CORRELATIONAL RESEARCH DESIGN

• Hesti Aprilia S. (20181111044)

• Astri Dewi F. (20181111046)

• Watcharakorn Mahamad (20181111069)

WHAT IS CORRELATIONAL RESEARCH?

Correlational designs provide an opportunity for you to predict scores and explain the relationship among variables. In correlational research designs, investigators use the cor- relation statistical test to describe and measure the degree of association (or relationship) between two or more variables or sets of scores. In this design, the researchers do not attempt to control or manipulate the variables as in an experiment; instead, they relate, using the correlation statistic, two or more scores for each person (e.g., a student motivation and a student achievement score for each individual).

WHY WE HAVE TO USE CORRELATION RESEARCH?

Correlational research enables researchers to establish the statistical pattern between 2 seemingly interconnected variables; as such, it is the starting point of any type of research. It allows you to link 2 variables by observing their behaviors in the most natural state.

WHAT ARE THE TYPES OF CORRELATIONAL DESIGNS?

Essentially, there are 3 types of correlational research which are positive correlational research, negative correlational research, and no correlational research. Each of these types is defined by peculiar characteristics.

1. Positive Correlational Research

Positive correlational research is a research method involving 2 variables that are statistically corresponding where an increase or decrease in 1 variable creates a like change in the other. An example is when an increase in workers' remuneration results in an increase in the prices of goods and services and vice versa.

2. Negative Correlational Research

Negative correlational research is a research method involving 2 variables that are statistically opposite where an increase in one of the variables creates an alternate effect or decrease in the other variable. An example of a negative correlation is if the rise in goods and services causes a decrease in demand and vice versa.

3. Zero Correlational Research

Zero correlational research is a type of correlational research that involves 2 variables that are not necessarily statistically connected. In this case, a change in one of the variables may not trigger a corresponding or alternate change in the other variable.

THE STEPS IN CONDUCTING A CORRELATIONAL STUDY :

Step 1. Determine If a Correlational Study Best Addresses the Research Problem

A correlational study is used when a need exists to study a problem requiring the identification of the direction and degree of association between two sets of scores. It is useful for identifying the type of association, explaining complex relationships of multiple factors that explain an outcome, and predicting an outcome from one or more predictors. Sample questions in a correlational study might be:

◆ Is creativity related to IQ test scores for elementary children? (associating two variables)

◆ What factors explain a student teacher’s ethical behavior during the student-teaching experience? (exploring a complex relationship)

◆ Does high school class rank predict a college student’s grade point average in the first semester of college? (prediction)

Step 2. Identify Individuals to Study

Ideally, you should randomly select the individuals to generalize results to the population, and seek permissions to collect the data from responsible authorities and from the institutional review board. The group needs to be of adequate size for use of the correlational statistic, such as N = 30; larger sizes contribute to less error variance and better claims of representativeness. For instance, a researcher might study 100 high school athletes to correlate the extent of their participation in different sports and their use of tobacco. A narrow range of scores from a population may influence the strength of the correlation relationships.

Step 3. Identify Two or More Measures for Each Individual in the Study

Because the basic idea of correlational research is to compare participants in this single group on two or more characteristics, measures of variables in the research question need to be identified (e.g., literature search of past studies), and instruments that measure the variables need to be obtained. Ideally, these instruments should have proven validity and reliability. You can obtain permissions from publishers or authors to use the instruments. Typically one variable is measured on each instrument, but a single instrument might contain both variables being correlated in the study.

Step 4. Collect Data and Monitor Potential Threats

The next step is to administer the instruments and collect at least two sets of data from each individual. The actual research design is quite simple as a visual presentation. Two data scores are collected for each individual until you obtain scores from each person in the study.

Step 5. Analyze the Data and Represent the Results

The objective in correlational research is to describe the degree of association between two or more variables. The investigator looks for a pattern of responses and uses statistical procedures to determine the strength of the relationship as well as its direction. A statistically significant relationship, if found, does not imply causation (cause and effect) but merely an association between the variables. More rigorous procedures, such as those used in experiments, can provide better control than those used in a correlational study.

The analysis begins with coding the data and transferring it from the instruments into a computer file. Then the researcher needs to determine the appropriate statistic to use. An initial question is whether the data are linearly or curvilinearly related. A scatterplot of the scores (if a bivariate study) can help determine this question.

Step 6. Interpret the Results

The final step in conducting a correlational study is interpreting the meaning of the results. This requires discussing the magnitude and the direction of the results in a correlational study, considering the impact of intervening variables in a partial correlation study, interpreting the regression weights of variables in a regression analysis, and developing a predictive equation for use in a prediction study.

In all of these steps, an overall concern is whether your data support the theory, the hypotheses, or questions. Further, the researcher considers whether the results confirm or disconfirm findings from other studies. Also, a reflection is made about whether some of the threats discussed above may have contributed to erroneous coefficients and the steps that might be taken by future researchers to address these concerns

WHAT ARE THE DATA COLLECTION METHODS IN CORRELATIONAL RESEARCH?

Data collection methods in correlational research are the research methodologies adopted by persons carrying out correlational research in order to determine the linear statistical relationship between 2 variables. These data collection methods are used to gather information in correlational research.

The 3 methods of data collection in correlational research are naturalistic observation method, archival data method, and the survey method. All of these would be clearly explained in the subsequent paragraphs.

1. Naturalistic Observation

Naturalistic observation is a correlational research methodology that involves observing people's behaviors as shown in the natural environment where they exist, over a period of time. It is a type of research-field method that involves the researcher paying closing attention to natural behavior patterns of the subjects under consideration.

This method is extremely demanding as the researcher must take extra care to ensure that the subjects do not suspect that they are being observed else they deviate from their natural behavior patterns. It is best for all subjects under observation to remain anonymous in order to avoid a breach of privacy.

The major advantages of the naturalistic observation method are that it allows the researcher to fully observe the subjects (variables) in their natural state. However, it is a very expensive and time-consuming process plus the subjects can become aware of this act at any time and may act contrary.

2. Archival Data

Archival data is a type of correlational research method that involves making use of already gathered information about the variables in correlational research. Since this method involves using data that is already gathered and analyzed, it is usually straight to the point.

For this method of correlational research, the research makes use of earlier studies conducted by other researchers or the historical records of the variables being analyzed. This method helps a researcher to track already determined statistical patterns of the variables or subjects.

This method is less expensive, saves time and provides the researcher with more disposable data to work with. However, it has the problem of data accuracy as important information may be missing from previous research since the researcher has no control over the data collection process.

3. Survey Method

The survey method is the most common method of correlational research; especially in fields like psychology. It involves random sampling of the variables or the subjects in the research in which the participants fill a questionnaire centered on the subjects of interest.

This method is very flexible as researchers can gather large amounts of data in very little time. However, it is subject to survey response bias and can also be affected by biased survey questions or under-representation of survey respondents or participants.

These would be properly explained under data collection methods in correlational research.

WHAT ARE THE ADVANTAGES OF CORRELATIONAL RESEARCH?

In cases where carrying out experimental research is unethical, correlational research can be used to determine the relationship between 2 variables. For example, when studying humans, carrying out an experiment can be seen as unsafe or unethical; hence, choosing correlational research would be the best option.

Through correlational research, you can easily determine the statistical relationship between 2 variables.

Carrying out correlational research is less time-consuming and less expensive than experimental research. This becomes a strong advantage when working with a minimum of researchers and funding or when keeping the number of variables in a study very low.

Correlational research allows the researcher to carry out shallow data gathering using different methods such as a short survey. A short survey does not require the researcher to personally administer it so this allows the researcher to work with a few people.

WHAT ARE THE DISADVANTAGES OF CORRELATIONAL RESEARCH?

Correlational research is limiting in nature as it can only be used to determine the statistical relationship between 2 variables. It cannot be used to establish a relationship between more than 2 variables.

It does not account for cause and effect between 2 variables as it doesn't highlight which of the 2 variables is responsible for the statistical pattern that is observed. For example, finding that education correlates positively with vegetarianism doesn't explain whether being educated leads to becoming a vegetarian or whether vegetarianism leads to more education.

Reasons for either can be assumed, but until more research is done, causation can't be determined. Also, a third, unknown variable might be causing both. For instance, living in the state of Detroit can lead to both education and vegetarianism.

Correlational research depends on past statistical patterns to determine the relationship between variables. As such, its data cannot be fully depended on for further research.

In correlational research, the researcher has no control over the variables. Unlike experimental research, correlational research only allows the researcher to observe the variables for connecting statistical patterns without introducing a catalyst.

The information received from correlational research is limited. Correlational research only shows the relationship between variables and does not equate to causation.

CONCLUSION:

Findings from correlational research can be used to determine prevalence and relationships among variables, and to forecast events from current data and knowledge. In spite of its many uses, prudence is required when using the methodology and analyzing data.

REFERENCES :

Creswell, J. W. (2012). Educational research Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Boston, MA Pearson

https://psychcentral.com/blog/the-importance-of-correlational-studies#1

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