Topic 4 Flashcards
1
Q
What is the normality assumption? What is this model called?
A
It assumes the error terms are normally distributed. The model is knwon as the classical normal linear regression model.
2
Q
How justified is the normality assumption.
A
Not so bad when applied judicously. See central limit theorum
3
Q
What are the applications of the normality assumption?
A
Gives us the distributions of parameters, and some sweet properties
4
Q
What is the distribution of beta1 hat in terms of the variance?
A
5
Q
What is the distribution of beta2 hat in terms of the variance?
A
6
Q
What are the properties of the CNLRM?
A
- Unbiased
- Minimum variance
- Consistancy (estmates converge to parameters with increasing n) - beta1 hat normally distributed
- beta2 hat normally distributed
- (n-2) (sample-variance)/(population-variance) has a chi-square distribution
- beta1 & beta2 hat both distributed independantly of sample variance
- beta1 & beta2 hat have minimum variance in their the class of estimators, linear or not. Is BUE
7
Q
What is BUE?
A
Best unbiased estimator
