The "Coefficients Part" in Regression Table
- Coef is short for coefficient. It is the output of the linear regression function.
The linear regression function can be rewritten mathematically as:
Calorie_Burnage = 0.3296 * Average_Pulse + 346.8662
These numbers means:
- If Average_Pulse increases by 1, Calorie_Burnage increases by 0.3296 (or 0,3 rounded)
- If Average_Pulse = 0, the Calorie_Burnage is equal to 346.8662 (or 346.9 rounded).
- Remember that the intercept is used to adjust the model's precision of predicting!
Do you think that this is a good model?
Define the Linear Regression Function in Python
Define the linear regression function in Python to perform predictions.
What is Calorie_Burnage if Average_Pulse is: 120, 130, 150, 180?
Example
def Predict_Calorie_Burnage(Average_Pulse):
return(0.3296*Average_Pulse +
346.8662)
print(Predict_Calorie_Burnage(120))
print(Predict_Calorie_Burnage(130))
print(Predict_Calorie_Burnage(150))
print(Predict_Calorie_Burnage(180))
