Week 1

Question 1

What are the different data types?

Question 2

Give examples of the 3 different data types?

Question 3

What is the linear regression model

Question 4

What is the population regression line?

Question 5

What is the error term?

Question 6

What is the interpretation of the beta1?

Question 7

What is the interpretation of beta0?

Question 8

What is the interpretation of the error term?

Question 9

Why do you need OLS?

Question 10

What is OLS? And what is the formula?

Answer 10

df

Question 11

What is the goal of OLS?

Question 12

MATH: derive the OLS estimator?

Question 13

MATH: show that the b1 estimator is equal to r_xy * (s_y / s_x)

Question 14

What is the sample covariance?

Question 15

What is the sample variance?

Question 16

What is the sample correlation coefficient?

Question 17

MATH: derive the estimators of the regression through the origin?

Question 18

What is extrapolation?

Question 19

What is TSS?

Question 20

What is SSR?

Question 21

What is ESS?

Question 22

What is the formula for R^2?

Question 23

What is the interpretation of R^2?

Question 24

What does R^2=0 and =1 mean?

Question 25

Why do we have Y^(-^) = Y^(-)

Question 26

MATH: show that R^2=r_xy ^(2)

Question 27

What is the implication of R^2=r_xy ^(2)?

Question 28

What is the reason for this implication: R^2=r_xy ^(2)

Question 29

MATH: derive the R^2 in regression through the origin?`

Question 30

What is the SER?

Question 31

When is SER optimal?

Answer 31

The smaller and further it lies from the standdsrd deviation s_y

Question 32

What is the formula of the SER?

Question 33

What is the difference between the SER and the R^2?

Question 34

What do the first order conditions imply?