The “Statistics of the Coefficients Part” in Regression Table
We aim to test if the linear regression coefficients significantly impact Calorie Burnage, demonstrating a relationship between Average Pulse and Calorie Burnage using four key statistical components.
- std err: Standard Error
- t: The “t-value” of the coefficients
- P>|t|: The “P-value”
- [0.025 0.975]: The confidence interval of the coefficients
In this module, we will focus on understanding the “P-value.”
The P-value
The P-value determines if a relationship exists between Average Pulse and Calorie Burnage by testing if the coefficient’s true value is zero through hypothesis testing.
- A low P-value (< 0.05) suggests that the coefficient is likely not zero.
- A high P-value (> 0.05) means we cannot conclude that the explanatory variable affects the dependent variable (in this case, whether Average Pulse affects Calorie Burnage).
- A high P-value is also referred to as an insignificant P-value.
