Question 1

In a regression analysis, if SSE = 200 and SSR = 300, then the coefficient of determination is

Accepted Answer

A)  .67. 
B)  .60. 
C)  .40. 
D)  .20. 
A)  .67. 
B)  .60. 
C)  .40. 
D)  .20.

Question 2

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). $$\begin{array} { l l } 
\Sigma x = 90 & \sum \left( y - \frac { y } { x } \right) \left( x - { } ^ { x } \right) = 466 \
\Sigma y = 170 & \sum ( x - ) ^ { 2 } = 234 \
n = 10 & \Sigma \left( y - y ^ { 2 } \right) ^ { 2 } = 1434 \
\mathrm { SSE } = 505.98 &
\end{array}$$   The sample correlation coefficient equals

Accepted Answer

A)  .8045. 
B)  -.8045. 
C)  .3528. 
D)  -.3528. 
A)  .8045. 
B)  -.8045. 
C)  .3528. 
D)  -.3528.

Question 3

You are given the following information about y and x. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
5 & 4 \
7 & 6 \
9 & 2 \
11 & 4
\end{array}$$   The coefficient of determination equals

Accepted Answer

A)  .3162. 
B)  -.3162. 
C)  .10. 
D)  -.10. 
A)  .3162. 
B)  -.3162. 
C)  .10. 
D)  -.10.

Question 4

Shown below is a portion of a computer output for a regression analysis relating y (demand) and x (unit price). $$\begin{array}{l}
\text { ANOVA }\
\begin{array} { l l l } 
& d f & S S \
\text { Regression } & 1 & 5048.818 \
\text { Residual } & 46 & 3132.661 \
\text { Total } & 47 & 8181.479 \\
& \text { Coefficients } & \text { Standard Error } \
\text { Intercept } & 80.390 & 3.102 \
\mathrm { X } & - 2.137 & 0.248
\end{array}
\end{array}$$ ​ 
a.
Perform a t test and determine whether or not demand and unit price are related. Let α = .05.
b.
Perform an F test and determine whether or not demand and unit price are related. Let α = .05.
c.
Compute the coefficient of determination and interpret its meaning. Be very specific.
d.
Compute the coefficient of correlation and explain the relationship between demand and unit price.

Accepted Answer

a and b
​ @#IMG-DLM& ​
Using both the t and F test

Question 5

It is possible for the coefficient of determination to be

Accepted Answer

A)  larger than 1. 
B)  less than 1. 
C)  less than -1. 
D)  equal to -1. 
A)  larger than 1. 
B)  less than 1. 
C)  less than -1. 
D)  equal to -1.

Question 6

A descriptive measure of the strength of linear association between two variables is the​

Accepted Answer

A)  ​coefficient of determination. 
B)  ​slope b1 of the estimated regression line. 
C)  ​standard error of the estimate. 
D)  ​correlation coefficient. 
A)  ​coefficient of determination. 
B)  ​slope b1 of the estimated regression line. 
C)  ​standard error of the estimate. 
D)  ​correlation coefficient.

Question 7

In regression analysis, the model in the form y = $\beta _ { 0 }$ + $\beta _ { 1 }$ x + $\varepsilon$ is called the

Accepted Answer

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

Question 8

SSE can never be

Accepted Answer

A)  larger than SST. 
B)  smaller than SST. 
C)  equal to one. 
D)  equal to zero. 
A)  larger than SST. 
B)  smaller than SST. 
C)  equal to one. 
D)  equal to zero.

Question 9

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is the​

Accepted Answer

A)  ​standard error. 
B)  ​residual. 
C)  ​prediction interval. 
D)  ​variance. 
A)  ​standard error. 
B)  ​residual. 
C)  ​prediction interval. 
D)  ​variance.

Question 10

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

Accepted Answer

A)  average value of the independent variables. 
B)  average value of the dependent variable. 
C)  least squares line. 
D)  origin. 
A)  average value of the independent variables. 
B)  average value of the dependent variable. 
C)  least squares line. 
D)  origin.

Question 11

For the following data, the value of SSE = 18. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
15 & 4 \
17 & 6 \
23 & 2 \
17 & 4
\end{array}$$   The total sum of squares (SST) equals

Accepted Answer

A)  36. 
B)  18. 
C)  9. 
D)  2. 
A)  36. 
B)  18. 
C)  9. 
D)  2.

Question 12

In the following estimated regression equation $\hat { y }$ = b0 + b1x,

Accepted Answer

A)  b1 is the slope. 
B)  b1 is the intercept. 
C)  b1x is the slope. 
D)  b1x is the intercept. 
A)  b1 is the slope. 
B)  b1 is the intercept. 
C)  b1x is the slope. 
D)  b1x is the intercept.

Question 13

As the value of the coefficient of determination increases, the

Accepted Answer

A)  absolute value of the regression equation's slope decreases. 
B)  total number of degrees of freedom increases. 
C)  goodness of fit for the estimated regression equation increases. 
D)  value of the correlation coefficient decreases. 
A)  absolute value of the regression equation's slope decreases. 
B)  total number of degrees of freedom increases. 
C)  goodness of fit for the estimated regression equation increases. 
D)  value of the correlation coefficient decreases.

Question 14

Regression analysis was applied between sales (y in $1000) and advertising (x in $100) and the following estimated regression equation was obtained.   $\hat { y }$ = 80 + 6.2x
 
Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

Accepted Answer

A)  $62,080. 
B)  $142,000. 
C)  $700. 
D)  $700,000. 
A)  $62,080. 
B)  $142,000. 
C)  $700. 
D)  $700,000.

Question 15

If the coefficient of determination is equal to 1, then the coefficient of correlation

Accepted Answer

A)  must also be +1. 
B)  can be either -1 or +1. 
C)  can be any value between -1 to +1. 
D)  must be -1. 
A)  must also be +1. 
B)  can be either -1 or +1. 
C)  can be any value between -1 to +1. 
D)  must be -1.

Question 16

If the coefficient of correlation is .8, the percentage of variation in the dependent variable explained by the variation in the independent variable is

Accepted Answer

A)  .80%. 
B)  80%. 
C)  .64%. 
D)  64%. 
A)  .80%. 
B)  80%. 
C)  .64%. 
D)  64%.

Question 17

For the following data, the value of SSE = 18. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
15 & 4 \
17 & 6 \
23 & 2 \
17 & 4
\end{array}$$ 
The slope of the regression equation is

Accepted Answer

A)  18. 
B)  24. 
C)  .71. 
D)  -1.5. 
A)  18. 
B)  24. 
C)  .71. 
D)  -1.5.

Question 18

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained.   $$\begin{array} { l } 
\widehat { y } = 12 + 1.8 x \
n = 17 \
\mathrm { SSR } = 225 \
\mathrm { SSE } = 75 \
\mathrm {~s} b _ { 1 } = .2683
\end{array}$$  
To perform an F test, the p-value is

Accepted Answer

A)  less than .01. 
B)  between .01 and .025. 
C)  between .025 and .05. 
D)  greater than .10. 
A)  less than .01. 
B)  between .01 and .025. 
C)  between .025 and .05. 
D)  greater than .10.

Question 19

The model developed from sample data that has the form of $\hat { y }$ = b0 + b1x is known as the

Accepted Answer

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

Question 20

You are given the following information about y and x. $$\begin{array} { l l } 
\text { Dependent Variable } ( y ) & \text { Independent Variable } ( x ) \
5 & 1 \
4 & 2 \
3 & 3 \
2 & 4 \
1 & 5
\end{array}$$   The sample correlation coefficient equals

Accepted Answer

A)  0. 
B)  +1. 
C)  -1. 
D)  -.5. 
A)  0. 
B)  +1. 
C)  -1. 
D)  -.5.

In a regression analysis, if SSE = 200 and SSR = 300, then the coefficient of determination is

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). \Sigmax=90 y- x- =466 \Sigmay=170 (x-=234 n=10 \Sigma=1434 =505.98 The sample correlation coefficient equals

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 5 4 7 6 9 2 11 4 The coefficient of determination equals

It is possible for the coefficient of determination to be

A descriptive measure of the strength of linear association between two variables is the

In regression analysis, the model in the form y = $\beta _ { 0 }$ + $\beta _ { 1 }$ x + $\varepsilon$ is called the

SSE can never be

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is the

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

For the following data, the value of SSE = 18. Dependent Variable (y) Independent Variable (x) 15 4 17 6 23 2 17 4 The total sum of squares (SST) equals

In the following estimated regression equation $\hat { y }$ = b₀ + b₁x,

As the value of the coefficient of determination increases, the

Regression analysis was applied between sales (y in $1000) and advertising (x in $100) and the following estimated regression equation was obtained. $\hat { y }$ = 80 + 6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is

If the coefficient of determination is equal to 1, then the coefficient of correlation

If the coefficient of correlation is .8, the percentage of variation in the dependent variable explained by the variation in the independent variable is

For the following data, the value of SSE = 18. Dependent Variable (y) Independent Variable (x) 15 4 17 6 23 2 17 4 The slope of the regression equation is

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. =12+1.8x n=17 =225 =75 =.2683 To perform an F test, the p-value is

The model developed from sample data that has the form of $\hat { y }$ = b₀ + b₁x is known as the

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 5 1 4 2 3 3 2 4 1 5 The sample correlation coefficient equals

Data and Statistics

Descriptive Statistics: Tabulargraphical

Descriptive Statistics: Numerical

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Filters

Exam 14: Simple Linear Regression

In a regression analysis, if SSE = 200 and SSR = 300, then the coefficient of determination is

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). \Sigmax=90 y- x- =466 \Sigmay=170 (x-=234 n=10 \Sigma=1434 =505.98 The sample correlation coefficient equals

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 5 4 7 6 9 2 11 4 The coefficient of determination equals

It is possible for the coefficient of determination to be

A descriptive measure of the strength of linear association between two variables is the​

In regression analysis, the model in the form y = β0\beta _ { 0 }β0​ + β1\beta _ { 1 }β1​ x + ε\varepsilonε is called the

SSE can never be

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is the​

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

For the following data, the value of SSE = 18. Dependent Variable (y) Independent Variable (x) 15 4 17 6 23 2 17 4 The total sum of squares (SST) equals

In the following estimated regression equation y^\hat { y }y^​ = b0 + b1x,

As the value of the coefficient of determination increases, the

If the coefficient of determination is equal to 1, then the coefficient of correlation

If the coefficient of correlation is .8, the percentage of variation in the dependent variable explained by the variation in the independent variable is

For the following data, the value of SSE = 18. Dependent Variable (y) Independent Variable (x) 15 4 17 6 23 2 17 4 The slope of the regression equation is

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. =12+1.8x n=17 =225 =75 =.2683 To perform an F test, the p-value is

The model developed from sample data that has the form of y^\hat { y }y^​ = b0 + b1x is known as the

You are given the following information about y and x. Dependent Variable (y) Independent Variable (x) 5 1 4 2 3 3 2 4 1 5 The sample correlation coefficient equals

Data and Statistics

Descriptive Statistics: Tabulargraphical

Descriptive Statistics: Numerical

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Multiple Regression

Filters

A descriptive measure of the strength of linear association between two variables is the

In regression analysis, the model in the form y = $\beta _ { 0 }$ + $\beta _ { 1 }$ x + $\varepsilon$ is called the

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is the

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

In the following estimated regression equation $\hat { y }$ = b₀ + b₁x,

The model developed from sample data that has the form of $\hat { y }$ = b₀ + b₁x is known as the