In correlation analysis, we often use Pearson correlation to test the relationship between variables measured on a ratio/interval scale. Variables measured on a ratio/interval scale have a greater potential to meet the normality assumption for data testing.
Correlation analysis is the chosen method when conducting research to understand the relationship between variables. Correlation analysis in statistics can take the form of partial correlation analysis and multiple correlation analysis.
Correlation analysis is an associative test commonly used by many researchers to understand the relationship between variables. Before discussing how to interpret the results of correlation analysis, it is essential to understand the basic theory of correlation analysis.
Correlation analysis is one of the analytical techniques used to test the associative relationship between variables. In correlation analysis, testing can be conducted to answer whether the relationship between variables is significant and how strong and the sign of the relationship between the variables.
Many researchers choose to use correlation analysis to know the relationship between variables. The simpler analysis technique causes correlation analysis to be widely used by researchers.
