Question 1

For the command/read out: regress networth educ
With coeffiecient for education:  26272.81 
What does this tell us?

Accepted Answer

For every 1 unit change in education there is a 26272.81 change in networth

Answer

WHO CAN SAY?

Answer

For every 1 unit change in networth there is a 26272.81 unit change in education

Question 2

For the command/print out regress networth educ, the equation is:

Accepted Answer

E(Y) = Beta0 + Beta1educ

Answer

WHO KNOWS

Answer

E(Y) = Beta0 + Beta1networth

Question 3

For the command/ print out regress networth edu
_cons refers to the intercept and therefore:

Accepted Answer

Beta 0 -> if you have 0 units of education, you have cons_ units of networth

Answer

Beta 0 -> if you have 0 units of networth, you have cons_ units of education

Answer

Beta1

Question 4

For the command regress networth educ,
how would we determine what 10 units of education do to networth?

Accepted Answer

E(Y) = Beta0 + Coeff(units educ)

Answer

Ask politely

Answer

E(Y)=Coeff(units educ)

Question 5

For the command regress networth educ,
how do we determine the t score?

Accepted Answer

Estimate Beta1-0/SEbeta

Answer

Estimate Beta0-1/SEbeta1

Answer

Estimate cons_-0/SEbeta1

Question 6

In the command regress networth educ, what is the predictor?

Accepted Answer

Both

Answer

Educ

Answer

Continuous

Question 7

For linear regression with a categorical predictor, what command is needed?

Accepted Answer

tab {variable}, gen(new variable)

Answer

Sudo Make Me a Sandwich

Question 8

For command regress networth male1, what category now matters a little more?

Accepted Answer

cons_

Answer

Std Error

Question 9

For command regress networth male1, what is Beta0

Accepted Answer

Networth for males outside of category 1

Answer

Networth for all nonhumans

Answer

Networth for all non-males

Question 10

For command regress networth male1, what is the equation for the Confidence Interval?

Accepted Answer

Beta0 +|- t crit (determined from t score and df) x StdErrorBeta

Answer

BetaEstimate +|- t crit (determined from t score and df) x StdErrorBeta

Question 11

For the command regress networth race2 race3, what is the hypothesis test and is it predictive? Associative?

Accepted Answer

Predictive yes, Associative no.

Answer

Predictive no, Associative yes.

Question 12

For the command regress networth age educ male1 , what are we doing with all these extra variables?

Accepted Answer

Controlling for things like age and education.

Answer

Multi Tasking

Question 13

For the command E(Y) = Beta0 + Beta1(age) + Beta2(educ) +Beta3(race2) + Beta4 (race3)
What test would we want to use to examine race2 and race3 to each other?

Accepted Answer

F Test

Answer

T Test

Answer

Z Test

Question 14

For the command logit mony age, how would we measure change?

Accepted Answer

Both

Answer

log (p/1-p)

Answer

Beta0 + Beta1(age)

Question 15

For the command logit mony age, what does the coeff refer to?

Accepted Answer

every year of age is increased log odds of X of needing help to manage mony.

Answer

every year of age is increased at the rate of X of needing help to manage mony.

Question 16

For the command logit mony age, what do with do with the coeff?

Accepted Answer

Exponentiate

Answer

Divide

Answer

Subtract

Question 17

For the command logit mony age, what would we do to look at the difference of log odds for different years?

Accepted Answer

Both

Answer

Difference of age 51 vs age 50 = log (p51/1-p51) – log (p50/1-p50)

Answer

Log Odds Ratio = log (p51/1-p51) | (p50/1-p50) = exponentiate

Question 18

For the command logit money male1, what must be exponentiated and why?

Accepted Answer

Both

Answer

The Coeff

Answer

The CI because this is a categorical predictor

Question 19

For the command logit mony male1, if the exponentiate score is 1.12, what does this mean?

Accepted Answer

This is an odds ratio: the odds of needing help managing money are 1.12x’s higher if male than female.

Answer

Something Something Dark Side

Question 20

For the command logit mony male1,how do we calculate the Z score?

Accepted Answer

Coeff / Std Err

Answer

Coeff /z score

Answer

Std err / coeff

Question 21

When comparing how GRE, GPA, having an MS degree affect PHD program admission, what is the model?

Accepted Answer

Log (p/1-p) = funny symbol0 + funny symbol GPA + funny symbol GRE + funny symbol MS

Answer

Log (odds ratio ) = funny symbol0 + funny symbol GPA + funny symbol GRE + funny symbol MS

Question 22

When comparing how GRE, GPA, having an MS degree affect PHD program admission, what is the interpretation of the parameters?

Accepted Answer

Beta0 = mean for population with no MS degress, 0 GRE, 0 GPA

Answer

funny symbol 0 = log odds of PHD for GPA0, GRE0, MSdegree 0

Question 23

What does adjustment mean?

Accepted Answer

The coefficient of a predictor has the interpretation of holding all adjusting factors constant.

Answer

The coefficient of a dependent variable has the interpretation of holding all adjusting factors constant

Question 24

For looking at how how mpg and car size affect the price of a car (categorical), what is the model?

Accepted Answer

E (price|mpg, size) = Beta0 + Beta1 mpg + Beta2 size2 + Beta3 size 3

Answer

E (size2|size3, price = Beta0 + Beta1 mpg + Beta2 price + Beta3 size 1

Question 25

For looking at how how mpg and car size affect the price of a car (categorical), what are some interpretations for parameters of the model?

Accepted Answer

All of the Above

Answer

Beta3 = expected price difference in size 3 and size 1 adjusting for mpg

Answer

Beta2= expected price difference in size 2 and size 1 adjusting for mpg

Answer

Beta1=Effect of mpg, adjusting for size

Answer

Beta0 = Mean price for size 1 with 0 mpg

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