Term 1 Flashcards Preview

EDA > Term 1 > Flashcards

Flashcards in Term 1 Deck (56)
Loading flashcards...
1

What are the implications of a statistical relationship?

A causes B
B causes A
A 3rd variable causes both
Random occurrence

2

What does the stochastic error include?

Other explanatory variables (X1, X2..) that are missing
Measurement error
Incorrect functional form
Random and unpredictable occurrences

3

What does a hat above a variable indicate?

It must be estimated

4

How do you calculate the residual and error term

e=Y-YHat
E=Y-E(Y|X)

5

How do you illustrate the residual and error term?

Difference between sample line and point is residual
Difference between point and true line is error

6

How do you estimate a value of B1 using OLS?

Sum(X-XBar)(Y-YBAR)/SUM(X-XBAR)^2

7

How do you estimate a value of B0 using OLS?

YBar-B1X

8

How do you calculate TSS?

Sum(Y-YBar)^2
TSS=ESS+RSS

9

How do you calculate ESS/?

Sum(Yhat-Ybar)^2

10

How do you calculate RSS/

Sum(e^2)

11

How do you calculate R^2?

ESS/TSS
OR
1-RSS/TSS

12

What is the DOF?

The number of observations (N) - Number of coefficients (K)

N-K
N-K-1 for intercept

13

How do you calculate Adjusted R^2

(RSS/N-K-1)/(TSS/N-1)

14

How can you calculate the correlation coefficient r?

Root R^2

15

What are the steps of applied regression?

0.5 Choose the dependant variable
1. Review the literature and develop a theoretical model
2. Specify the model - expected signs
3. Hypothesise the expected signs and coefficents
4. Collect Data, Inspect and Clean
5. Estimate, evaluate and analyse the equation
6. Document the Results

16

What is the sampling distribution of Bhat?

The variety of Bhat you get from different samples

17

How can the mean reveal bias?

An estimated BHat should have an expected value of B
E(βHat)=β

18

What are the classical assumptions of OLS? (1-4)

The regression model is linear, is correctly specified, and has an additive error term

The error term has a zero population mean

All explanatory variables are uncorrelated with the error term

Observations of the error term are uncorrelated with each other (no serial correlation)

19

What are the classical assumptions of OLS? (5-7)

The error term has a constant variance (no heteroskedasticity)

No explanatory variable is a perfect linear function of any other explanatory variable(s) (no perfect multicollinearity)

The error term is normally distributed (this assumption is optional but usually is invoked)

20

If the classical assumptions are met., what can be said?

OLS will provide the Best Linear Unbiased Linear Estimator (BLUE)

21

What is the formula for the T-Test?

T=(Bk-BH0)/SE(BK)
Bk is the coefficient
Bho is the null, usually 0

22

How do you calculate the variance of an estimation?

=Sum(e^2)/N-2

23

How do you calculate the variance and SE of a coefficent?

VAR(B)=VAR/SUm(X-Xbar)^2
Root for SE

24

How do you calculate a confidence interval?

B +- Tc*SE(B)

25

What are the limitations of the T-Test?

Does not consider theoretical validity
Does not test importance

26

What are the three potential specificaiton errors?

Independent variables
Functional Form
Form of the stochastic error term

27

What is the effect of omitting a revlevant variable?

It cannot be held constant therefore biases other coefficents

Violates CA-3
Correlates with error term

28

What is the effect of an irrelevant variable?

Does not cause bias
Will increase variance and hence t-scores
Will reduce adjusted R^2

29

What is the four criteria to test whether a variable belongs?

Theory: Is the variables place theoretically sound
t-Test: Is the variables estimated coefficient significant in the expected direction
Adjusted R^2: Does the overall fit of the equation improve when the variable is added
Bias: Do other variables coefficients change significantly when the variable is added

30

What is the equation for the F-Test?

F=(RSSm-RSS)/M
/ (RSS/N-
k-1)
M = Number of constraints