Bivariate statistical measures regression and correlation

Bivariate statistical measures regression and correlation

1. Correlation coefficient

   • It is a measure that indicates the strength and direction of the linear relationship between two variables.
   • The Pearson correlation coefficient is commonly used for continuous variables, while the Spearman correlation coefficient is used for variables that are not necessarily linear.

2. Coefficient of determination (R squared)

   • This measure indicates how much variation in the dependent variable is explained by the independent variable in a regression model.
   • Indicates the goodness of fit of the model.

3. Linear regression

   • It is a mathematical model that describes the relationship between two variables, a dependent variable and one or more independent variables.
   • It is used to predict the value of a dependent variable based on the value of the independent variable.

4. Slope (beta) analysis

   • In linear regression, the slope is the measure that represents how much the dependent variable changes when the independent variable increases by one unit.

5. Intercept (alpha) analysis

   • In linear regression, the intercept (also called a constant term) is the value of the dependent variable when the independent variable is equal to zero.