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Correlational Studies

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Correlational Studies

Correlational studies are a non-experimental research method used to understand the linear relationship/association between two variables determined by statistical analysis.

In this type of research, results are determined based on observations between variables rather than manipulation of variables (experimental techniques). Correlational research aims to observe how strongly the variables are associated.

  • In correlational research, we first make a hypothesis.
  • Based on the hypothesis, we identify the variables.
  • According to the scientific research process, we should operationalise the variables, i.e., define the variable and how to measure it in the study.

    An example of an operationalised correlational hypothesis is: 'It is hypothesised that there is a relationship between scores on an IQ test (measuring intelligence) and school attendance'.

  • Once we establish the operationalised correlational hypothesis, we can conduct the research. There are several types of correlational studies discussed below.
  • The final phase is analysis.

What are the different types of correlational studies?

Three types of correlation studies exist, and we will describe them in detail below, with examples and the advantages and disadvantages of each type.

Naturalistic observation

In naturalistic observation correlation studies, we record observations of variables in a natural setting. This is a non-experimental method in which no variables are manipulated.

An example scenario for this type of correlational research is researchers going to a supermarket (natural setting) and observing how many people buy ice cream on a hot day.

A strength of naturalistic observational research is that it allows researchers to observe participants in a natural setting.

Participants are more likely to behave indifferently than in an artificial environment, which increases the power of the results. However, some limitations should be considered, such as the difficulty in limiting confounding factors, which can affect and reduce validity.

Survey method

In this method, surveys/questionnaires are used to measure the researchers' variables.

An example would be using questionnaires to determine the highest level of education and socioeconomic status. Such a survey aims to find out if there is a relationship between the level of education and the individual's income.

The advantages of this research method are that it is relatively inexpensive, does not take too much time, and can recruit many participants in a short period of time.

This method usually uses random samples for recruitment, so the research results are more generalisable. However, respondents may answer in a 'socially desirable' manner rather than answering honestly, which reduces the validity of the results.

Archival research

Archival research is a type of correlational research that uses secondary data, such as previous research, case studies, historical documents, and medical registries to measure variables.

Using the Children's Health Foundation Paediatric Asthma Registry to observe the relationship between asthma and prevalence in children is an example of archival research.

The advantage of correlational archival research is that it can be cheaper than alternative methods. Data is readily available, and researchers can obtain data that may no longer be collected, such as documents from historical periods.

Nevertheless, some disadvantages should be considered, such as the researcher having no control over data collection methods. It is then difficult to determine if the data is reliable/valid as data may be missing that is needed for the research.

Interpreting correlational studies results

In statistical analysis of correlation data, a correlation coefficient is calculated.

The correlation coefficient is a measure that determines the strength of the relationship between the two variables.

The values of the correlation coefficient range from +1 to -1.

A positive number indicates a positive relationship between the variables. This means that if one variable increases, the other is also expected to increase. A negative coefficient indicates a negative relationship between the variables. If one variable increases, the other is expected to decrease. A coefficient of 0 indicates that there is no relationship between the two variables.

The value of the correlation coefficient determines the strength of the correlation data:

  • No correlation - 0.
  • Weak correlation - 0.1- 0.39.
  • Moderate correlation - 0.4 - 0.69.
  • Strong correlation - 0.7 - 0.99.
  • Perfect correlation - 1.

When reporting correlation data, scatter plots are typically used to show the relationship between variables by plotting the data. We can then visually see the strength of the correlation and the direction between the variables (see figure below). If the data points are close to the gradient line and have a positive gradient, then this indicates a positive relationship. If the gradient is negative, the association is negative.

Correlational Studies Scatterplots showing positive negative and no correlation between variables StudySmarter

Scatterplots showing positive, negative and no correlation between variables, Hung, Bounsanga & Voss (2017)

Use of correlational studies in psychology research

Correlational research has many uses in psychology, such as providing preliminary results to determine whether we should conduct further research.

  • This can help understand the reasons why we found a correlation.
  • This type of research is also commonly used to determine a relationship between new and established measures, such as between the results of two different scales measuring anxiety.
  • If there is strong positive correlation, the scale has high concurrent validity, i.e., both scales measure the same thing. Such research has important implications for the clinical setting.

Correlational study advantages and disadvantages in psychology

As mentioned earlier, there are many advantages to using correlations as a research method, but let us consider the disadvantages.

For example, we can't establish cause and effect.

Cause and effect mean that although research can establish a relationship between two variables, it cannot infer whether one of the variables causes a change in the other or vice versa.

Since correlational studies only measure the co-variables, other potential confounding factors are not considered. The confounding variables may be a better explanatory factor for the study's outcome, making it difficult to determine the validity of the results.

Correlational Studies - Key takeaways

  • Correlation studies are a non-experimental research method used to understand the linear relationship/association between two variables.
  • The three types of correlational studies are naturalistic observational studies, surveys, and archival correlational studies.
  • In the statistical analysis of correlational data, a correlation coefficient is calculated.
    • It tells researchers about the strength and direction of a relationship between two variables. The calculated value can range from -1 to +1.
  • Correlation research has many uses in psychology, for example, to obtain preliminary results that inform whether further research should be conducted.

Frequently Asked Questions about Correlational Studies

Correlational studies are a non-experimental research method used to understand the linear relationship/association between two variables determined by statistical analysis. 

In this type of research, results are determined based on observations between variables rather than manipulation of variables (experimental techniques). Correlational research aims to observe how strongly the variables are associated.

The purpose of correlational research is to identify if there is a relationship between two variables and, if so, how strongly associated these variables are.

The hypothesis for correlational studies should highlight the variables being investigated and should be operationalised. This means that the variables should be clearly defined and should state how they will be measured in the study. (e.g., measuring anxiety using the Generalised Anxiety Disorder Scale).

The three types of correlational studies are naturalistic observational, survey and archival correlational studies.

An example of a correlational study would be observing the number of ice creams sold on the hottest day in the supermarket.

Final Correlational Studies Quiz

Question

Why are correlational studies considered a non-experimental research method?

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Answer

Experimental methods involve manipulating variables. However, this is not a requirement of correlational data as variables are measured via observational techniques.

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Question

What are the three types of correlational studies?

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Answer

Natural observational, survey and archival are three types of correlational research.

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Question

What would be the most appropriate type of correlation to use if a researcher was investigating a relationship between the amount of time spent playing video games and aggressiveness?

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Answer

Surveys would be the most appropriate method, as respondents could complete a questionnaire that includes questions concerning identifying time spent playing games and a scale that measures aggressiveness.

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Question

 What type of data does archival correlational research use?

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Answer

Archival correlation research uses secondary sources to collect data, such as historical documents, previous research, and case studies.

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Question

What advantage does naturalistic observational correlational research hold over the other types?

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Answer

As the research is carried out in a natural setting, participants are more likely to act in their ‘usual’ manner. Therefore, results can be considered highly valid.

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Question

What do the negative and positive signs before the correlation coefficient number indicate?

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Answer

The sign before the coefficient value indicates the direction of the association/relationship between co-variables. A negative value is indicative of a negative relationship, and a positive number is indicative of a positive relationship between the variables.

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Question

A correlation coefficient of -0.7 was reported. How would you interpret these results?

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Answer

A strong, negative correlation was found between the variables.

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Question

What do scatter plots tell us about correlational data? 


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Answer

Scatter plots provide visual data of the strength of association and direction found between co-variables. If the data points are close to the gradient line and have a positive gradient, this indicates a positive relationship. If the gradient is negative, the association is negative.

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Question

What are the advantages of using correlation studies?

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Answer

  • Correlational research has many uses in psychology, such as providing preliminary results to determine whether further research should be conducted to understand the reasons for finding the association.
  • It can be used to determine if there is a relationship between new and established measures, for example, between the results of two different scales measuring anxiety. If a strong positive correlation is found, the scale has high concordant validity, i.e., both scales measure the same thing. This has important implications for the clinical setting.

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Question

What are the disadvantages of using correlational studies?

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Answer

  • Cause and effect cannot be established, so research cannot conclude whether one causes the change in the other or vice versa.
  • Since correlational studies only measure co-variables, other potential confounding factors are not considered. The confounding variables may be a better explanatory factor for the study's outcome, making it difficult to determine the validity of the results.

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