Howtosignalprocessing
- How do you interpret regression results?
- What if p-value is greater than 0.05 in regression?
- How to interpret r2?
How do you interpret regression results?
Interpreting Linear Regression Coefficients
A positive coefficient indicates that as the value of the independent variable increases, the mean of the dependent variable also tends to increase. A negative coefficient suggests that as the independent variable increases, the dependent variable tends to decrease.
What if p-value is greater than 0.05 in regression?
The P-value
The statistical test for this is called Hypothesis testing. A low P-value (< 0.05) means that the coefficient is likely not to equal zero. A high P-value (> 0.05) means that we cannot conclude that the explanatory variable affects the dependent variable (here: if Average_Pulse affects Calorie_Burnage).
How to interpret r2?
The most common interpretation of r-squared is how well the regression model explains observed data. For example, an r-squared of 60% reveals that 60% of the variability observed in the target variable is explained by the regression model.
