Chapter 2
1. A dependent variable is also known as a(n) _____.
a. explanatory variable
b. control variable
c. predictor variable
d. respon variable
Answer: d
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Definition of the Simple Regression Model
BUSPROG:
Feedback: A dependent variable is known as a respon variable.
2. If a change in variable x caus a change in variable y, variable x is called the _____.
a. dependent variable
b. explained variable
c. explanatory variable
d. respon variable
Answer: c
Difficulty: Easy
Bloom’s: Comprehension
A-Head: Definition of the Simple Regression Model
BUSPROG:
Feedback: If a change in variable x caus a change in variable y, variable x is called the independent variable or the explanatory variable.
3. In the equation y = + x + u, is the _____.
a. dependent variable
b. independent variable
c. slope parameter
d. intercept parameter
Answer: d
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Definition of the Simple Regression Model
BUSPROG:
Feedback: In the equation y = + x + u, is the intercept parameter.
4. In the equation y = + x + u, what is the estimated value of?
a.
b.
c.
d.
Answer: a
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Deriving the Ordinary Least Squares Estimates
BUSPROG:
Feedback: The estimated value of is .
5. In the equation c = + i + u, c denotes consumption and i denotes income. What is the residual for the 5th obrvation if =$500 and =$475?
a. $975
b. $300
c. $25
d. $50
Answer: c
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Deriving the Ordinary Least Squares Estimates
BUSPROG:
Feedback: The formula for calculating the residual for the ith obrvation is . In this ca, the residual is =$500 -$475= $25.
6. What does the equation denote if the regression equation is y = β0 + β1x1 + u?
a. The explained sum of squares
b. The total sum of squares
c. The sample regression function
d. The population regression function
Answer: c
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Deriving the Ordinary Least Squares Estimates
BUSPROG:
Feedback: The equation denotes the sample regression function of the given regression model.
7. Consider the following regression model: y = β0 + β1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?
a. The sum, and therefore the sample average of the OLS residuals, is positive.
b. The sum of the OLS residuals is negative.
c. The sample covariance between the regressors and the OLS residuals is positive.
d. The point (, ) always lies on the OLS regression line.
Answer: d
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Properties of OLS on Any Sample of Data
BUSPROG:
Feedback: An important property of the OLS estimates is that the point (, ) always lies on the OLS regression line. In other words, if , the predicted value of .
8. The explained sum of squares for the regression function, , is defined as _____.
a.
b.
c.
d.
Answer: b
Difficulty: Easy
Bloom’s: Knowledge
A-Head: Properties of OLS on Any Sample of Data
BUSPROG:
Feedback: The explained sum of squares is defined as
9. If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?
a. 64
b. 56
c. 32
d. 18
Answer: b
Difficulty: Moderate
Bloom’s: Application
A-Head: Properties of OLS on Any Sample of Data
BUSPROG: Analytic
Feedback: Total sum of squares (SST) is given by the sum of explained sum of squares (SSE) and residual sum of squares (SSR). Therefore, in this ca, SSE=81-25=56.
10. If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?
a. 0.73
b. 0.55
c. 0.27
d. 1.2
Answer: c
Difficulty: Moderate
Bloom’s: Application
A-Head: Properties of OLS on Any Sample of Data
BUSPROG: Analytic
Feedback: The formula for calculating the coefficient of determination is . In this ca,
11. Which of the following is a nonlinear regression model?
a. y = β0 + β1x1/2 + u
