Question

True or False? In-sample r-squared is generally a more important measure of a regression model’s predictive power than out of sample r-squared

True or False? If the p-value for an IV is larger than acceptable error (usually .05), it suggests that there is no significant relationship between that IV and the DV.

True or False? If the p-value for an IV is larger than acceptable error (usually .05), it is irrelevant what the sign of the beta for that IV is because p-value suggests that there is no significant relationship between that IV and the DV.

True or False? From a practical point of view, the more IVs we can include in the regression model the better, since that may increase r-squared. Hint: who is gathering data on those IVs?

Answer 1

1. The regression models' predictive accuracy is determined by the in sample r-squared value. Hence, the given statement is True.

2. If the p-value of IV is larger than acceptable error, then we fail to reject null hypothesis and conclude that the variable is not significant. Hence, the given statement is True.

3. Based on p-value, the null hypothesis is not rejected and there ie no significant relationship between the IV and DV. Hence, the statement is True.

4. More Independent variables in to the model will increase the r-square value. But at the same time it will decrease the adjusted r-square. Adjusted r-spuare provides a penalty for increasing the number of IVs. Hence, the given statement is False.