What does it mean if a linear regression model has a p-value less than 0.05 for
Practice Questions
Q1
What does it mean if a linear regression model has a p-value less than 0.05 for a predictor variable?
The predictor is not statistically significant
The predictor is statistically significant
The model is overfitting
The model has high bias
Questions & Step-by-Step Solutions
What does it mean if a linear regression model has a p-value less than 0.05 for a predictor variable?
Step 1: Understand what a p-value is. A p-value helps us determine if the results we see are due to chance or if they are meaningful.
Step 2: Know the common threshold for significance. A p-value less than 0.05 is often used as a cutoff to indicate that results are statistically significant.
Step 3: Recognize what a predictor variable is. In a linear regression model, a predictor variable is an independent variable that we think might influence the dependent variable.
Step 4: Interpret the p-value for the predictor variable. If the p-value is less than 0.05, it suggests that there is strong evidence that this predictor variable has a real effect on the dependent variable.
Step 5: Conclude that a p-value less than 0.05 means the predictor variable is important for making predictions about the dependent variable.
