Question 1

Application of the least squares method results in values of the y-intercept and the slope that minimizes the sum of the squared deviations between the​

Accepted Answer

A)  ​observed values of the independent variable and the predicted values of the independent variable. 
B)  ​observed values of the independent variable and the predicted values of the dependent variable. 
C)  ​observed values of the dependent variable and the predicted values of the dependent variable. 
D)  ​observed values of the dependent variable and the predicted values of the independent variable. 
A)  ​observed values of the independent variable and the predicted values of the independent variable. 
B)  ​observed values of the independent variable and the predicted values of the dependent variable. 
C)  ​observed values of the dependent variable and the predicted values of the dependent variable. 
D)  ​observed values of the dependent variable and the predicted values of the independent variable.

Question 2

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 sample correlation coefficient equals

Accepted Answer

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

Question 3

A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation:   $\hat { y }$ = 9 - 3x
 
The above equation implies that if the price is increased by $1, the demand is expected to

Accepted Answer

A)  increase by 6 units. 
B)  decrease by 3 units. 
C)  decrease by 6000 units. 
D)  decrease by 3000 units. 
A)  increase by 6 units. 
B)  decrease by 3 units. 
C)  decrease by 6000 units. 
D)  decrease by 3000 units.

Question 4

In a regression analysis, if SST = 4500 and SSE = 1575, then the coefficient of determination is

Accepted Answer

A)  .35. 
B)  .65. 
C)  .85. 
D)  .45. 
A)  .35. 
B)  .65. 
C)  .85. 
D)  .45.

Question 5

The following information regarding a dependent variable y and an independent variable x is provided: $$\begin{array} { l l } 
\Sigma x = 90 & \sum \left( y - \frac { y } { ) } \right) ( x - x ) = - 156 \
\Sigma y = 340 & \Sigma \left( x - \frac { x } { 2 } \right) ^ { 2 } = 234 \
n = 4 & \sum ( y - y ) ^ { 2 } = 1974 \
\mathrm { SSR } = 104 &
\end{array}$$   The total sum of squares (SST) is

Accepted Answer

A)  -156. 
B)  234. 
C)  1870. 
D)  1974. 
A)  -156. 
B)  234. 
C)  1870. 
D)  1974.

Question 6

A regression and correlation analysis resulted in the following information regarding an independent variable (x) and a dependent variable (y). $$\begin{array} { l l } 
\sum x = 42 & \sum ( y - y ) ( x - x ) = 37 \
\Sigma y = 63 & \sum ( x - \bar { x } ) ^ { 2 } = 84 \
n = 7 & \Sigma ( y - \bar { y } ) ^ { 2 } = 28 \
& \sum ( y - \widehat { y } ) ^ { 2 } = 11.7024
\end{array}$$ ​ 
a.
Develop the least squares estimated regression equation.
b.
At a .05 level of significance, 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 = .05.
d.
Compute the coefficient of determination.

Accepted Answer

​
a. @#IMG-DLM& = 6.357 + .440

Question 7

If there is a very strong 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)  equal to zero. 
D)  closer or equal to 1. 
A)  much larger than 1, if the correlation is positive. 
B)  much smaller than -1, if the correlation is negative. 
C)  equal to zero. 
D)  closer or equal to 1.

Question 8

Correlation analysis is used to determine

Accepted Answer

A)  the equation of the regression line. 
B)  the strength of the linear relationship between the dependent and the independent variables. 
C)  a specific value of the dependent variable for a given value of the independent variable. 
D)  a cause-and-effect relationship between the dependent and the independent variables. 
A)  the equation of the regression line. 
B)  the strength of the linear relationship between the dependent and the independent variables. 
C)  a specific value of the dependent variable for a given value of the independent variable. 
D)  a cause-and-effect relationship between the dependent and the independent variables.

Question 9

If the coefficient of correlation is a negative value, then the coefficient of determination

Accepted Answer

A)  must also be negative. 
B)  must be zero. 
C)  can be either negative or positive. 
D)  will be positive. 
A)  must also be negative. 
B)  must be zero. 
C)  can be either negative or positive. 
D)  will be positive.

Question 10

If the coefficient of determination is .90, the percentage of variation in the dependent variable explained by the variation in the independent variable is

Accepted Answer

A)  .90%. 
B)  90%. 
C)  81%. 
D)  .81%. 
A)  .90%. 
B)  90%. 
C)  81%. 
D)  .81%.

Question 11

If the coefficient of correlation is .90, then the coefficient of determination

Accepted Answer

A)  is also .90. 
B)  is either .81 or -.81. 
C)  will be -.90. 
D)  must be .81. 
A)  is also .90. 
B)  is either .81 or -.81. 
C)  will be -.90. 
D)  must be .81.

Question 12

If the coefficient of correlation is a positive value, then the

Accepted Answer

A)  intercept of the regression line must also be positive. 
B)  coefficient of determination can be either a negative or a positive value, depending on the slope. 
C)  regression equation could have either a positive or a negative slope. 
D)  slope of the regression line must be positive. 
A)  intercept of the regression line must also be positive. 
B)  coefficient of determination can be either a negative or a positive value, depending on the slope. 
C)  regression equation could have either a positive or a negative slope. 
D)  slope of the regression line must be positive.

Question 13

In regression analysis, the variable that is being predicted is the

Accepted Answer

A)  dependent variable. 
B)  independent variable. 
C)  intercept variable. 
D)  error variable. 
A)  dependent variable. 
B)  independent variable. 
C)  intercept variable. 
D)  error variable.

Question 14

In a regression analysis, the coefficient of correlation is .16.The coefficient of determination in this situation is

Accepted Answer

A)  .4000. 
B)  .0256. 
C)  4.00. 
D)  2.56. 
A)  .4000. 
B)  .0256. 
C)  4.00. 
D)  2.56.

Question 15

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
 
The coefficient of determination is

Accepted Answer

A)  .7906. 
B)  -.7906. 
C)  .625. 
D)  .375. 
A)  .7906. 
B)  -.7906. 
C)  .625. 
D)  .375.

Question 16

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
 
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 17

In regression analysis, if the dependent variable is measured in dollars, the independent variable

Accepted Answer

A)  must also be in dollars. 
B)  must be in some units of currency. 
C)  can be measured in any units. 
D)  cannot be in dollars. 
A)  must also be in dollars. 
B)  must be in some units of currency. 
C)  can be measured in any units. 
D)  cannot be in dollars.

Question 18

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained.   $$\begin{array} { l } 
\widehat { y } = 12 + 1.8 x \
n = 17 \
\mathrm { SSR } = 225 \
\mathrm { SSE } = 75 \
\mathrm {~s} b _ { 1 } = .2683
\end{array}$$ The critical t value for testing the significance of the slope, at a .05 level of significance, is

Accepted Answer

A)  1.753. 
B)  2.131. 
C)  1.746. 
D)  2.120. 
A)  1.753. 
B)  2.131. 
C)  1.746. 
D)  2.120.

Question 19

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)  one dependent, one independent, and several error variables are related. 
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)  one dependent, one independent, and several error variables are related.

Question 20

In a regression analysis, the regression equation is given by y = 12 - 6x.If SSE = 510 and SST = 1000, then the coefficient of correlation is

Accepted Answer

A)  -.7. 
B)  +.7. 
C)  .49. 
D)  -.49. 
A)  -.7. 
B)  +.7. 
C)  .49. 
D)  -.49.

Application of the least squares method results in values of the y-intercept and the slope that minimizes the sum of the squared deviations between the

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 sample correlation coefficient equals

A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation: $\hat { y }$ = 9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to

In a regression analysis, if SST = 4500 and SSE = 1575, then the coefficient of determination is

The following information regarding a dependent variable y and an independent variable x is provided: \Sigmax=90 y- (x-x)=-156 \Sigmay=340 \Sigma=234 n=4 (y-y=1974 =104 The total sum of squares (SST) is

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

Correlation analysis is used to determine

If the coefficient of correlation is a negative value, then the coefficient of determination

If the coefficient of determination is .90, the percentage of variation in the dependent variable explained by the variation in the independent variable is

If the coefficient of correlation is .90, then the coefficient of determination

If the coefficient of correlation is a positive value, then the

In regression analysis, the variable that is being predicted is the

In a regression analysis, the coefficient of correlation is .16.The coefficient of determination in this situation is

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 The coefficient of determination is

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 The least squares estimate of the slope is

In regression analysis, if the dependent variable is measured in dollars, the independent variable

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 The critical t value for testing the significance of the slope, at a .05 level of significance, is

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

In a regression analysis, the regression equation is given by y = 12 - 6x.If SSE = 510 and SST = 1000, then the coefficient of correlation is

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

Application of the least squares method results in values of the y-intercept and the slope that minimizes the sum of the squared deviations between the​

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 sample correlation coefficient equals

A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation: y^\hat { y }y^​ = 9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to

In a regression analysis, if SST = 4500 and SSE = 1575, then the coefficient of determination is

The following information regarding a dependent variable y and an independent variable x is provided: \Sigmax=90 y- (x-x)=-156 \Sigmay=340 \Sigma=234 n=4 (y-y=1974 =104 The total sum of squares (SST) is

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

Correlation analysis is used to determine

If the coefficient of correlation is a negative value, then the coefficient of determination

If the coefficient of determination is .90, the percentage of variation in the dependent variable explained by the variation in the independent variable is

If the coefficient of correlation is .90, then the coefficient of determination

If the coefficient of correlation is a positive value, then the

In regression analysis, the variable that is being predicted is the

In a regression analysis, the coefficient of correlation is .16.The coefficient of determination in this situation is

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 The coefficient of determination is

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 The least squares estimate of the slope is

In regression analysis, if the dependent variable is measured in dollars, the independent variable

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 The critical t value for testing the significance of the slope, at a .05 level of significance, is

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

In a regression analysis, the regression equation is given by y = 12 - 6x.If SSE = 510 and SST = 1000, then the coefficient of correlation is

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

Application of the least squares method results in values of the y-intercept and the slope that minimizes the sum of the squared deviations between the

A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation: $\hat { y }$ = 9 - 3x The above equation implies that if the price is increased by $1, the demand is expected to