Question 1

In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The coefficient of determination is

Accepted Answer

A) 0.300 
B) 0.192 
C) 0.500 
D) 0.700 
A) 0.300 
B) 0.192 
C) 0.500 
D) 0.700 D

Question 2

A multiple regression model has the form   = 7 + 2 x1 + 9 x2 As x1 increases by 1 unit (holding x2 constant),   is expected to

Accepted Answer

A) increase by 9 units 
B) decrease by 9 units 
C) increase by 2 units 
D) decrease by 2 units 
A) increase by 9 units 
B) decrease by 9 units 
C) increase by 2 units 
D) decrease by 2 units C

Question 3

In a multiple regression model, the error term F1F1F1S1F1F1F10 is assumed to be a random variable with a mean of

Accepted Answer

A) zero 
B) -1 
C) 1 
D) any value 
A) zero 
B) -1 
C) 1 
D) any value A

Question 4

Exhibit 13-4
a.
y = F1F1F1S1F1F1F10S1U1B10S1U1B0 + F1F1F1S1F1F1F10S1U1B11S1U1B0xS1U1B11S1U1B0 + F1F1F1S1F1F1F10S1U1B12S1U1B0xS1U1B12S1U1B0 + F1F1F1S1F1F1F10
b.
E(y) = F1F1F1S1F1F1F10S1U1B10S1U1B0 + F1F1F1S1F1F1F10S1U1B11S1U1B0xS1U1B11S1U1B0 + F1F1F1S1F1F1F10S1U1B12S1U1B0xS1U1B12S1U1B0
c. = bS1U1B1oS1U1B0 + bS1U1B11S1U1B0 xS1U1B11S1U1B0 + bS1U1B12S1U1B0 xS1U1B12S1U1B0
d.
E(y) = F1F1F1S1F1F1F10S1U1B10S1U1B0 + F1F1F1S1F1F1F10S1U1B11S1U1B0xS1U1B11S1U1B0 + F1F1F1S1F1F1F10S1U1B12S1U1B0xS1U1B12S1U1B0
-Refer to Exhibit 13-4. Which equation describes the multiple regression equation?

Accepted Answer

A) equation a 
B) equation b 
C) equation c 
D) equation d 
A) equation a 
B) equation b 
C) equation c 
D) equation d

Question 5

Exhibit 13-6
Below you are given a partial Excel output based on a sample of 16 observations.
  
-Refer to Exhibit 13-6. The test statistic used to determine if there is a relationship among the variables equals

Accepted Answer

A) -1.4 
B) 0.2 
C) 0.77 
D) 5 
A) -1.4 
B) 0.2 
C) 0.77 
D) 5

Question 6

Multiple regression analysis was used to study how an individual's income (y in thousands of dollars) is influenced by age (x1 in years), level of education (x2 ranging from 1 to 5), and the person's gender (x3 where 0 =female and 1=male). The following is a partial result of Excel output that was used on a sample of 20 individuals.
   
a.Compute the coefficient of determination.
b.Perform a t test and determine whether or not the coefficient of the variable "level of education" (i.e., x2) is significantly different from zero. Let F1F1F1S1F1F1F10 = 0.05.
c.At F1F1F1S1F1F1F10 = 0.05, perform an F test and determine whether or not the regression model is significant.
d.As you note the coefficient of x3 is -0.510. Fully interpret the meaning of this coefficient.

Accepted Answer

a.0.4286
b.t = 4.84 > 2.12; si

Question 7

If a qualitative variable has k levels, the number of dummy variables required is

Accepted Answer

A) k F1F1F1S1F1F1F10 1 
B) k 
C) k + 1 
D) 2k 
A) k F1F1F1S1F1F1F10 1 
B) k 
C) k + 1 
D) 2k

Question 8

Exhibit 13-5
Below you are given a partial Excel output based on a sample of 25 observations.
  
-Refer to Exhibit 13-5. Carry out the test of significance for the parameter F1F1F1S1F1F1F101 at the 5% level. The null hypothesis should be

Accepted Answer

A) rejected 
B) not rejected 
C) revised 
D) None of these alternatives is correct. 
A) rejected 
B) not rejected 
C) revised 
D) None of these alternatives is correct.

Question 9

The multiple coefficient of determination is

Accepted Answer

A) MSR/MST 
B) MSR/MSE 
C) SSR/SST 
D) SSE/SSR 
A) MSR/MST 
B) MSR/MSE 
C) SSR/SST 
D) SSE/SSR

Question 10

Exhibit 13-6
Below you are given a partial Excel output based on a sample of 16 observations.
  
-Refer to Exhibit 13-6. The t value obtained from the table which is used to test an individual parameter at the 1% level is

Accepted Answer

A) 2.65 
B) 2.921 
C) 2.977 
D) 3.012 
A) 2.65 
B) 2.921 
C) 2.977 
D) 3.012

Question 11

In a multiple regression model, the variance of the error term F1F1F1S1F1F1F10 is assumed to be

Accepted Answer

A) the same for all values of the dependent variable 
B) zero 
C) the same for all values of the independent variable 
D) -1 
A) the same for all values of the dependent variable 
B) zero 
C) the same for all values of the independent variable 
D) -1

Question 12

Exhibit 13-6
Below you are given a partial Excel output based on a sample of 16 observations.
  
-Refer to Exhibit 13-6. The interpretation of the coefficient of x1 is that

Accepted Answer

A) a one unit change in x1 will lead to a 3.682 unit decrease in y 
B) a one unit increase in x1 will lead to a 3.682 unit decrease in y when all other variables are held constant 
C) a one unit increase in x1 will lead to a 3.682 unit decrease in x2 when all other variables are held constant 
D) It is impossible to interpret the coefficient. 
A) a one unit change in x1 will lead to a 3.682 unit decrease in y 
B) a one unit increase in x1 will lead to a 3.682 unit decrease in y when all other variables are held constant 
C) a one unit increase in x1 will lead to a 3.682 unit decrease in x2 when all other variables are held constant 
D) It is impossible to interpret the coefficient.

Question 13

The following regression model has been proposed to predict sales at a furniture store.   = 10 - 4x1 + 7x2 + 18x3
where
x1 = competitor's previous day's sales (in $1,000s)
x2 = population within 1 mile (in 1000s)
x3 = 1 if any form of advertising was used, 0 if otherwise   = sales (in $1,000s) 
a.Fully interpret the meaning of the coefficient of x3.
b.Predict sales (in dollars) for a store with competitor's previous day's sale of $3,000, a population of 10,000 within 1 mile, and six radio advertisements.

Accepted Answer

a.When advertising w

Question 14

The Natural Drink Company has developed a regression model relating its sales (y in $10,000s) with four independent variables. The four independent variables are price per unit (PRICE, in dollars), competitor's price (COMPRICE, in dollars), advertising (ADV, in $1,000s) and type of container used (CONTAIN; 1 = Cans and 0 = Bottles). Part of the regression results is shown below. (Assume n = 25)
   
a.If the manufacturer uses can containers, his price is $1.25, advertising $200,000, and his competitor's price is $1.50, what is your estimate of his sales? Give your answer in dollars.
b.Test to see if there is a significant relationship between sales and unit price. Let F1F1F1S1F1F1F10 = 0.05.
c.Test to see if there is a significant relationship between sales and advertising. Let F1F1F1S1F1F1F10 = 0.05.
d.Is the type of container a significant variable? Let F1F1F1S1F1F1F10 = 0.05.
e.Test to see if there is a significant relationship between sales and competitor's price. Let F1F1F1S1F1F1F10 = 0.05.

Accepted Answer

a.$3,228,490
b.t = -2.8 < - 2.

Question 15

The ratio of MSE/MSR yields

Accepted Answer

A) SST 
B) the F statistic 
C) SSR 
D) None of these alternatives is correct. 
A) SST 
B) the F statistic 
C) SSR 
D) None of these alternatives is correct.

Question 16

In multiple regression analysis,

Accepted Answer

A) there can be any number of dependent variables but only one independent variable 
B) there must be only one independent variable 
C) the coefficient of determination must be larger than 1 
D) there can be several independent variables, but only one dependent variable 
A) there can be any number of dependent variables but only one independent variable 
B) there must be only one independent variable 
C) the coefficient of determination must be larger than 1 
D) there can be several independent variables, but only one dependent variable

Question 17

A regression model in which more than one independent variable is used to predict the dependent variable is called

Accepted Answer

A) a simple linear regression model 
B) a multiple regression model 
C) an independent model 
D) None of these alternatives is correct. 
A) a simple linear regression model 
B) a multiple regression model 
C) an independent model 
D) None of these alternatives is correct.

Question 18

Exhibit 13-1
In a regression model involving 44 observations, the following estimated regression equation was obtained.   = 29 + 18xS1U1B11S1U1B0 +43xS1U1B12S1U1B0 + 87xS1U1B13S1U1B0
For this model SSR = 600 and SSE = 400.
-Refer to Exhibit 13-1. MSR for this model is

Accepted Answer

A) 200 
B) 10 
C) 1,000 
D) 43 
A) 200 
B) 10 
C) 1,000 
D) 43

Question 19

Exhibit 13-5
Below you are given a partial Excel output based on a sample of 25 observations.
  
-Refer to Exhibit 13-5. The estimated regression equation is

Accepted Answer

A) y = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 + F1F1F1S1F1F1F103x3 + F1F1F1S1F1F1F10 
B) E(y) = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 + F1F1F1S1F1F1F103x3 
C)  = 145.321 + 25.625x1 - 5.720x2 + 0.823x3 
D)  = 48.682 + 9.15x1 + 3.575x2 + 0.183x3 
A) y = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 + F1F1F1S1F1F1F103x3 + F1F1F1S1F1F1F10 
B) E(y) = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 + F1F1F1S1F1F1F103x3 
C)  = 145.321 + 25.625x1 - 5.720x2 + 0.823x3 
D)  = 48.682 + 9.15x1 + 3.575x2 + 0.183x3

Question 20

Exhibit 13-8
The following estimated regression model was developed relating yearly income (y in $1,000s) of 30 individuals with their age (xS1U1B11S1U1B0) and their gender (xS1U1B12S1U1B0) (0 if male and 1 if female).   = 30 + 0.7xS1U1B11S1U1B0 + 3xS1U1B12S1U1B0
Also provided are SST = 1,200 and SSE = 384.
-Refer to Exhibit 13-8. From the above function, it can be said that the expected yearly income of

Accepted Answer

A) males is $3 more than females 
B) females is $3 more than males 
C) males is $3,000 more than females 
D) females is $3,000 more than males 
A) males is $3 more than females 
B) females is $3 more than males 
C) males is $3,000 more than females 
D) females is $3,000 more than males

In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The coefficient of determination is

A multiple regression model has the form = 7 + 2 x₁ + 9 x₂ As x₁ increases by 1 unit (holding x₂ constant), is expected to

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

Exhibit 13-4 a. y = ₀ + ₁x₁ + ₂x₂ +  b. E(y) = ₀ + ₁x₁ + ₂x₂ c.= b_o + b₁ x₁ + b₂ x₂ d. E(y) = ₀ + ₁x₁ + ₂x₂ -Refer to Exhibit 13-4. Which equation describes the multiple regression equation?

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The test statistic used to determine if there is a relationship among the variables equals

If a qualitative variable has k levels, the number of dummy variables required is

Exhibit 13-5 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 13-5. Carry out the test of significance for the parameter ₁ at the 5% level. The null hypothesis should be

The multiple coefficient of determination is

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The t value obtained from the table which is used to test an individual parameter at the 1% level is

In a multiple regression model, the variance of the error term  is assumed to be

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The interpretation of the coefficient of x₁ is that

The ratio of MSE/MSR yields

In multiple regression analysis,

A regression model in which more than one independent variable is used to predict the dependent variable is called

Exhibit 13-1 In a regression model involving 44 observations, the following estimated regression equation was obtained. = 29 + 18x₁ +43x₂ + 87x₃ For this model SSR = 600 and SSE = 400. -Refer to Exhibit 13-1. MSR for this model is

Exhibit 13-5 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 13-5. The estimated regression equation is

Data and Statistics

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Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

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Comparisons Involving Means, Experimental Design, and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

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Exam 13: Multiple Regression

In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The coefficient of determination is

A multiple regression model has the form = 7 + 2 x1 + 9 x2 As x1 increases by 1 unit (holding x2 constant), is expected to

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

Exhibit 13-4 a. y = 0 + 1x1 + 2x2 +  b. E(y) = 0 + 1x1 + 2x2 c.= bo + b1 x1 + b2 x2 d. E(y) = 0 + 1x1 + 2x2 -Refer to Exhibit 13-4. Which equation describes the multiple regression equation?

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The test statistic used to determine if there is a relationship among the variables equals

If a qualitative variable has k levels, the number of dummy variables required is

Exhibit 13-5 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 13-5. Carry out the test of significance for the parameter 1 at the 5% level. The null hypothesis should be

The multiple coefficient of determination is

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The t value obtained from the table which is used to test an individual parameter at the 1% level is

In a multiple regression model, the variance of the error term  is assumed to be

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The interpretation of the coefficient of x1 is that

The ratio of MSE/MSR yields

In multiple regression analysis,

A regression model in which more than one independent variable is used to predict the dependent variable is called

Exhibit 13-1 In a regression model involving 44 observations, the following estimated regression equation was obtained. = 29 + 18x1 +43x2 + 87x3 For this model SSR = 600 and SSE = 400. -Refer to Exhibit 13-1. MSR for this model is

Exhibit 13-5 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 13-5. The estimated regression equation is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Presentations

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design, and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Simple Linear Regression

Statistical Methods for Quality Control

Time Series Analysis and Forecastng

Filters

A multiple regression model has the form = 7 + 2 x₁ + 9 x₂ As x₁ increases by 1 unit (holding x₂ constant), is expected to

Exhibit 13-4 a. y = ₀ + ₁x₁ + ₂x₂ +  b. E(y) = ₀ + ₁x₁ + ₂x₂ c.= b_o + b₁ x₁ + b₂ x₂ d. E(y) = ₀ + ₁x₁ + ₂x₂ -Refer to Exhibit 13-4. Which equation describes the multiple regression equation?

Exhibit 13-5 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 13-5. Carry out the test of significance for the parameter ₁ at the 5% level. The null hypothesis should be

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The interpretation of the coefficient of x₁ is that

Exhibit 13-1 In a regression model involving 44 observations, the following estimated regression equation was obtained. = 29 + 18x₁ +43x₂ + 87x₃ For this model SSR = 600 and SSE = 400. -Refer to Exhibit 13-1. MSR for this model is