what is descriptive correlational research

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What Is Descriptive Correlational Method?

In scientific research, a descriptive correlational method refers to a type of study in which information is collected without making any changes to the study subject. This means that the experimenter cannot directly interact with the environment in which she is studying in a way that would cause any changes related to the experiment. These types of studies are also sometimes known as observational studies.

All descriptive correlational method studies have the same basic property of avoiding any direct changes in the environment of the study. However, there are a number of different types of descriptive correlational methods that each perform research in a slightly different way. Some scientists and researchers prefer to meet with a group of people one time and ask them questions. This is called a cross-sectional study, and as long as the scientists do not change the behavior of the people they are interacting with, it is a descriptive correlational study. Some researchers prefer to keep track of people over time. This is called a longitudinal study. In these cases, behavior must remain unchanged, but the subjects are often brought back in for further questions. Descriptive studies generally use surveys or other methods of data collection that rely on existing records.

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Descriptive Correlational: Descriptive vs Correlational Research

Descriptive research and Correlational research are two important types of research studies that help researchers make ambitious and measured decisions in their respective fields. Both descriptive research and correlational research are used in descriptive correlational research. 

Descriptive research is defined as a research method that involves observing behavior to describe attributes objectively and systematically. A descriptive research project seeks to comprehend phenomena or groups in depth.

Correlational research , on the other hand, is a method that describes and predicts how variables are naturally related in the real world without the researcher attempting to alter them or assign causation between them.

The main objective of descriptive research is to create a snapshot of the current state of affairs, whereas correlational research helps in comparing two or more entities or variables.

What is descriptive correlational research?

Descriptive correlational research is a type of research design that tries to explain the relationship between two or more variables without making any claims about cause and effect. It includes collecting and analyzing data on at least two variables to see if there is a link between them. 

In descriptive correlational research, researchers collect data to explain the variables of interest and figure out how they relate. The main goal is to give a full account of the variables and how they are related without changing them or assuming that one thing causes another.

In descriptive correlational research, researchers do not change any variables or try to find cause-and-effect connections. Instead, they just watch and measure the variables of interest and then look at the patterns and relationships that emerge from the data.

Experimental research involves the independent variable to see how it affects the dependent variable, while descriptive correlational research just describes the relationship between variables. 

In descriptive correlational research, correlational research designs measure the magnitude and direction of the relationship between two or more variables, revealing their associations. At the outset creating initial equivalence between the groups or variables being compared is essential in descriptive correlational research

The independent variable occurs prior to the measurement of the measured dependent variable in descriptive correlational research. Its goal is to explain the traits or actions of a certain population or group and look at the connections between independent and dependent variables.

How are descriptive research and correlational research carried out?

Descriptive research is carried out using three methods, namely:  

• Case studies – Case studies involve in-depth research and study of individuals or groups. Case studies lead to a hypothesis and widen a further scope of studying a phenomenon. However, case studies should not be used to determine cause and effect as they don’t have the capacity to make accurate predictions.
• Surveys – A survey is a set of questions that is administered to a population, also known as respondents. Surveys are a popular market research tool that helps collect meaningful insights from the respondents. To gather good quality data, a survey should have good survey questions, which should be a balanced mix of open-ended and close-ended questions .
• Naturalistic Observation – Naturalistic observations are carried out in the natural environment without disturbing the person/ object in observation. It is much like taking notes about people in a supermarket without letting them know. This leads to a greater validity of collected data because people are unaware they are being observed here. This tends to bring out their natural characteristics.

Correlational research also uses naturalistic observation to collect data. However, in addition, it uses archival data to gather information. Archival data is collected from previously conducted research of a similar nature. Archival data is collected through primary research.

In contrast to naturalistic observation, information collected through archived is straightforward. For example, counting the number of people named Jacinda in the United States using their social security number.  

Descriptive Research vs Correlational Research

Features of Descriptive Correlational Research

The key features of descriptive correlational research include the following:

01. Description

The main goal, just like with descriptive research, is to describe the variables of interest thoroughly. Researchers aim to explain a certain group or event’s traits, behaviors, or attitudes. 

02. Relationships

Like correlational research, descriptive correlational research looks at how two or more factors are related. It looks at how variables are connected to each other, such as how they change over time or how they are linked.

03. Quantitative analysis

Most methods for analyzing quantitative analysis data are used in descriptive correlational research. Researchers use statistical methods to study and measure the size and direction of relationships between variables.

04. No manipulation

As with correlational research, the researcher does not change or control the variables. The data is taken in its natural environment without any changes or interference.

05. Cross-sectional or longitudinal

Cross-sectional or longitudinal designs can be used for descriptive correlational research. It collects data at one point in time, while longitudinal research collects data over a long period of time to look at changes and relationships over time. 

Examples of descriptive correlational research

For example, descriptive correlational research could look at the link between a person’s age and how much money they make. The researcher would take a sample of people’s ages and incomes and then look at the data to see if there is a link between the two factors.

• Example 1 : A research project is done to find out if there is a link between how long college students sleep and how well they do in school. They keep track of how many hours kids sleep each night and what their GPAs are. By studying the data, the researcher can describe how the students sleep and find out if there is a link between how long they sleep and how well they do in school.
• Example 2 : A researcher wants to know how people’s exercise habits affect their physical health if they are between the ages of 40 and 60. They take notes on things like how often and how hard you work out, your body mass index (BMI), blood pressure, and cholesterol numbers. By analyzing the data, the researcher can describe the participants’ exercise habits and physical health and look for any links between these factors.
• Example 3 : Let’s say a researcher wants to find out if college students who work out feel less stressed. Using a poll, the researcher finds out how many hours students spend exercising each week and how stressed they feel. By looking at the data, the researcher may find that there is a moderate negative correlation between exercise and stress levels. This means that as exercise grows, stress levels tend to go down. 

Descriptive correlational research is a good way to learn about the characteristics of a population or group and the relationships between its different parts. It lets researchers describe variables in detail and look into their relationships without suggesting that one variable caused another. 

Descriptive correlational research gives useful insights and can be used as a starting point for more research or to come up with hypotheses. It’s important to be aware of the problems with this type of study, such as the fact that it can’t show cause and effect and relies on cross-sectional data. 

Still, descriptive correlational research helps us understand things and makes making decisions in many areas easier.

QuestionPro is a very useful tool for descriptive correlational research. Its many features and easy-to-use interface help researchers collect and study data quickly, giving them a better understanding of the characteristics and relationships between variables in a certain population or group. 

The different kinds of questions, analytical research tools, and reporting features on the software improve the research process and help researchers come up with useful results. QuestionPro makes it easier to do descriptive correlational research, which makes it a useful tool for learning important things and making decisions in many fields.

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Descriptive Correlational Design in Research

Looking for descriptive correlational design definition and meaning? This research paper example explains all the details of this quantitative research method.

Introduction

Why use descriptive correlational design.

Descriptive statistics refers to information that has been analyzed in order to reveal the basic features of data collected or used in a study (Fowler, 2013). They provide researchers with summaries and other critical information regarding study samples and measures. The two main types include measures of central tendency and the measure of spread (Kothari, 2004). A common occurrence when using descriptive data is the emergence of certain patterns that make it easy for researchers to understand and make sense of data. The statistical data can either be used for further research studies or as an independent entity that can be used to make conclusions (Fowler, 2013). Certain research situations involve the use of only descriptive statistics because of the large sample sizes and complexity of data. A study that involves the computation of mean, median, and mode would require descriptive statistics (Yin, 2009).

For instance, they would be sued in a study that aims to find the media score in a class of 100 students with different test results. On the other hand, surveys, case studies, and naturalistic observations can only be successfully conducted using descriptive statistics. An example of research that involved descriptive statistics only is a research study conducted by Andreyeva, Michaud, and Soest (2007) to investigate obesity and health in Europeans aged 50 years and older. The study aimed to study the prevalence of obesity and related health complications among Europeans aged 50 years and above (Andreyeva, Michaud & Soest, 2007). The study involved the collection of data from participants without altering any environmental factors. It was published in the Journal of Public Health in 2007.

Descriptive correlational design is used in research studies that aim to provide static pictures of situations as well as establish the relationship between different variables (McBurney & White, 2009). In correlational research, two variables, such as the height and weight of individuals, are studied to establish their relationship. One of the research topics that can be studied using a descriptive correctional design is the height and weight of college students between the ages of 18 and 25. This study can be tied to their nutrition or frequency of taking meals in a day. The design is appropriate for the aforementioned topic because in conducting the study, the researcher will be required to collect data based on the behavior or attitudes of the participants.

For instance, the number of times the participants eat a certain meal or take a certain beverage. On the other hand, the researcher will be required to establish the relationship between the frequency of taking certain meals or beverages and gains in weight. The researcher could also establish the relationship between the weight and height of the participants. The study design would also enable the researcher to determine changes in the participants’ behaviors or attitudes over time in order to determine how these changes affect the outcomes or possible trends that could emerge in the future (Monsen & Horn, 2007).

Do SAT scores determine the GPA achieved by college students? This research question has both predictor and criterion variables. In this research question, SAT scores represent the predictor variable, and college GPA represents the criterion variable. College GPA is the criterion variable because it is the component being predicted using students’ SAT scores. On the other hand, SAT scores are the predictor variable because they determine the GPA attained in college. The research question seeks to determine whether students’ SAT scores predict the GPA scores they attain in college.

This research paper focused on descriptive correlation design definition and goals. This quantitative research method aims to describe two or more variables and their relationships. Descriptive correlation design can provide a picture of the current state of affairs. For instance, in psychology, it can be a picture of a given group of individuals, their thoughts, behaviors, or feelings.

Andreyeva, T., Michaud, P. C., & Soest, A. (2007). Obesity and Health in Europeans Aged 50 Years and Older. Public Health 121 (1), 497-509.

Fowler, F. J. (2013). Survey Research Methods . New York, NY: SAGE Publications.

Kothari, C. R. (2004). Research Methodology: Methods and Techniques . New York, NY: New Age International.

McBurney, D. & White, T. (2009). Research Methods . New York, NY: Cengage Learning.

Monsen, E. R & Horn, L. V. (2007). Research: Successful Approaches . New York: American Dietetic Association.

Yin, R. K. (2009). Case Study Research: Design and Methods . New York, NY: SAGE Publications.

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IvyPanda. (2020, July 6). Descriptive Correlational Design in Research. https://ivypanda.com/essays/descriptive-statistics-and-correlational-design/

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Correlational Research vs. Descriptive Research

What's the difference.

Correlational research and descriptive research are both methods used in scientific inquiry, but they differ in their objectives and approaches. Correlational research aims to examine the relationship between two or more variables and determine the strength and direction of their association. It seeks to establish whether a relationship exists, but it does not imply causation. On the other hand, descriptive research focuses on describing and documenting the characteristics or behaviors of a particular group or phenomenon. It aims to provide a detailed and accurate account of the subject under study, without attempting to establish relationships or causality. While correlational research explores connections between variables, descriptive research provides a comprehensive snapshot of a specific situation or group.

Further Detail

Introduction.

Research plays a crucial role in expanding our knowledge and understanding of various phenomena. Two common types of research methods used in social sciences are correlational research and descriptive research. While both approaches aim to gather information and provide insights, they differ in their objectives, designs, and data analysis techniques. In this article, we will explore the attributes of correlational research and descriptive research, highlighting their similarities and differences.

Correlational Research

Correlational research is a quantitative research method that aims to examine the relationship between two or more variables. It seeks to determine whether a relationship exists, the strength of the relationship, and the direction of the relationship. This type of research does not involve manipulating variables or establishing causality. Instead, it focuses on measuring and analyzing the degree of association between variables.

In correlational research, data is collected through surveys, questionnaires, observations, or existing datasets. Researchers use statistical techniques, such as correlation coefficients, to analyze the data and determine the strength and direction of the relationship. The results of correlational research can be presented in the form of scatter plots, correlation matrices, or regression analyses.

One of the key advantages of correlational research is its ability to explore relationships between variables that cannot be manipulated or controlled. For example, researchers can examine the relationship between smoking and lung cancer by collecting data from individuals without intervening in their behavior. Correlational research also allows for the examination of complex relationships involving multiple variables, providing a more comprehensive understanding of the phenomenon under investigation.

However, correlational research has limitations. It cannot establish causality, meaning that it cannot determine whether changes in one variable directly cause changes in another. Additionally, correlational research relies heavily on the quality and accuracy of the data collected. If the data is flawed or incomplete, the results may be misleading or inaccurate. Despite these limitations, correlational research remains a valuable tool for exploring relationships and generating hypotheses for further investigation.

Descriptive Research

Descriptive research, as the name suggests, aims to describe and document the characteristics, behaviors, or conditions of a particular population or phenomenon. It focuses on providing an accurate and detailed account of the subject under study without attempting to establish relationships or causality. Descriptive research is often used in the early stages of a research project to gain a better understanding of the topic or to generate hypotheses for further investigation.

Data in descriptive research is collected through various methods, including surveys, interviews, observations, or existing records. Researchers aim to collect comprehensive and representative data to ensure the accuracy and reliability of their findings. The collected data is then analyzed using descriptive statistics, such as frequencies, percentages, means, or standard deviations, to summarize and present the information in a meaningful way.

One of the main advantages of descriptive research is its ability to provide a detailed and comprehensive account of a particular phenomenon or population. It allows researchers to gather information about various aspects, such as demographics, behaviors, attitudes, or opinions, which can be useful for decision-making or policy development. Descriptive research also provides a foundation for further research by identifying gaps in knowledge or areas that require further investigation.

However, descriptive research also has limitations. It does not involve manipulation of variables or testing of hypotheses, which limits its ability to establish causality or determine the underlying mechanisms of a phenomenon. Descriptive research is also susceptible to biases and errors, such as social desirability bias or sampling errors, which can affect the accuracy and generalizability of the findings. Despite these limitations, descriptive research remains an essential tool for providing a detailed and accurate description of various phenomena.

Comparing Correlational Research and Descriptive Research

While correlational research and descriptive research have distinct objectives and designs, they also share some similarities. Both approaches are quantitative in nature, relying on the collection and analysis of numerical data. They also involve the use of statistical techniques to analyze the data and draw conclusions. Additionally, both types of research can be conducted using various data collection methods, such as surveys, questionnaires, or observations.

However, the main difference between correlational research and descriptive research lies in their objectives and focus. Correlational research aims to examine the relationship between variables, while descriptive research focuses on providing a detailed description of a particular phenomenon or population. Correlational research seeks to determine the strength and direction of the relationship, whereas descriptive research aims to document and summarize the characteristics or behaviors of the subject under study.

Another difference between the two approaches is their data analysis techniques. Correlational research involves the use of correlation coefficients or regression analyses to determine the relationship between variables. On the other hand, descriptive research relies on descriptive statistics, such as frequencies or means, to summarize and present the collected data. While both approaches use statistical techniques, the specific methods employed differ based on the research objectives.

Furthermore, correlational research and descriptive research differ in their ability to establish causality. Correlational research cannot determine causality, as it does not involve manipulation of variables or control over extraneous factors. It can only identify associations between variables. In contrast, descriptive research does not aim to establish causality and focuses solely on describing the subject under study.

Despite their differences, both correlational research and descriptive research have their own strengths and limitations. Correlational research allows for the exploration of relationships between variables that cannot be manipulated, providing valuable insights and generating hypotheses for further investigation. Descriptive research, on the other hand, provides a detailed and accurate description of a particular phenomenon or population, serving as a foundation for decision-making or further research.

Correlational research and descriptive research are two common research methods used in social sciences. While correlational research aims to examine the relationship between variables, descriptive research focuses on providing a detailed description of a particular phenomenon or population. Both approaches have their own strengths and limitations, and the choice between them depends on the research objectives and the nature of the subject under study. By understanding the attributes of correlational research and descriptive research, researchers can make informed decisions about the most appropriate method to use in their studies, ultimately contributing to the advancement of knowledge in their respective fields.

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Home » Correlational Research – Methods, Types and Examples

Correlational Research – Methods, Types and Examples

Table of Contents

Correlational research is a type of non-experimental research that investigates the relationship between two or more variables. Unlike experimental research, it does not involve manipulation of variables but rather observes and measures them as they naturally occur. The primary aim is to determine whether a statistical relationship exists between the variables and, if so, the strength and direction of that relationship.

This article explores the definition, methods, types, and practical examples of correlational research while highlighting its advantages and limitations.

Correlational Research

Correlational research examines whether and how variables are related. It seeks to identify patterns of association, which can provide insights into how one variable might predict or relate to another. However, it does not establish causation, meaning it cannot determine whether one variable causes changes in another.

For example:

• A study investigating the relationship between daily screen time and sleep quality may find a negative correlation, where higher screen time is associated with poorer sleep quality.

When to Use Correlational Research

• Exploratory Studies: When exploring new areas of research to identify potential relationships between variables.
• Ethical Constraints: When manipulation of variables is impractical or unethical, such as studying the link between smoking and lung health.
• Prediction: When predicting outcomes based on known relationships, such as predicting academic success from study habits.
• Analyzing Trends: Understanding how variables interact over time, like temperature and electricity consumption.

Types of Correlational Research

1. positive correlation.

• Definition: As one variable increases, the other also increases.
• The relationship between exercise frequency and physical fitness level.

2. Negative Correlation

• Definition: As one variable increases, the other decreases.
• The relationship between stress levels and job satisfaction.

3. No Correlation

• Definition: No consistent relationship exists between the variables.
• The relationship between shoe size and intelligence.

4. Linear Correlation

• Definition: The relationship between variables follows a straight-line pattern.
• The relationship between hours studied and exam performance.

5. Nonlinear (Curvilinear) Correlation

• Definition: The relationship between variables follows a curved or non-linear pattern.
• The relationship between arousal and performance, as per the Yerkes-Dodson Law.

Methods of Correlational Research

1. observational studies.

• Description: Observing and recording variables as they occur naturally without intervention.
• Observing how classroom participation relates to academic performance.

2. Surveys and Questionnaires

• Description: Collecting self-reported data from participants about variables of interest.
• Examining the correlation between social media usage and self-esteem using a questionnaire.

3. Archival Research

• Description: Analyzing pre-existing data to identify relationships between variables.
• Analyzing historical temperature and rainfall data to study climate patterns.

4. Cross-Sectional Studies

• Description: Examining data from a population at a single point in time.
• Investigating the correlation between age and technology adoption in a specific year.

5. Longitudinal Studies

• Description: Tracking the same variables over a period of time to observe changes in relationships.
• Studying the correlation between income levels and health outcomes over a decade.

Steps to Conduct Correlational Research

1. define the research problem.

• Clearly state the variables and the research question.
• Example: Is there a relationship between exercise frequency and mental health?

2. Choose the Research Method

• Decide whether to use surveys, observational studies, or archival research based on the variables and context.

3. Collect Data

• Gather data using appropriate tools such as surveys, observation, or secondary datasets.

4. Analyze the Data

• Use statistical tools like Pearson’s correlation coefficient, Spearman’s rank correlation, or scatterplots to analyze relationships.

5. Interpret Results

• Determine the strength and direction of the correlation and discuss its implications.

6. Report Findings

• Present results with clear explanations of the correlation, supported by visual aids like scatterplots or correlation matrices.

Examples of Correlational Research

1. education.

• Research Question: Is there a relationship between attendance rates and academic performance?
• Method: Analyze attendance records and exam scores of students.
• Finding: A positive correlation indicates that higher attendance is associated with better performance.
• Research Question: How does physical activity correlate with mental well-being?
• Method: Survey participants about their exercise habits and self-reported mental health scores.
• Finding: A positive correlation suggests that more frequent exercise improves mental well-being.

3. Business

• Research Question: Does employee satisfaction correlate with productivity levels?
• Method: Use employee surveys and productivity data.
• Finding: A positive correlation highlights that satisfied employees tend to be more productive.

4. Environmental Studies

• Research Question: Is there a correlation between air pollution levels and respiratory health issues?
• Method: Analyze health records and air quality indices from different regions.
• Finding: A negative correlation shows that higher pollution levels are linked to increased respiratory problems.

Advantages of Correlational Research

• Ethical Flexibility: Can study relationships where experimentation is unethical.
• Exploratory Potential: Identifies potential relationships for further investigation.
• Wide Application: Applicable across disciplines like psychology, health, business, and education.
• Cost-Effective: Often less expensive than experimental research.
• Supports Predictions: Useful for predicting trends based on observed relationships.

Limitations of Correlational Research

• Cannot Establish Causation: Correlation does not imply causation; variables may be related without one causing the other.
• Example: The correlation between ice cream sales and drowning incidents may be due to hot weather as a third variable.
• Subjectivity in Data Collection: Surveys and self-reports may introduce bias.
• Overgeneralization: Findings from correlational research may not apply to all populations or settings.

Statistical Tools for Correlational Research

• Values range from -1 (strong negative correlation) to +1 (strong positive correlation).
• Spearman’s Rank Correlation: Used for non-linear relationships or ordinal data.
• Scatterplots: Visual representation of the relationship between variables.
• Regression Analysis: Explores the predictive relationship between variables.

Correlational research is an invaluable tool for understanding relationships between variables. By identifying associations, it provides insights that inform predictions, shape policies, and guide further research. While it cannot establish causation, its flexibility, and applicability across disciplines make it a powerful method for exploring patterns and trends in data. With careful design, analysis, and interpretation, correlational research can significantly contribute to knowledge and decision-making.

• Creswell, J. W. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . Sage Publications.
• Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences . Routledge.
• Gravetter, F. J., & Forzano, L. B. (2018). Research Methods for the Behavioral Sciences . Cengage Learning.
• Babbie, E. R. (2020). The Practice of Social Research . Cengage Learning.
• Field, A. (2017). Discovering Statistics Using IBM SPSS Statistics . Sage Publications.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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