CORRELATION

Concept Of Correlation And Its Uses In Educational Research

Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel; a negative correlation indicates the extent to which one variable increases as the other decreases.

     There are three types of correlation: positive, negative, and none (no correlation). Positive Correlation: as one variable increases so does the other. Height and shoe size are an example; as one's height increases so does the shoe size. Negative Correlation: as one variable increases, the other decrease

While studying statistics, one comes across the concept of correlation. It is a statistical method which enables the researcher to find whether two variables are related and to what extent they are related. Correlation is considered as the sympathetic movement of two or more variables. We can observe this when a change in one particular variable is accompanied by changes in other variables as well, and this happens either in the same or opposite direction, then the resultant variables are said to be correlated. Considering a data where we find two or more variables getting valued then we might study the related variation for these variables.

Correlation Are Of Three Types:

• Positive Correlation
• Negative Correlation
• No correlation

In correlation, when values of one variable increase with the increase in another variable, it is supposed to be a positive correlation. On the other hand, if the values of one variable decrease with the decrease in another variable, then it would be a negative correlation. There might be the case when there is no change in a variable with any change in another variable. In this case, it is defined as no correlation between the two.

Positive Correlation

A relationship between two variables in which both variables move in same directions. A positive correlation exists when as one variable decreases, the other variable also decreases and vice versa. When the values of two variables x and y move in the same direction, the correlation is said to be positive. That is in positive correlation, when there is an increase in x, there will be and an increase in y also. Similarly when there is a decrease in x, there will be a decrease in y also.

Negative Correlation

In a negative correlation, as the values of one of the variables increase, the values of the second variable decrease or the value of one of the variables decreases, the value of the other variable increases. When the values of two variables x and y move in opposite direction, we say correlation is negative. That is in negative correlation, when there is an increase in x, there will be a decrease in y. Similarly when there is a decrease in x, there will be an increase in y increase.

Zero correlation

A zero correlation suggests that the correlation statistic did not indicate a relationship between the two variables. It's important to note that this does not mean that there is not a relationship at all; it simply means that there is not a linear relationship

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Figure 1. positive correlation

Figure 2. negativr correlation

   

 

Figure 3. zero/no correlation

Correlation analysis.

Methods of correlation and regression can be used in order to analyze the extent and the nature of relationships between different variables. Correlation analysis is used to understand the nature of relationships between two individual variables. For example, if we aim to study the impact of foreign direct investment (FDI) on the level of economic growth in Vietnam, then two variables can be specified as the amounts of FDI and GDP for the same period

Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However, in general, the presence of a correlation is not sufficient to infer the presence of a causal relationship 

Uses of Correlation In Educational Research

·         Only experimental data can be  conclusively demonstrate causal relations between variable .

·         In  experimental  research ,  we manipulate some variables and then measure the effects of this manipulation on other variables.

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