Question 1

If a data set has SSR = 400 and SSE = 100, then the coefficient of determination is

Accepted Answer

A)  0.10 
B)  0.25 
C)  0.40 
D)  0.80 
A)  0.10 
B)  0.25 
C)  0.40 
D)  0.80

Question 2

In regression analysis, the model in the form y = β₀ + β₁x + ε is called

Accepted Answer

A)  regression equation 
B)  correlation equation 
C)  estimated regression equation 
D)  regression model 
A)  regression equation 
B)  correlation equation 
C)  estimated regression equation 
D)  regression model

Question 3

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, Ey) = β₀ + β₁x, is known as

Accepted Answer

A)  regression equation 
B)  correlation equation 
C)  estimated regression equation 
D)  regression model 
A)  regression equation 
B)  correlation equation 
C)  estimated regression equation 
D)  regression model

Question 4

Exhibit 12-1
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\4&2\3&1\4&4\6&3\8&5
\end{array}$ SSE = 6
SST = 16
-Refer to Exhibit 12-1. The coefficient of determination is

Accepted Answer

A)  0.7096 
B)  - 0.7906 
C)  0.625 
D)  0.375 
A)  0.7096 
B)  - 0.7906 
C)  0.625 
D)  0.375

Question 5

In a regression analysis, the error term ε is a random variable with a mean or expected value of

Accepted Answer

A)  zero 
B)  one 
C)  any positive value 
D)  any value 
A)  zero 
B)  one 
C)  any positive value 
D)  any value

Question 6

If only MSE is known, you can compute the

Accepted Answer

A)  r square 
B)  coefficient of determination 
C)  standard error 
D)  all of these alternatives are correct 
A)  r square 
B)  coefficient of determination 
C)  standard error 
D)  all of these alternatives are correct

Question 7

Regression analysis was applied between demand for a product Y) and the price of the product X), and the following estimated regression equation was obtained. $\hat { Y }$ = 120 - 10 X
Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

Accepted Answer

A)  increase by 120 units 
B)  increase by 100 units 
C)  increase by 20 units 
D)  decease by 20 units 
A)  increase by 120 units 
B)  increase by 100 units 
C)  increase by 20 units 
D)  decease by 20 units

Question 8

Regression analysis was applied between sales in $1000) and advertising in $100) and the following regression function was obtained. = 500 + 4 X
$\hat { Y }$ Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales in dollars) is

Accepted Answer

A)  $900 
B)  $900,000 
C)  $40,500 
D)  $505,000 
A)  $900 
B)  $900,000 
C)  $40,500 
D)  $505,000

Question 9

Given below are seven observations collected in a regression study on two variables, X independent variable) and Y dependent variable).
 $\begin{array} { l l } 
x&y\2&12\3&9\6&8\7&7\8&6\9&5\9&2
\end{array}$ 
a. Develop the least squares estimated regression equation.
b. At 95% confidence, perform a t test and determine whether or not the slope is significantly different from zero.
c. Perform an F test to determine whether or not the model is significant. Let α = 0.05.
d. Compute the coefficient of determination.

Accepted Answer

a. = 13.75 -1.125X
 @#IMG-DLM& 
b. t = -5.196; p-v

Question 10

Below you are given a partial computer output based on a sample of 14 observations, relating an independent variable x) and a dependent variable y).
 $$\begin{array} { l c c } 
\text { Predictor } & \text { Coefificient } & \text { Standard Error } \
\text { Canstant } & 6.428 & 1.202 \
\text { X } & 0.470 & 0.035
\end{array}$$ Analysis of Variance
SOURCE SS
Regression 958.584
Error Residual)
Total 1021.429 
a. Develop the estimated regression line.
b. At α = 0.05, test for the significance of the slope.
c. At α = 0.05, perform an F test.
d. Determine the coefficient of determination.
e. Determine the coefficient of correlation.

Accepted Answer

a. @#IMG-DLM& = 6.428 + 0.47x
b. t = 13.529; p-val

Question 11

In a regression analysis, the variable that is being predicted

Accepted Answer

A)  must have the same units as the variable doing the predicting 
B)  is the independent variable 
C)  is the dependent variable 
D)  usually is denoted by x 
A)  must have the same units as the variable doing the predicting 
B)  is the independent variable 
C)  is the dependent variable 
D)  usually is denoted by x

Question 12

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

Accepted Answer

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 these alternatives is correct. 
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 these alternatives is correct.

Question 13

Exhibit 12-1
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\4&2\3&1\4&4\6&3\8&5
\end{array}$ SSE = 6
SST = 16
-Refer to Exhibit 12-1. The least squares estimate of the slope is

Accepted Answer

A)  1 
B)  2 
C)  3 
D)  4 
A)  1 
B)  2 
C)  3 
D)  4

Question 14

The model developed from sample data that has the form of $\widehat { y }$ = b? + b?x is known as

Accepted Answer

A)  regression equation 
B)  correlation equation 
C)  estimated regression equation 
D)  regression model 
A)  regression equation 
B)  correlation equation 
C)  estimated regression equation 
D)  regression model

Question 15

Exhibit 12-5
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\
1&1\2&2\3&3&\4&4\5&5
\end{array}$
-Refer to Exhibit 12-5. The MSE is

Accepted Answer

A)  0 
B)  -1 
C)  1 
D)  0.5 
A)  0 
B)  -1 
C)  1 
D)  0.5

Question 16

The coefficient of correlation

Accepted Answer

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 
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

Question 17

Exhibit 12-5
The following information regarding a dependent variable Y) and an independent variable X) is provided.
 $\begin{array} { l l } 
Y&X\
1&1\2&2\3&3&\4&4\5&5
\end{array}$
-Refer to Exhibit 12-5. The least squares estimate of the slope is

Accepted Answer

A)  1 
B)  -1 
C)  0 
D)  3 
A)  1 
B)  -1 
C)  0 
D)  3

Question 18

Exhibit 12-9
A regression and correlation analysis resulted in the following information regarding a dependent variable y) and an independent variable x).
 $\begin{array}{ll}
\Sigma \mathrm{X}=90 & \Sigma \mathrm{Y}-{\bar{\mathrm{Y}}) X}-\bar{X})=466 \
\Sigma \mathrm{Y}=170 & \Sigma \mathrm{Y}-\overline{\mathrm{Y}})^{2}=1434 \
\mathrm{n}=10\
\mathrm{SSE}=505.98 &  \Sigma \mathrm{X}-\bar{X})^{2}=234 
\end{array}$

-Refer to Exhibit 12-9. The sum of squares due to regression SSR) is

Accepted Answer

A)  1434 
B)  505.98 
C)  50.598 
D)  928.02 
A)  1434 
B)  505.98 
C)  50.598 
D)  928.02

Question 19

A regression analysis between sales Y in $1000) and advertising X in dollars) resulted in the following equation $\hat { Y }$ = 30,000 + 4 X
The above equation implies that an

Accepted Answer

A)  increase of $4 in advertising is associated with an increase of $4,000 in sales 
B)  increase of $1 in advertising is associated with an increase of $4 in sales 
C)  increase of $1 in advertising is associated with an increase of $34,000 in sales 
D)  increase of $1 in advertising is associated with an increase of $4,000 in sales 
A)  increase of $4 in advertising is associated with an increase of $4,000 in sales 
B)  increase of $1 in advertising is associated with an increase of $4 in sales 
C)  increase of $1 in advertising is associated with an increase of $34,000 in sales 
D)  increase of $1 in advertising is associated with an increase of $4,000 in sales

Question 20

If there is a very weak correlation between two variables, then the coefficient of determination must be

Accepted Answer

A)  much larger than 1, if the correlation is positive 
B)  much smaller than -1, if the correlation is negative 
C)  much larger than one 
D)  None of these alternatives is correct. 
A)  much larger than 1, if the correlation is positive 
B)  much smaller than -1, if the correlation is negative 
C)  much larger than one 
D)  None of these alternatives is correct.

If a data set has SSR = 400 and SSE = 100, then the coefficient of determination is

In regression analysis, the model in the form y = β₀ + β₁x + ε is called

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, Ey) = β₀ + β₁x, is known as

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The coefficient of determination is

In a regression analysis, the error term ε is a random variable with a mean or expected value of

If only MSE is known, you can compute the

Regression analysis was applied between demand for a product Y) and the price of the product X), and the following estimated regression equation was obtained. $\hat { Y }$ = 120 - 10 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

Regression analysis was applied between sales in $1000) and advertising in $100) and the following regression function was obtained. = 500 + 4 X $\hat { Y }$ Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales in dollars) is

In a regression analysis, the variable that is being predicted

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The least squares estimate of the slope is

The model developed from sample data that has the form of $\widehat { y }$ = b? + b?x is known as

Exhibit 12-5 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 1 1 2 2 3 3 4 4 5 5 -Refer to Exhibit 12-5. The MSE is

The coefficient of correlation

Exhibit 12-5 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 1 1 2 2 3 3 4 4 5 5 -Refer to Exhibit 12-5. The least squares estimate of the slope is

Exhibit 12-9 A regression and correlation analysis resulted in the following information regarding a dependent variable y) and an independent variable x). \Sigma=90 \Sigma- )X -)=466 \Sigma=170 \Sigma-=1434 =10 =505.98 \Sigma-=234 -Refer to Exhibit 12-9. The sum of squares due to regression SSR) is

A regression analysis between sales Y in $1000) and advertising X in dollars) resulted in the following equation $\hat { Y }$ = 30,000 + 4 X The above equation implies that an

If there is a very weak correlation between two variables, then the coefficient of determination must be

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

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

Multiple Regression

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Exam 12: Simple Linear Regression

If a data set has SSR = 400 and SSE = 100, then the coefficient of determination is

In regression analysis, the model in the form y = β₀ + β₁x + ε is called

The mathematical equation relating the independent variable to the expected value of the dependent variable; that is, Ey) = β₀ + β₁x, is known as

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The coefficient of determination is

In a regression analysis, the error term ε is a random variable with a mean or expected value of

If only MSE is known, you can compute the

Regression analysis was applied between demand for a product Y) and the price of the product X), and the following estimated regression equation was obtained. Y^\hat { Y }Y^ = 120 - 10 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

Regression analysis was applied between sales in $1000) and advertising in $100) and the following regression function was obtained. = 500 + 4 X Y^\hat { Y }Y^ Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales in dollars) is

In a regression analysis, the variable that is being predicted

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

Exhibit 12-1 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 4 2 3 1 4 4 6 3 8 5 SSE = 6 SST = 16 -Refer to Exhibit 12-1. The least squares estimate of the slope is

The model developed from sample data that has the form of y^\widehat { y }y​ = b? + b?x is known as

Exhibit 12-5 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 1 1 2 2 3 3 4 4 5 5 -Refer to Exhibit 12-5. The MSE is

The coefficient of correlation

Exhibit 12-5 The following information regarding a dependent variable Y) and an independent variable X) is provided. Y X 1 1 2 2 3 3 4 4 5 5 -Refer to Exhibit 12-5. The least squares estimate of the slope is

Exhibit 12-9 A regression and correlation analysis resulted in the following information regarding a dependent variable y) and an independent variable x). \Sigma=90 \Sigma- )X -)=466 \Sigma=170 \Sigma-=1434 =10 =505.98 \Sigma-=234 -Refer to Exhibit 12-9. The sum of squares due to regression SSR) is

A regression analysis between sales Y in $1000) and advertising X in dollars) resulted in the following equation Y^\hat { Y }Y^ = 30,000 + 4 X The above equation implies that an

If there is a very weak correlation between two variables, then the coefficient of determination must be

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

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

Multiple Regression

Filters

Regression analysis was applied between demand for a product Y) and the price of the product X), and the following estimated regression equation was obtained. $\hat { Y }$ = 120 - 10 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to

Regression analysis was applied between sales in $1000) and advertising in $100) and the following regression function was obtained. = 500 + 4 X $\hat { Y }$ Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales in dollars) is

The model developed from sample data that has the form of $\widehat { y }$ = b? + b?x is known as

A regression analysis between sales Y in $1000) and advertising X in dollars) resulted in the following equation $\hat { Y }$ = 30,000 + 4 X The above equation implies that an