5 DS 101 VERSION R082 – SAMPLE EXAM QUESTIONS

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MIS 175 Section 4 - Second Midterm Examination

DS 101 Version R082 – Sample Exam Questions

Simple Linear Regression Questions

1. In regression analysis, the model in the form is called

a.	regression equation
b.	correlation equation
c.	estimated regression equation
d.	regression model

2. The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, E(y) = 0 + 1x, is known as

a.	regression equation
b.	correlation equation
c.	estimated regression equation
d.	regression model

3. The model developed from sample data that has the form of is known as

a.	regression equation
b.	correlation equation
c.	estimated regression equation
d.	regression model

4. In regression analysis, the unbiased estimate of the variance is

a.	coefficient of correlation
b.	coefficient of determination
c.	mean square error
d.	slope of the regression equation

5. The interval estimate of the mean value of y for a given value of x is

a.	prediction interval estimate
b.	confidence interval estimate
c.	average regression
d.	x versus y correlation interval

6. The standard error is the

a.	t-statistic squared
b.	square root of SSE
c.	square root of SST
d.	square root of MSE

7. If MSE is known, you can compute the

a.	r square
b.	coefficient of determination
c.	standard error
d.	all of these alternatives are correct

8. In regression analysis, which of the following is not a required assumption about the error term ?

a.	The expected value of the error term is one.
b.	The variance of the error term is the same for all values of X.
c.	The values of the error term are independent.
d.	The error term is normally distributed.

9. Larger values of r² imply that the observations are more closely grouped about the

a.	average value of the independent variables
b.	average value of the dependent variable
c.	least squares line
d.	origin

10. In a regression and correlation analysis if r² = 1, then

a.	SSE must also be equal to one
b.	SSE must be equal to zero
c.	SSE can be any positive value
d.	SSE must be negative

11. In a regression and correlation analysis if r² = 1, then

a.	SSE = SST
b.	SSE = 1
c.	SSR = SSE
d.	SSR = SST

12. The coefficient of correlation

a.	is the square of the coefficient of determination
b.	is the square root of the coefficient of determination
c.	is the same as r-square
d.	can never be negative

13. In regression analysis, if the independent variable is measured in pounds, the dependent variable

a.	must also be in pounds
b.	must be in some unit of weight
c.	cannot be in pounds
d.	can be any units

14. A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation

= 50,000 - 8X

The above equation implies that an

a.	increase of $1 in price is associated with a decrease of $8 in sales
b.	increase of $8 in price is associated with an increase of $8,000 in sales
c.	increase of $1 in price is associated with a decrease of $42,000 in sales
d.	increase of $1 in price is associated with a decrease of $8000 in sales

15. Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.

= 500 + 4 X

Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is

a.	$900
b.	$900,000
c.	$40,500
d.	$505,000

Multiple Regression Questions

1. The mathematical equation relating the expected value of the dependent variable to the value of the independent variables, which has the form of E(y) = is

a.	a simple linear regression model
b.	a multiple nonlinear regression model
c.	an estimated multiple regression equation
d.	a multiple regression equation

2. The estimate of the multiple regression equation based on the sample data, which has the form of E(y) =

a.	a simple linear regression model
b.	a multiple nonlinear regression model
c.	an estimated multiple regression equation
d.	a multiple regression equation

3. The mathematical equation that explains how the dependent variable y is related to several independent variables x₁, x₂, ..., x_p and the error term  is

a.	a simple nonlinear regression model
b.	a multiple regression model
c.	an estimated multiple regression equation
d.	a multiple regression equation

4. A measure of the effect of an unusual x value on the regression results is called

a.	Cook’s D
b.	Leverage
c.	odd ratio
d.	unusual regression

5. In a multiple regression model, the error term  is assumed to be a random variable with a mean of

a.	zero
b.	-1
c.	1
d.	any value

6. 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 these alternatives is correct.

7. A multiple regression model has the form

As x₁ increases by 1 unit (holding x₂ constant), y is expected to

a.	increase by 9 units
b.	decrease by 9 units
c.	increase by 2 units
d.	decrease by 2 units

8. A multiple regression model has the form

As X increases by 1 unit (holding W constant), Y is expected to

a.	increase by 11 units
b.	decrease by 11 units
c.	increase by 6 units
d.	decrease by 6 units

Exhibit 15-2

A regression model between sales (Y in $1,000), unit price (X₁ in dollars) and television advertisement (X₂ in dollars) resulted in the following function:

For this model SSR = 3500, SSE = 1500, and the sample size is 18.

9. Refer to Exhibit 15-2. The coefficient of the unit price indicates that if the unit price is

a.	increased by $1 (holding advertising constant), sales are expected to increase by $3
b.	decreased by $1 (holding advertising constant), sales are expected to decrease by $3
c.	increased by $1 (holding advertising constant), sales are expected to increase by $4,000
d.	increased by $1 (holding advertising constant), sales are expected to decrease by $3,000

10. Refer to Exhibit 15-2. The coefficient of X₂ indicates that if television advertising is increased by $1 (holding the unit price constant), sales are expected to

a.	increase by $5
b.	increase by $12,000
c.	increase by $5,000
d.	decrease by $2,000

Exhibit 15-4

11. Which equation describes the multiple regression model?

a.	Equation A
b.	Equation B
c.	Equation C
d.	Equation D

12. Which equation gives the estimated regression line?

a.	Equation A
b.	Equation B
c.	Equation C
d.	Equation D

13. Which equation describes the multiple regression equation?

a.	Equation A
b.	Equation B
c.	Equation C
d.	Equation D

Exhibit 15-5

Below you are given a partial Minitab output based on a sample of 25 observations.

	Coefficient	Standard Error
Constant	145.321	48.682
X₁	25.625	9.150
X₂	-5.720	3.575
X₃	0.823	0.183

14. Refer to Exhibit 15-5. The estimated regression equation is

a.
b.
c.
d.

15. Refer to Exhibit 15-5. The interpretation of the coefficient on X₁ is that

a.	a one unit change in X₁ will lead to a 25.625 unit change in Y
b.	a one unit change in X₁ will lead to a 25.625 unit increase in Y when all other variables are held constant
c.	a one unit change in X₁ will lead to a 25.625 unit increase in X₂ when all other variables are held constant
d.	It is impossible to interpret the coefficient.

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