CORRELATIONAL STUDIES

Correlational Studies

A correlational study determines whether or not two variables are correlated. This means to study whether an increase or decrease in one variable corresponds to an increase or decrease in the other variable (“Difference Between Correlation and Regression (with Comparison Chart)—Key Differences,” n.d.).

Figure1. Correlation in class

Types of Co-relation.

There are three types of correlations that are identified.  Mainly there are three type of co-relation.

Positive correlation. Positive correlation between two variables is when an increase in one variable leads to an increase in the other and a decrease in one leads to a decrease in the other. For example, the amount of money that a person possesses might correlate positively with the number of cars he owns(Hayes, n.d.).

Negative correlation.  Negative correlation is when an increase in one variable leads to a decrease in another and vice versa. For example, the level of education might correlate negatively with crime. This means if by some way the education level is improved in a country, it can lead to lower crime. Note that this doesn't mean that a lack of education causes crime. It could be, for example, that both lack of education and crime have a common reason: poverty.

No correlation.  Two variables are uncorrelated when a change in one doesn't lead to a change in the other and vice versa. For example, among millionaires, happiness is found to be uncorrelated to money. This means an increase in money doesn't lead to happiness.

A correlation coefficient is usually used during a correlational study. It varies between +1 and -1. A value close to +1 indicates a strong positive correlation while a value close to -1 indicates strong negative correlation. A value near zero shows that the variables are uncorrelated(“A Correlational Study Tries to Find a Relationship Between Variables,” n.d.).

Limitations

It is very important to remember that correlation doesn't imply causation and there is no way to determine or prove causation from a correlational study. This is a common mistake made by people in almost all spheres of life.

 correlation comic.  For example, a US politician speaking out against free lunches to poor kids at school argues -“You show me the school that has the highest free and reduced lunch, and I'll show you the worst test scores, folks” (nymag.com). This is a correlation he is speaking about one cannot imply causation. The obvious explanation for this is a common cause of poverty: people who are too poor to feed their children will not have the best test scores.

Correlation Tables

The correlation table is normally presented using the lower triangle. The first example is a table that does not have to be divided because all variables fit in the table set in landscape format. The second table adds two variables to illustrate what to do when there are more variables than can fit across the page. These examples include descriptive names of the variables in the first column. If abbreviations for variable names are used, it is necessary to define these terms in specific table notes. Correlation tables should include control, predictor, and outcome variables when relevant. It is also important to reporting Ms and SDs. Doing so in correlation tables rather than in a separate descriptive table could save precious journal space. In the first example, the range of each variable is included and the alpha is included for those variables that have one. This information may not be necessary if it is provided elsewhere such as in a sample description table.

 Table 1

Comparison between positive correlations

positive correlation	negetive correlation	No correlation
One variable increases other Variable also increases.	One variable increases other variable decreases.	No dependence between variables.
Money increases living style becomes good.	Eg.  Tension increases marks decreases.	Eg. Colour of skin and marks awarded.
Positively increasing graph	Positively decreasing graph	No shape

REFERENCE

A Correlational Study Tries to Find a Relationship Between Variables. (n.d.). Retrieved August 21, 2019, from https://explorable.com/correlational-study

Difference Between Correlation and Regression (with Comparison Chart)—Key Differences. (n.d.). Retrieved August 21, 2019, from https://keydifferences.com/difference-between-correlation-and-regression.html

Hayes, A. (n.d.). Understanding Positive Correlation. Retrieved August 21, 2019, from Investopedia website: https://www.investopedia.com/terms/p/positive-correlation.asp
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Correlational studies from AiswaryaRaveendran

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