Regression and correlation analysis
Regression and correlation analysis Regression analysis involves identifying the relationship between a dependent variable and one or more independent variables . A model of the relationship is hypothesized, and estimates of the parameter values are used to develop an estimated regression equation . Various tests are then employed to determine if the model is satisfactory. If the model is deemed satisfactory, the estimated regression equation can be used to predict the value of the dependent variable given values for the independent variables. Regression model In simple linear regression , the model used to describe the relationship between a single dependent variable y and a single independent variable x is y = β 0 + β 1 x + ε. β 0 and β 1 are referred to as the model parameters, and ε is a probabilistic error term that accounts for the variability in y that cannot be explained by the linear relationship with x . If the error term were not present, the model