### 2. and independent variables. 2. Both the correlated

2. Getting a quantitative figure for correlation makes the decision making process, objective. 3. It helps in forecasting and planning because, changes in variables and its impact can be estimated beforehand.

4. It helps the researcher in identifying such factor which can stabilize the economy. 3. Precaution in Applying Correlation:1. It is difficult to distinguish between dependent variables and independent variables. 2. Both the correlated variables are affected by a third variable, which has not been taken into consideration by the researcher.

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3. The correlation may be due to chance. 4.

.Very high degree of correlation between two variables does not necessarily indicate a cause and effect relationship between them. 4. Types of Correlation:1. Single and Multiple Correlation: Only two variable are considered in single correlation, i.e.

1 one independent and another dependent variable. In case of multiple correlations, the relation between more than two variables is judged. 2. Partial and Total Correlation: In the case of partial correlation, relations of two or more variables are considered assuming other variables to be constant. Total correlation is based on all the variables without assuming any variable to be constant. 3.

Linear and Non-liner Correlation: When variation in the values of two variables has a constant ratio, there will be liner correlation between them. In non-liner correlation, the amount of change in one variable does not bear a constant ratio to the amount of change in the other related variable. 5. Methods of Determining Correlation:(a) Scatter diagram. (b) Karl Pearson’s coefficient of correlation. (c) Spearman’s Rank coefficient of correlation.