Briefly explain the concepts of Correlation in your own words

Types of Correlation are given below:

a. Positive of Negative

b. Simple, Partial and Multiple

c. Linear and Non-Linear



a. Positive Correlation: Both the variables (X and Y) will vary in the same direction. If variable X increases, variable Y also will increase; if variable X decreases, variable Y also will decrease.

Negative Correlation: The given variables will vary in opposite direction. If on variable increases, other variable will decrease.



b. Simple, Partial and Multiple Correlations: In simple correlation, relationship between two variables are studies. In partial and multiple correlations three or more variables are studies. Three or more variables are simultaneously studied in multiple correlation. In partial correlation more than two variables are studied, but the effect on one variable is kept constant and relationship between other two variables is studied.





c. Linear and Non-Linear Correlation: It depends upon the constance of the ration of change between the variables. In linear correlation the percentage change in one variable will be equal to the percentage change in another variable. It is not so in non-linear correlation.



Method of Studying Correlation::

The various methods of studying correlation are given below.



a. Scatter Diagram Method.

b. Graphic Method

c. Karl Pearson’s Coefficient of Correlation

d. Concurrent Deviation Method

e. Method of Least Squares

In probability theory and statistics, correlation, also called correlation coefficient, indicates the strength and direction of a linear relationship between two random variables. In general statistical usage, correlation or co-relation refers to the departure of two variables from independence. In this broad sense there are several coefficients, measuring the degree of correlation, adapted to the nature of data.

A number of different coefficients are used for different situations. The best known is the Pearson product-moment correlation coefficient, which is obtained by dividing the covariance of the two variables by the product of their standard deviations.