Question

When do we look at Adjusted R-squared rather than regular R-squared? What would you do if adding an independent variable decreased the Adjusted R-squared value?

Answer 1

ANSWER:

Adjusted r squared model is seen rather then regular r squared when the addition of an variable increases the regular r squared value significantly so as to determine whether the variable has added significantly to the model or is useless because adjusted r squared value only increases when the variable added has significantly improved the model . for example if there is 5 variable model we must find the regression analysis after each variable is added and only if the adjusted r squared value is increased then the addition of variable is deemed important otherwise it is useless and so adjusted r square is seen instead of regular r square in order to determine whether the variables added is significant to the model or not because r squared might show that it is important.

  if adding an independent variable decreased the Adjusted R-squared value then we will remove it from the model as adjusted r squared value should increase and not decrease when the independent variable is important to the model and so we discard it from the regression analysis.