R Squared And Violations Of Clrm

Question 1

R squared

Answer 1

Goodness of fit- how well the regression fits the data points

Question 2

Adjusted r squared

Answer 2

Takes info accounting a higher r squared if more variables have been added
So adjusted r squared falls if more variables are added

Question 3

Violation- errors have mean zero

Answer 3

Only true if there’s a constant teen in regression so it’s fits data better

Question 4

Violation- variance in errors is constant

Answer 4

Homescadacity isn’t true if there’s patterns in the errors

Question 5

Test for heteroscedacity

Answer 5

Whites test- checks for a pattern between errors

Question 6

Violation- errors normally distributed

Answer 6

Test coefficient skewness- berd jarque

To see if curve is skewed

Question 7

Violation- correlation between errors

Answer 7

Multicolinerity
E.g if x3= 2x2

R squared will be high
Solution- collect more data
Don’t remove important variables- bias

Question 8

Violation- no pattern between errors

Answer 8

Test for autocorrelation Detect- durbin Watson test- assumes errors are autocorrelated
Patterns in residuals could be positive - curve or negative- straight jumps through x