I am studying leadership style's impact on job satisfaction. in the data collection instrument, there are 13 questions on leadership style divided into a couple of leadership styles. on the other hand, there are only four questions for job satisfaction. how do i run correlational tests on these variables? What values do i select to analyze in Excel?
- For Independent Variable you can go for Correlation Analysis and for Dependent Variable Regression analysis can be applied.
- Use the CORREL function in Excel to compute the correlation coefficient between the two variables. This will measure the strength and direction of the linear relationship between them. A correlation coefficient close to +1 or -1 indicates a strong linear relationship, while a value close to 0 indicates a weak relationship.
Arpita Grover thank you for the response. but my question is, what do i choose to run the correlation test on? i have several responses for the independent (leadership style) variable, and several for the dependent (job satisfaction) variable. it's not one value like age, or height etc.
First, you need to do the correlation between your target variable and each of your potential independent variables. After checking what independent variables are the more correlated to your target variable (as mentioned earlier coefficient correlation closest to - 1 or + 1). Once, you decide according to these correlation coefficients which variables you can select for your model, you need to ensure that there will be no multicollinearity in your model. To ensure that, for each independent variable you do correlation tests again. If two independent variables are too correlated, you should introduce only one in your model (e.g. the variable which had the higher correlation rate with your dependent variable).
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