Multiple Linear Regression and Wald Test (Part 2)

The Wald test, also known as the Wald Chi-Square test, is a statistical test used to assess the significance of individual coefficients in a regression model or to evaluate the overall fit of the model. It is commonly used in multiple linear regression, logistic regression, and other generalized linear models. The Wald test helps determine whether specific coefficients are different from hypothesized values ( i.e., 0) and whether they contribute significantly to explaining the variation in the dependent variable. Use: i) In linear regression, the Wald test can be used to assess whether individual predictors (independent variables) have a significant impact on the dependent variable. ii) In logistic regression, it can be used to test the significance of coefficients in binary classification models. iii) In generalized linear models, the Wald test helps assess the significance of parameters for various types of dependent variables, such as count data, categorical data, and more.