COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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R-square will not change
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R-square will increase
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R-square will decrease
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There is not enough information to make conclusions about R-square
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Detailed explanation-1: -Adding more variables will increase R Squared whether or not the added variables have any statistically significant effect on the dependent variable. On the other hand, adjusted R Squared can increase or decrease.
Detailed explanation-2: -Problem 1: R-squared increases every time you add an independent variable to the model. The R-squared never decreases, not even when it’s just a chance correlation between variables.
Detailed explanation-3: -Every time if we add Xi (independent/predictor/explanatory) to a regression model, R2 increases even if the independent variable is insignificant for our regression model. R2 assumes that every independent variable in the model helps to explain variations in the dependent variable.
Detailed explanation-4: -Adding a group of regressors to the model will increase (decrease) RA2 depending on whether the F-statistic for testing that their coefficients are all zero is greater (less) than one in value. RA2 is unchanged if that F-statistic is exactly equal to one.