Correlation and Simple Linear Regression

Simple correlation and regression analysis are used to determine whether a relationship exists between two variables. Pearson’s correlation coefficient is used for measuring linear relationships and Spearman’s rank correlation coefficient for ranked relationships between two continuous variables. When estimating the linear relationship between a predictor and an outcome variable, a simple linear regression analysis is conducted. The purpose of this chapter is to answer these questions statistically: (1) Are two variables linear related? If so, what type of relationship exists? What is the strength of the relationship? (2) How to estimate the linear dependency relation between the predictor and response variable by the simple linear regression equation? SPSS software is used to measure the correlation coefficient and establish a simple linear regression model form the example.