Lecture 1

Question 1

What are not so large data sets?

Answer 1

The number of observations n exceeds the number of regressors d.

Question 2

What is the general idea of all regression models? (Name 2)

Answer 2

Question 3

Answer 3

Question 4

Answer 4

Question 5

Answer 5

Question 6

What is the difference between a fixed design and a random design model?

Answer 6

Question 7

What is the second criterion to categorize linear models (based on the error terms)?

Answer 7

Question 8

What are the two possible ways of writing down a classical non-random linear model? What is the difference between the two?

Answer 8

Question 9

How can the classical model be estimated with ML?

Answer 9

Question 10

What is the fixed design normal error terms theorem?

Answer 10

Question 11

How is the following model different from the classical model?

Answer 11

Question 12

Answer 12

Question 13

What is the fixed design non-normal errors theorem? When does it hold?

Answer 13

Question 14

Answer 14

Question 15

What is the random design non-normal errors theorem?

Answer 15

Question 16

Please explain the t-test. How is the t-statistic computed? Which distribution does the null-hypothesis have?

Answer 16