4 - Linear Regression Flashcards
1
Q
Assumptions the model makes
A
- There exists some linear relationship between Y & X
- 3.
4.
2
Q
What is used to find the “best” line
A
Residual Sum of Squares (RSS)
3
Q
What does the RSE do?
A
serves as a measure of the amount of training error in the model
4
Q
What is r^2?
A
The coefficient of determination. Is it the proportion of the total variation that is explained by the regression line
It is a measure of how close to the fitted line is to the observed data
5
Q
What what the Correlation Coefficient (r) tell us?
A
tells us if there is a negative or positive linear relationship between X and Y(and measures the strength of that relationship)
- its a value between -1 and 1
