Econ 391

For a t-test or an F-test, as the test statistic becomes farther from zero, the chance of rejecting the null hypothesis... a. Increases b. Decreases c. Does not Change d. Increases or Decreases depending on which test statistic

A

A student receives a test score of 70%. The teacher announces to the class that each student will have their test score increased by 3%. How many percentage points will this increase the student's test? a. 2.1 b. 73 c. 6.3 d. 73.6

A

If we change a 95% confidence interval estimate to a 99% confidence interval estimate, we can expect the _____. a. width of the confidence interval to increase b. width of the confidence interval to decrease c. width of the confidence interval to remain the same d. sample size to increase

A

In a regression analysis, if R2 = 1, then ___________ a. RSS = TSS b. RSS = 1 c. ESS = RSS d. ESS = TSS

A

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

A

In a simple linear regression, if we can reject the null hypothesis of an F-test, we can also be certain that our only independent variable is statistically significant. a. True b. False

A

Increasing the confidence level will increase the width of a confidence interval, all else constant. a. True b. False

A

Taking a sample of Lexington residents will likely result in biased estimates compared to the entire population of Kentucky. a. True b. False

A

The Adjusted R2 will fall if you add an additional independent variable (explanatory variable) that is not statistically significant. a. True b. False

A

The F-statistic from a regression output is used to test the significance of the entire model. a. True b. False

A

The assumed null hypothesis for regression coefficients is that H0: b = 0 (is not statistically significant. Therefore HA: 𝛽 does not equal 0 (is statistically significant) a. True b. False

A

When the level of confidence decreases, the margin of error: a. Becomes smaller. b. Stays the same. c. Becomes larger. d. Becomes smaller or larger, depending on the sample size.

A

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.

B

Adding an independent variable, which has no predictive power, to a regression model will usually lower the value of R2 . a. True b. False

B

An assumption of the classic regression model is that there is no Multicollinearity. a. True b. False

B

As the sample size increases, the margin of error _____. a. increases b. decreases c. stays the same d. None of the answers is correct.

B

Based on the regression output, which form of advertising is more effective? a. TV b. Internet c. They are equally effective d. Not enough information

B

Data on income in America tends to have a very long right-tail. Knowing this, which value will be larger, median household income or mean household income? a. Median Household Income b. Mean Household Income c. They will be equal d. It will depend on how far out the right-tail goes

B

For data with a heteroskedasticity problem, the estimated parameter coefficients will be wrong if we do not correct for the heteroskedasticity. a. True b. False

B

For 𝛼 = 0.05, we will reject the null hypothesis for a p-value that is 0.08. a. True b. False

B

If SSE = 300 and SST = 625, compute R2 . a. 0.48 b. 0.52 c. 0.68 d. 0.32

B

If SSE = 300 and SST = 625, compute SSR. a. -325 b. 325 c. 925 d. 625

B

If we dropped every independent variable except one, what would we expect to happen to the value of R2 ? a. Increase b. Decrease c. Not Change d. Not enough information

B

In a multivariable regression, if we know that one of the coefficients is statistically significant, what can we say about the conclusion of an F-test? a. We cannot make any conclusions without know more information. b. We will reject the null hypothesis because at least one variable is statistically different from zero. c. We will fail to reject the null hypothesis because at least one variable is statistically different than zero. d. We can conclude that the model as a whole does not predict our dependent variable.

B

Math scores on the SAT are normally distributed with mean at 500 points and a standard deviation of 100 points. If 1000 students take the SAT how many would be expected to have a math score above 700 points? a. 125 b. 23 c. 50 d. 47

B

On a standard normal curve, the area to the right of what Z-score is 95%? a. 1.645 b. -1.645 c. 1.96 d. -1.96

B

Suppose you want to test the hypothesis at the 99% level that average height is less than 70 inches. What will your conclusion be and why? a. Fail to reject - 70 inches is outside of the confidence interval. b. Fail to reject - 70 inches is inside of the confidence interval. c. Reject - 70 inches is outside of the confidence interval. d. Reject - 70 inches is inside of the confidence interval.

B

The normal distribution is always symmetric and centered around zero. a. True b. False

B

The sample variance can be positive or negative. a. True b. False

B

Which is a way to increase the value of R2 . a. Drop a variable from the model which is not particularly useful in predicting the dependent variable. b. Add an independent variable to the model which is useful for predicting the dependent variable. c. Correct for heteroskedasticity. d. Reduce Multicollinearity by dropping an independent variable.

B

Which of the following will increase the width of a confidence interval? a. Increasing the sample size b. Increasing the level of confidence c. Decreasing the level of confidence d. None of the above

B

Below is the estimated regression equation of car price on mileage. Which is the correct interpretation of the coefficient on mileage? Price = 23,000 - 0.57Mileage 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 price of a car decreases 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.

C

Find the margin of error for the confidence interval. a. 1.2 inches b. 2.9 inches c. 1.45 inches d. Not Enough Information to answer this question.

C

For some uniform distribution, there is a 40% probability of drawing an observation between 0 and 3. Assuming the distribution begins at 0, where does the distribution end? a. 10 b. 8 c. 7.5 d. 6

C

If the seller is selling a non-luxury good and decides to make the item a luxury good and increase the price by $3, what is the expected change in number of units sold, holding any advertising spending constant? a. 103 units b. -10.8 units c. 92.2 units d. 113.8 units

C

Interpret the coefficient on price. a. On average, a $1 increase in price will decrease the number of units sold by 3.6. b. On average, a $1 increase in price will increase the number of units sold by 3.6 units. c. On average holding all else constant, a $1 decrease in price will increase the number of units sold by 3.6 units. d. On average holding all else constant, a $1 decrease in price will decrease the number of units sold by 3.6 units.

C

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 is correct.

C

Suppose we found out that there is a heteroskedasticity problem that was not corrected. Are we able to tell whether the coefficient for luxury is statistically significant without correcting the standard errors? a. Yes, the p-value is zero before correcting the standard errors, so it should be even lower after correcting the standard errors. b. Yes, the p-value will increase, but not enough to make the coefficient insignificant. c. No, we cannot know how much the p-value will change without running the corrected regression. d. No, the coefficient will now be insignificant after correcting the standard error.

C

The difference between the observed value and the predicted value is called the a. Standard deviation b. Variance c. Error d. Laffer's Constant

C

The difference between the observed value and the predicted value is called... a. Standard deviation b. Variance c. Error d. Laffer's Constant

C

When we construct a confidence interval, what is our parameter of interest? a. The Variance b. The Standard Deviation c. The mean d. Range

C

A person wants to buy a laptop which costs $1000. When he purchases the laptop, he first applies a 20% discount and then uses a $15 off coupon. What percent of the cost of the laptop was removed by the discount and the coupon? a. 35% b. 24.5% c. 78.5% d. 21.5%

D

For a simple linear regression of car price (Y) on mileage (X), what is the correct interpretation of𝛽, the intercept? a. The price of a car for a car with average mileage b. A one unit increase in X increases Y by 𝛽 dollars. c. The mileage of a car when the price is zero. d. The average price of a car with zero mileage.

D

For a uniform distribution from 3 to 10, what is the probability of an observation being between 6 and 8? a. 20% b. 86% c. 43% d. 29%

D

If we run a simple linear regression and find an R2 = 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.

D

If we run a simple linear regression and find an R2 = 0.12, we can conclude which of the following? a. There is a weak 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% of the variation in Y.

D

Suppose you construct a 95% confidence interval based on a sample of students' height and find a confidence interval of (67.3, 70.2). What is the point estimate for students' average height? a. 67.3 b. 70.2 c. 69.5 d. 68.75

D

Which descriptive statistic does not give information about the spread of the data? a. Range b. Standard Deviation c. Variance d. Mean

D

Which factor does not affect the size of the margin of error? a. The confidence level. b. The sample size. c. The amount of variability in the population. d. The sample mean.

D

Which of the following regarding the Adjusted R2 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 R2 because it takes into account whether the variables you added to the regression equation are irrelevant or not. d. Shows the direction of the relationship between the two variables being compared.

D

Which of the following will decrease the width of a confidence interval? a. Increase the confidence level b. Increase the sample mean c. Increase the margin of error d. Increase the sample size

D

Which statement about homoskedasticity is not correct? a. A key assumption of the classic regression model (Ordinary Least Squares (SSE)) is homoskedasticity b. Homoskedasticity requires that the standard errors are constant across all x's. c. Coefficient estimates are correct under heteroskedasticity d. When heteroskedasticity is present, standard errors do not depend on any independent variable.

D

Which variables are statistically significant at the 95% level? a. Price b. TV advertising c. Internet Advertising d. All of the above

D