his famous experiment trying to prove the inorganic beginning of life.

Miller combined various gases that were though to exist in the earliest stages of Earth. These gases were combined in a chamber, and shocked with large amount of electricity for weeks at a time. After the trial, Miller would analyze the samples. He found that the molecules had begun the process of combining into more advanced molecules. Miller theorized that over billions of years, these molecules could combine into self-replicating versions, such as RNA and DNA. Further laboratory experiments confirmed these findings in later decades. Several very precise experiments have provided sufficient evidence that many of the molecular structures of cells could be created from inorganic solutions with an input of energy. Polypeptides (proteins) and RNA have both been synthesized in this way.

The synthesis of both proteins and RNA in the laboratory is a crucial piece of evidence for abiogenesis theory. It is though that the abiogenesis of these molecules could lead to self-replicating RNA molecules. Both proteins and RNA molecules are known to act as catalysts. These molecules, produced by abiogenesis, could catalyze important reactions that could lead to the replication of RNA and the production of complexes such as ribosome , which translate proteins from RNA messages. The formation of these two molecules through abiogenesis proves that the first steps in abiogenesis theory could have taken place. Due to the large amount of energy used, some scientists argue that abiogenesis theory does not consider the amount of lightning and other energy sources in the early atmosphere.

Abiogenesis Theory

Abiogenesis theory is the theory that all life started from inorganic molecules, which recombined in different ways due to energy input. These different forms eventually formed a self-replicating molecule, which may have used the other molecules produced by abiogenesis to start creating the basic structures of life, such as the cell.

Just as populations change over time in the evolution of organisms, the evolution of molecules involves the changing of molecules over time. Scientist speculate that the first self-replicating molecules were probably RNA molecules. Some RNA molecules have a known ability to catalyze the formation of new RNA molecules, as seen in the ribosomes of nearly all creatures on Earth. One of these early RNA molecules formed just right, so that it produced an RNA molecule that was identical to it. The concentration of this molecule in the prebiotic soup increased drastically, and the molecule further interacted with itself and some proteins formed around it, also through abiogenesis.

Eventually, the RNA molecule acquired mutations that allowed it to synthesize a protein that would produce more RNA. Other mutations caused proteins to be created that synthesized strands of DNA from RNA. Thus, the genome of the modern organism was born. Over millions of years of evolutionary history, changes slowly accumulated in these molecules, giving rise to the complexity of life we see today. Various scientist that study abiogenesis theory argue over the exact point that abiogenesis switches to biogenesis. Similar arguments can be seen in the case of whether or not viruses constitute living organisms. Abiogenesis, by definition, is simply the creation of organic molecules from inorganic sources. It does not necessarily imply where life begins.

Related Biology Term

• Evolution – The process that changes populations of organisms over time, adapting them to the environment.
• Inorganic – Molecules containing little carbon, not made in living organisms.
• Organic – Molecules synthesized in living organisms that contain many carbon-carbon bonds.
• Ribosome – One of the first cellular machines, capable of producing proteins from RNA molecules and amino acids.

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Definition of hypothesis

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

• proposition
• supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of hypothesis in a Sentence

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

Word History

Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do

1641, in the meaning defined at sense 1a

Phrases Containing hypothesis

• counter - hypothesis
• nebular hypothesis
• null hypothesis
• planetesimal hypothesis
• Whorfian hypothesis

Articles Related to hypothesis

This is the Difference Between a...

This is the Difference Between a Hypothesis and a Theory

In scientific reasoning, they're two completely different things

Dictionary Entries Near hypothesis

hypothermia

hypothesize

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“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 20 Jun. 2024.

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• Education Resources Information Center - Understanding Hypotheses, Predictions, Laws, and Theories
• Simply Psychology - Research Hypothesis: Definition, Types, & Examples
• Cornell University - The Learning Strategies Center - Hypothesis
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hypothesis , something supposed or taken for granted, with the object of following out its consequences (Greek hypothesis , “a putting under,” the Latin equivalent being suppositio ).

In planning a course of action, one may consider various alternatives , working out each in detail. Although the word hypothesis is not typically used in this case, the procedure is virtually the same as that of an investigator of crime considering various suspects. Different methods may be used for deciding what the various alternatives may be, but what is fundamental is the consideration of a supposal as if it were true, without actually accepting it as true. One of the earliest uses of the word in this sense was in geometry . It is described by Plato in the Meno .

The most important modern use of a hypothesis is in relation to scientific investigation . A scientist is not merely concerned to accumulate such facts as can be discovered by observation: linkages must be discovered to connect those facts. An initial puzzle or problem provides the impetus , but clues must be used to ascertain which facts will help yield a solution. The best guide is a tentative hypothesis, which fits within the existing body of doctrine. It is so framed that, with its help, deductions can be made that under certain factual conditions (“initial conditions”) certain other facts would be found if the hypothesis were correct.

The concepts involved in the hypothesis need not themselves refer to observable objects. However, the initial conditions should be able to be observed or to be produced experimentally, and the deduced facts should be able to be observed. William Harvey ’s research on circulation in animals demonstrates how greatly experimental observation can be helped by a fruitful hypothesis. While a hypothesis can be partially confirmed by showing that what is deduced from it with certain initial conditions is actually found under those conditions, it cannot be completely proved in this way. What would have to be shown is that no other hypothesis would serve. Hence, in assessing the soundness of a hypothesis, stress is laid on the range and variety of facts that can be brought under its scope. Again, it is important that it should be capable of being linked systematically with hypotheses which have been found fertile in other fields.

If the predictions derived from the hypothesis are not found to be true, the hypothesis may have to be given up or modified. The fault may lie, however, in some other principle forming part of the body of accepted doctrine which has been utilized in deducing consequences from the hypothesis. It may also lie in the fact that other conditions, hitherto unobserved, are present beside the initial conditions, affecting the result. Thus the hypothesis may be kept, pending further examination of facts or some remodeling of principles. A good illustration of this is to be found in the history of the corpuscular and the undulatory hypotheses about light .

Null hypothesis

Null hypothesis n., plural: null hypotheses [nʌl haɪˈpɒθɪsɪs] Definition: a hypothesis that is valid or presumed true until invalidated by a statistical test

Table of Contents

Null Hypothesis Definition

Null hypothesis is defined as “the commonly accepted fact (such as the sky is blue) and researcher aim to reject or nullify this fact”.

More formally, we can define a null hypothesis as “a statistical theory suggesting that no statistical relationship exists between given observed variables” .

In biology , the null hypothesis is used to nullify or reject a common belief. The researcher carries out the research which is aimed at rejecting the commonly accepted belief.

What Is a Null Hypothesis?

A hypothesis is defined as a theory or an assumption that is based on inadequate evidence. It needs and requires more experiments and testing for confirmation. There are two possibilities that by doing more experiments and testing, a hypothesis can be false or true. It means it can either prove wrong or true (Blackwelder, 1982).

For example, Susie assumes that mineral water helps in the better growth and nourishment of plants over distilled water. To prove this hypothesis, she performs this experiment for almost a month. She watered some plants with mineral water and some with distilled water.

In a hypothesis when there are no statistically significant relationships among the two variables, the hypothesis is said to be a null hypothesis. The investigator is trying to disprove such a hypothesis. In the above example of plants, the null hypothesis is:

There are no statistical relationships among the forms of water that are given to plants for growth and nourishment.

Usually, an investigator tries to prove the null hypothesis wrong and tries to explain a relation and association between the two variables.

An opposite and reverse of the null hypothesis are known as the alternate hypothesis . In the example of plants the alternate hypothesis is:

There are statistical relationships among the forms of water that are given to plants for growth and nourishment.

The example below shows the difference between null vs alternative hypotheses:

Alternate Hypothesis: The world is round Null Hypothesis: The world is not round.

Copernicus and many other scientists try to prove the null hypothesis wrong and false. By their experiments and testing, they make people believe that alternate hypotheses are correct and true. If they do not prove the null hypothesis experimentally wrong then people will not believe them and never consider the alternative hypothesis true and correct.

The alternative and null hypothesis for Susie’s assumption is:

• Null Hypothesis: If one plant is watered with distilled water and the other with mineral water, then there is no difference in the growth and nourishment of these two plants.
• Alternative Hypothesis:  If one plant is watered with distilled water and the other with mineral water, then the plant with mineral water shows better growth and nourishment.

The null hypothesis suggests that there is no significant or statistical relationship. The relation can either be in a single set of variables or among two sets of variables.

Most people consider the null hypothesis true and correct. Scientists work and perform different experiments and do a variety of research so that they can prove the null hypothesis wrong or nullify it. For this purpose, they design an alternate hypothesis that they think is correct or true. The null hypothesis symbol is H 0 (it is read as H null or H zero ).

Why is it named the “Null”?

The name null is given to this hypothesis to clarify and explain that the scientists are working to prove it false i.e. to nullify the hypothesis. Sometimes it confuses the readers; they might misunderstand it and think that statement has nothing. It is blank but, actually, it is not. It is more appropriate and suitable to call it a nullifiable hypothesis instead of the null hypothesis.

Why do we need to assess it? Why not just verify an alternate one?

In science, the scientific method is used. It involves a series of different steps. Scientists perform these steps so that a hypothesis can be proved false or true. Scientists do this to confirm that there will be any limitation or inadequacy in the new hypothesis. Experiments are done by considering both alternative and null hypotheses, which makes the research safe. It gives a negative as well as a bad impact on research if a null hypothesis is not included or a part of the study. It seems like you are not taking your research seriously and not concerned about it and just want to impose your results as correct and true if the null hypothesis is not a part of the study.

Development of the Null

In statistics, firstly it is necessary to design alternate and null hypotheses from the given problem. Splitting the problem into small steps makes the pathway towards the solution easier and less challenging. how to write a null hypothesis?

Writing a null hypothesis consists of two steps:

• Firstly, initiate by asking a question.
• Secondly, restate the question in such a way that it seems there are no relationships among the variables.

In other words, assume in such a way that the treatment does not have any effect.

The usual recovery duration after knee surgery is considered almost 8 weeks.

A researcher thinks that the recovery period may get elongated if patients go to a physiotherapist for rehabilitation twice per week, instead of thrice per week, i.e. recovery duration reduces if the patient goes three times for rehabilitation instead of two times.

Step 1: Look for the problem in the hypothesis. The hypothesis either be a word or can be a statement. In the above example the hypothesis is:

“The expected recovery period in knee rehabilitation is more than 8 weeks”

Step 2: Make a mathematical statement from the hypothesis. Averages can also be represented as μ, thus the null hypothesis formula will be.

In the above equation, the hypothesis is equivalent to H1, the average is denoted by μ and > that the average is greater than eight.

Step 3: Explain what will come up if the hypothesis does not come right i.e., the rehabilitation period may not proceed more than 08 weeks.

There are two options: either the recovery will be less than or equal to 8 weeks.

H 0 : μ ≤ 8

In the above equation, the null hypothesis is equivalent to H 0 , the average is denoted by μ and ≤ represents that the average is less than or equal to eight.

What will happen if the scientist does not have any knowledge about the outcome?

Problem: An investigator investigates the post-operative impact and influence of radical exercise on patients who have operative procedures of the knee. The chances are either the exercise will improve the recovery or will make it worse. The usual time for recovery is 8 weeks.

Step 1: Make a null hypothesis i.e. the exercise does not show any effect and the recovery time remains almost 8 weeks.

H 0 : μ = 8

In the above equation, the null hypothesis is equivalent to H 0 , the average is denoted by μ, and the equal sign (=) shows that the average is equal to eight.

Step 2: Make the alternate hypothesis which is the reverse of the null hypothesis. Particularly what will happen if treatment (exercise) makes an impact?

In the above equation, the alternate hypothesis is equivalent to H1, the average is denoted by μ and not equal sign (≠) represents that the average is not equal to eight.

Significance Tests

To get a reasonable and probable clarification of statistics (data), a significance test is performed. The null hypothesis does not have data. It is a piece of information or statement which contains numerical figures about the population. The data can be in different forms like in means or proportions. It can either be the difference of proportions and means or any odd ratio.

The following table will explain the symbols:

P-value is the chief statistical final result of the significance test of the null hypothesis.

• P-value = Pr(data or data more extreme | H 0 true)
• | = “given”
• Pr = probability
• H 0 = the null hypothesis

The first stage of Null Hypothesis Significance Testing (NHST) is to form an alternate and null hypothesis. By this, the research question can be briefly explained.

Null Hypothesis = no effect of treatment, no difference, no association Alternative Hypothesis = effective treatment, difference, association

When to reject the null hypothesis?

Researchers will reject the null hypothesis if it is proven wrong after experimentation. Researchers accept null hypothesis to be true and correct until it is proven wrong or false. On the other hand, the researchers try to strengthen the alternate hypothesis. The binomial test is performed on a sample and after that, a series of tests were performed (Frick, 1995).

Step 1: Evaluate and read the research question carefully and consciously and make a null hypothesis. Verify the sample that supports the binomial proportion. If there is no difference then find out the value of the binomial parameter.

Show the null hypothesis as:

H 0 :p= the value of p if H 0 is true

To find out how much it varies from the proposed data and the value of the null hypothesis, calculate the sample proportion.

Step 2: In test statistics, find the binomial test that comes under the null hypothesis. The test must be based on precise and thorough probabilities. Also make a list of pmf that apply, when the null hypothesis proves true and correct.

When H 0 is true, X~b(n, p)

N = size of the sample

P = assume value if H 0 proves true.

Step 3: Find out the value of P. P-value is the probability of data that is under observation.

Rise or increase in the P value = Pr(X ≥ x)

X = observed number of successes

P value = Pr(X ≤ x).

Step 4: Demonstrate the findings or outcomes in a descriptive detailed way.

• Sample proportion
• The direction of difference (either increases or decreases)

Perceived Problems With the Null Hypothesis

Variable or model selection and less information in some cases are the chief important issues that affect the testing of the null hypothesis. Statistical tests of the null hypothesis are reasonably not strong. There is randomization about significance. (Gill, 1999) The main issue with the testing of the null hypothesis is that they all are wrong or false on a ground basis.

There is another problem with the a-level . This is an ignored but also a well-known problem. The value of a-level is without a theoretical basis and thus there is randomization in conventional values, most commonly 0.q, 0.5, or 0.01. If a fixed value of a is used, it will result in the formation of two categories (significant and non-significant) The issue of a randomized rejection or non-rejection is also present when there is a practical matter which is the strong point of the evidence related to a scientific matter.

The P-value has the foremost importance in the testing of null hypothesis but as an inferential tool and for interpretation, it has a problem. The P-value is the probability of getting a test statistic at least as extreme as the observed one.

The main point about the definition is: Observed results are not based on a-value

Moreover, the evidence against the null hypothesis was overstated due to unobserved results. A-value has importance more than just being a statement. It is a precise statement about the evidence from the observed results or data. Similarly, researchers found that P-values are objectionable. They do not prefer null hypotheses in testing. It is also clear that the P-value is strictly dependent on the null hypothesis. It is computer-based statistics. In some precise experiments, the null hypothesis statistics and actual sampling distribution are closely related but this does not become possible in observational studies.

Some researchers pointed out that the P-value is depending on the sample size. If the true and exact difference is small, a null hypothesis even of a large sample may get rejected. This shows the difference between biological importance and statistical significance. (Killeen, 2005)

Another issue is the fix a-level, i.e., 0.1. On the basis, if a-level a null hypothesis of a large sample may get accepted or rejected. If the size of simple is infinity and the null hypothesis is proved true there are still chances of Type I error. That is the reason this approach or method is not considered consistent and reliable. There is also another problem that the exact information about the precision and size of the estimated effect cannot be known. The only solution is to state the size of the effect and its precision.

Null Hypothesis Examples

Here are some examples:

Example 1: Hypotheses with One Sample of One Categorical Variable

Among all the population of humans, almost 10% of people prefer to do their task with their left hand i.e. left-handed. Let suppose, a researcher in the Penn States says that the population of students at the College of Arts and Architecture is mostly left-handed as compared to the general population of humans in general public society. In this case, there is only a sample and there is a comparison among the known population values to the population proportion of sample value.

• Research Question: Do artists more expected to be left-handed as compared to the common population persons in society?
• Response Variable: Sorting the student into two categories. One category has left-handed persons and the other category have right-handed persons.
• Form Null Hypothesis: Arts and Architecture college students are no more predicted to be lefty as compared to the common population persons in society (Lefty students of Arts and Architecture college population is 10% or p= 0.10)

Example 2: Hypotheses with One Sample of One Measurement Variable

A generic brand of antihistamine Diphenhydramine making medicine in the form of a capsule, having a 50mg dose. The maker of the medicines is concerned that the machine has come out of calibration and is not making more capsules with the suitable and appropriate dose.

• Research Question: Does the statistical data recommended about the mean and average dosage of the population differ from 50mg?
• Response Variable: Chemical assay used to find the appropriate dosage of the active ingredient.
• Null Hypothesis: Usually, the 50mg dosage of capsules of this trade name (population average and means dosage =50 mg).

Example 3: Hypotheses with Two Samples of One Categorical Variable

Several people choose vegetarian meals on a daily basis. Typically, the researcher thought that females like vegetarian meals more than males.

• Research Question: Does the data recommend that females (women) prefer vegetarian meals more than males (men) regularly?
• Response Variable: Cataloguing the persons into vegetarian and non-vegetarian categories. Grouping Variable: Gender
• Null Hypothesis: Gender is not linked to those who like vegetarian meals. (Population percent of women who eat vegetarian meals regularly = population percent of men who eat vegetarian meals regularly or p women = p men).

Example 4: Hypotheses with Two Samples of One Measurement Variable

Nowadays obesity and being overweight is one of the major and dangerous health issues. Research is performed to confirm that a low carbohydrates diet leads to faster weight loss than a low-fat diet.

• Research Question: Does the given data recommend that usually, a low-carbohydrate diet helps in losing weight faster as compared to a low-fat diet?
• Response Variable: Weight loss (pounds)
• Explanatory Variable: Form of diet either low carbohydrate or low fat
• Null Hypothesis: There is no significant difference when comparing the mean loss of weight of people using a low carbohydrate diet to people using a diet having low fat. (population means loss of weight on a low carbohydrate diet = population means loss of weight on a diet containing low fat).

Example 5: Hypotheses about the relationship between Two Categorical Variables

A case-control study was performed. The study contains nonsmokers, stroke patients, and controls. The subjects are of the same occupation and age and the question was asked if someone at their home or close surrounding smokes?

• Research Question: Did second-hand smoke enhance the chances of stroke?
• Variables: There are 02 diverse categories of variables. (Controls and stroke patients) (whether the smoker lives in the same house). The chances of having a stroke will be increased if a person is living with a smoker.
• Null Hypothesis: There is no significant relationship between a passive smoker and stroke or brain attack. (odds ratio between stroke and the passive smoker is equal to 1).

Example 6: Hypotheses about the relationship between Two Measurement Variables

A financial expert observes that there is somehow a positive and effective relationship between the variation in stock rate price and the quantity of stock bought by non-management employees

• Response variable- Regular alteration in price
• Explanatory Variable- Stock bought by non-management employees
• Null Hypothesis: The association and relationship between the regular stock price alteration ($) and the daily stock-buying by non-management employees ($) = 0.

Example 7: Hypotheses about comparing the relationship between Two Measurement Variables in Two Samples

• Research Question: Is the relation between the bill paid in a restaurant and the tip given to the waiter, is linear? Is this relation different for dining and family restaurants?
• Explanatory Variable- total bill amount
• Response Variable- the amount of tip
• Null Hypothesis: The relationship and association between the total bill quantity at a family or dining restaurant and the tip, is the same.

Try to answer the quiz below to check what you have learned so far about the null hypothesis.

Choose the best answer. 

Send Your Results (Optional)

• Blackwelder, W. C. (1982). “Proving the null hypothesis” in clinical trials. Controlled Clinical Trials , 3(4), 345–353.
• Frick, R. W. (1995). Accepting the null hypothesis. Memory & Cognition, 23(1), 132–138.
• Gill, J. (1999). The insignificance of null hypothesis significance testing. Political Research Quarterly , 52(3), 647–674.
• Killeen, P. R. (2005). An alternative to null-hypothesis significance tests. Psychological Science, 16(5), 345–353.

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Last updated on June 16th, 2022

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