Pearson’s correlation coefficient measures the linear relationship
Pearson’s correlation coefficient measures the linear relationship between two or more variables in statistical analysis. The test is concerned with the degree of the relationship between the two or more variables and the direction of the relationship. It does not show the dependent variable and the independent variable in the test, it purely deals with the strength of the relationship between variables under study. The Pearson’s correlation coefficient denoted (r) takes the values in the range of (-1<r<1) (Beck, 1995, p. 325). An evaluation conducted showed the linear relationship between employees’ ages and employee engagement scale score using the Pearson correlation coefficient r test to be -0.66. This indicates the relationship between the employees’ ages and their engagement scale are strongly correlated. The relationship between the two variables has a negative correlation meaning the slope of the curve/line has a negative gradient. This implies an increase in one variable leads to a decrease in the value of the other variable. The result of the test means that an Increase in the employee age results in a corresponding decrease in employee engagement scale score, or a decrease in employee age results in a corresponding increase in the employee engagement scale score.
