What does it mean if a linear regression model has a p-value less than 0.05 for

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Question: What does it mean if a linear regression model has a p-value less than 0.05 for a predictor variable?

Options:

Correct Answer: The predictor is statistically significant

Solution:

A p-value less than 0.05 indicates that the predictor variable is statistically significant in predicting the dependent variable.

What does it mean if a linear regression model has a p-value less than 0.05 for a predictor variable?

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.

Statistical Significance – A p-value less than 0.05 suggests that there is strong evidence against the null hypothesis, indicating that the predictor variable has a meaningful relationship with the dependent variable.
Linear Regression – A statistical method used to model the relationship between a dependent variable and one or more independent variables.