Correlation Analysis

Abbreviation:  

Correlation analysis is an analysis to see the statistical relationship between two variables. This analysis can be done in statistical tools such as SPSS as well as in Excel. For example, when you analyze the duration of the call, and the satisfaction scores given by the customers after the call, the relationship between the two variables can be analyzed. The positive correlation shows that both variables increase or decrease in the same direction (When the satisfaction of the [[customer representative]] increases, the [[customer satisfaction score]] increases as well) and the negative correlation indicates that when a variable varies the other variable varies in the opposite direction (the decrease in the customer satisfaction score while the [[call time]] increases).

The correlation coefficient should be higher than 0.5 in order for the variables to be related. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally described as weak. Although the correlation shows the relationship between the variables, it does not explain the causality. [[Regression analysis]] should be done for causality analysis.

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