Econ 391 final exam questions with
complete solutions
the difference between the observed variable and the predicted value is called
a. sd
b. variance
c. error
d. laffers constants - correct answer ✔✔c. error
if we run a simple linear regression and find an R^2 = 0.12, we can conclude which of the
following
a. there is a relationship between X and Y
b. there is a strong relationship between X and Y
c. there is a non-linear relationship between X and Y
d. the variation in X explains 12 percent of the variation in Y - correct answer ✔✔d. the
variation in X explains 12 % of the variation in Y
in a regression analysis, if SSE = 200 and SSR = 300, the coefficient of determination is:
a. 0.60
b. 1.50
c. 0.66
d. 0.40 - correct answer ✔✔a. 0.60
in a regression analysis if R^2 =1 then
a. RSS =TSS
,b. RSS = 1
c. ESS = RSS
d. ESS = TSS - correct answer ✔✔a. RSS = TSS
the adjusted R^2 will fall if you add an additional independent variable (explanatory variable)
that is not statistically significant
a. true
b. false - correct answer ✔✔a. true
which of the following regarding the adjusted R^2 is false
a. can be used to determine whether or not an independent variable should be added to a
model or not
b. it is a measure of how much variation in the dependent variable is explained by the
independent variables
c. it is generally preferred to the R^2 because it takes into account whether the variables you
added to the regression equation are irrelevant or not
d. it shows the direction of the relationship between the 2 variables being compared - correct
answer ✔✔d. it shows the direction of the relationship between the 2 variables being
compared
R^2 says nothing about the relationship of the direction of variables being compared, it is a tool
to help compare which model better explains the variation in the data
below is the estimated regression equation of car price on milage. which is the correct
interpretation of the coefficient on mileage?
a. the price of a car decreases by 23,000 for every mile a car is driven
b. the price of a car decreases by 57 cents for every mile a car is driven
c. the prices of a car decrease by 57 cents for every additional mile that car is driven, on average
, d. on average driving a car another mile will increase the value of that car by 57 cents - correct
answer ✔✔c. the prices of a car decrease by 57 cents for every additional mile that car is
driven, on average
a regression model in which more than one independent variable is used to predict the
dependent variable is called
a. a simple linear regression model
b. a multiple regression model
c. an independent model
d. none of the answers is correct - correct answer ✔✔b. a multiple regression model
Regression analysis is a statistical procedure for developing a mathematical equation that
describes how
a. one independent and one or more dependent variables are related
b. several independent and several dependent variables are related
c. one dependent and one or more independent variables are related
d. none of the answers are correct - correct answer ✔✔c. one dependent and one ore more
independent variables are related
t - statistic - correct answer ✔✔coefficient divided by the standard error
for a t - test as the test statistic becomes farther from zero, the chance of rejecting the null
hypothesis
a. increases
b. decreases
c. doesn't change
d. increase or decreases depending on which test stat - correct answer ✔✔a. increases
complete solutions
the difference between the observed variable and the predicted value is called
a. sd
b. variance
c. error
d. laffers constants - correct answer ✔✔c. error
if we run a simple linear regression and find an R^2 = 0.12, we can conclude which of the
following
a. there is a relationship between X and Y
b. there is a strong relationship between X and Y
c. there is a non-linear relationship between X and Y
d. the variation in X explains 12 percent of the variation in Y - correct answer ✔✔d. the
variation in X explains 12 % of the variation in Y
in a regression analysis, if SSE = 200 and SSR = 300, the coefficient of determination is:
a. 0.60
b. 1.50
c. 0.66
d. 0.40 - correct answer ✔✔a. 0.60
in a regression analysis if R^2 =1 then
a. RSS =TSS
,b. RSS = 1
c. ESS = RSS
d. ESS = TSS - correct answer ✔✔a. RSS = TSS
the adjusted R^2 will fall if you add an additional independent variable (explanatory variable)
that is not statistically significant
a. true
b. false - correct answer ✔✔a. true
which of the following regarding the adjusted R^2 is false
a. can be used to determine whether or not an independent variable should be added to a
model or not
b. it is a measure of how much variation in the dependent variable is explained by the
independent variables
c. it is generally preferred to the R^2 because it takes into account whether the variables you
added to the regression equation are irrelevant or not
d. it shows the direction of the relationship between the 2 variables being compared - correct
answer ✔✔d. it shows the direction of the relationship between the 2 variables being
compared
R^2 says nothing about the relationship of the direction of variables being compared, it is a tool
to help compare which model better explains the variation in the data
below is the estimated regression equation of car price on milage. which is the correct
interpretation of the coefficient on mileage?
a. the price of a car decreases by 23,000 for every mile a car is driven
b. the price of a car decreases by 57 cents for every mile a car is driven
c. the prices of a car decrease by 57 cents for every additional mile that car is driven, on average
, d. on average driving a car another mile will increase the value of that car by 57 cents - correct
answer ✔✔c. the prices of a car decrease by 57 cents for every additional mile that car is
driven, on average
a regression model in which more than one independent variable is used to predict the
dependent variable is called
a. a simple linear regression model
b. a multiple regression model
c. an independent model
d. none of the answers is correct - correct answer ✔✔b. a multiple regression model
Regression analysis is a statistical procedure for developing a mathematical equation that
describes how
a. one independent and one or more dependent variables are related
b. several independent and several dependent variables are related
c. one dependent and one or more independent variables are related
d. none of the answers are correct - correct answer ✔✔c. one dependent and one ore more
independent variables are related
t - statistic - correct answer ✔✔coefficient divided by the standard error
for a t - test as the test statistic becomes farther from zero, the chance of rejecting the null
hypothesis
a. increases
b. decreases
c. doesn't change
d. increase or decreases depending on which test stat - correct answer ✔✔a. increases
