Deck 5: Prediction, Goodness-Of-Fit and Modeling Issues

Question 1

You have estimated a regression model and your printout includes the following information s_xy= 3614.00
S_x = 12.72
S_y = 394.61
SST = 758912.00.
Use this information to calculate SSE.

A)546,416.64
B)212,495.36
C)381.89
D)5019.44

Answer 1

B

Question 2

You have estimated a regression model and your printout includes the following information s_xy= 3614.00
S_x = 12.72
S_y = 394.61
SST = 758912.00.
What is R² for this regression model?

A).72
B).11
C).03
D).53

Answer 2

A

Question 3

Which of the following expressions is NOT equal to Ʃ(y_i - y̅)² ?

A)Ʃ(ŷ_i-y̅)²+ Ʃe_i²
B)SSR + SSE
C)SSR/SSE
D)SST

Answer 3

C

Question 4

A measure of the symmetry of a distribution is ________________________.

Question 5

At what values of x₀ will the standard error of the forecast be smallest?

A)x₀ = 0
B)x₀ =x̅
C)x₀² = $\sigma$ ²
D)x₀ = t_c se(f)

Question 6

What hypothesis is tested when using the Jarque-Berra test ?

A)H₀: The model is correctly specified as estimated
B)H₀: The error terms are normally distributed
C)H₀: The error terms are uncorrelated with x
D)H₀: The error terms are random

Question 7

Which of the following leads to large forecast errors?

A)larger sample size,N
B)variation in the explanatory variable,x,is large
C)overall uncertainty in the model,as measured by $\sigma$ ²,is smaller
D)the value of (x₀ - x̄)² is larger

Question 8

While working with the sales manager of your firm you have estimated the following model of sales volume as a function of monthly household income: (0.781)(0.392) Where Q is monthly sales volume,I is monthly household income in thousands,and standard errors are listed below the parameter estimates.
What is the income elasticity of your firm's product?

A)1.212
B)2.206
C)3.418
D)4.630

Question 9

What about the distribution of a random variable does kurtosis measure?

Question 10

What does R2,the coefficient of determination,measure?

A)the probability of the true value falling within the forecast interval
B)the p-value on the coefficient we are using to test our hypothesis of interest
C)the confidence interval of the error terms as determined by the coefficients
D)the proportion of the variation in y explained by x within the regression model

Question 11

What is the skewness of the normal distribution?

Question 12

You have estimated the following simple regression model y = 379 + 1.44 x³
What is the elasticity when x = 8.49?

A)263.19
B)311.39
C)2.10
D)-24.7

Question 13

You have estimated a model of two variables related such that ln(y)= 17.3 - .04 x
If x decreases by 2 units,what is the expected change in y?

A)y decreases by .08 units.
B)y increases by 8 percent.
C)y increases by 4 units
D)y decreases by 8 percent.

Question 14

Which of the following will change if you scale the dependent variable in a simple regression model?

A)p-value
B)t-value of $\beta$ ₂
C)R²
D) $\beta$ ₁

Question 15

When should a researcher consider transforming the explanatory variable in the simple linear regression model?

A)to estimate a coefficient on the dependent variable that matches economic theory
B)to allow non-constant marginal effects
C)to reduce variance in the dependent variable
D)to reduce (Note: the "hat" should be over the whole expression,but I can't accomplish that in my software right now)

Question 16

If a scatter plot of the data reveals an inverted U shape,what data transformation would allow it to be estimated with simple linear regression?

Question 17

You have estimated the following simple regression model y = 379 + 1.44 x³
What does this model predict y to be when x = 8.49?

A)415.68
B)690.39
C)1260.22
D)2205.47

Question 18

While working with the sales manager of your firm you have estimated the following model of sales volume as a function of monthly household income: (0.781)(0.392) Where Q is monthly sales volume,I is monthly household income in thousands,and standard errors are listed below the parameter estimates.
What does the model predict sales volume to be if using the corrected predictor when income is $4000 per month?

A)708,133.68
B)723,146.11
C)163.73
D)167.20

Question 19

When should a researcher consider transforming the explanatory variable in a simple linear regression model?

A)when a data plot suggests there is a non-linear functional form
B)to get a coefficient estimate with the sign predicted by economic theory
C)to reduce the variation in the explanatory variable
D)to maximize SSR

Question 20

When the residuals from a simple regression model appear to be correlated with x,this is known as_______________________________.