Question 1

The dependent variable is the variable that is being described,predicted,or controlled.

Accepted Answer

A) True 
 B)False  True

Question 2

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

$$\begin{array} { l l l l l } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \ \text { Constant } & 4.8615 & 0.5201 & 9.35 & 0.000 \ \text { Independent Var } & - 0.34655 & 0.05866 & & \end{array}$$ $$S = 0.4862 \quad \mathrm { R } - \mathrm { Sq } =$$ Analysis of Variance $\begin{array}{lcccccc} \text { Source } & \text { DF } & \text { SS } & & \text { MS } & \text { F } & \text { P } \ \text { Regression } & 1 & & & & 34.90 & 0.000 \ \text { Residual Error } & 13 & & & & & \ \text { Total } & 14 & 11.3240 & & & & \end{array}$ What is the estimated slope? b₁ = -0.347

Question 3

Regression Analysis
  
The local grocery store wants to predict its daily sales in dollars.The manager believes that the amount of newspaper advertising significantly affects the store's sales.He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars)and advertising expenditures (in thousands of dollars).The Excel/MegaStat output given above summarizes the results of the regression model.
At a significance level of .05,test the significance of the slope and state your conclusion.

Accepted Answer

We reject H₀,because t_b₁ = 4.00 and p-value = .0103 < .05.Thus,we conclude that there is sufficient evidence that dollars spent on advertising is a useful linear predictor of the grocery store sales.

Question 4

A data set with 7 observations yielded the following.Use the simple linear regression model.

Accepted Answer

\[\begin{array} { l } 
\sum X = 21.57 \

Question 5

In simple regression analysis,the quantity that gives the amount by which Y (dependent variable)changes for a unit change in X (independent variable)is called the:

Accepted Answer

A) Coefficient of determination. 
B) Slope of the regression line. 
C) Y-intercept of the regression line. 
D) Correlation coefficient. 
E) Standard error. 
A) Coefficient of determination. 
B) Slope of the regression line. 
C) Y-intercept of the regression line. 
D) Correlation coefficient. 
E) Standard error.

Question 6

After plotting the data points on a scatter diagram,we have observed an inverse relationship between the independent variable (X)and the dependent variable (Y).Therefore,we can expect both the sample ___________ and the sample _____________ to be negative values.

Accepted Answer

A) Intercept,slope 
B) Slope,coefficient of determination 
C) Intercept,correlation coefficient 
D) Slope,correlation coefficient 
E) Slope,standard error of estimate 
A) Intercept,slope 
B) Slope,coefficient of determination 
C) Intercept,correlation coefficient 
D) Slope,correlation coefficient 
E) Slope,standard error of estimate

Question 7

Regression Analysis
  
The local grocery store wants to predict its daily sales in dollars.The manager believes that the amount of newspaper advertising significantly affects the store's sales.He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars)and advertising expenditures (in thousands of dollars).The Excel/MegaStat output given above summarizes the results of the regression model.
What are the limits of the 99 percent prediction interval of the daily sales in dollars of an individual grocery store that has spent $3000 on advertising expenditures?

Accepted Answer

The distance value for this particular p

Question 8

The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.

Accepted Answer

A) True 
 B)False

Question 9

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

\[\begin{array} { l l l l l } 
\text { P

Question 10

A data set with 7 observations yielded the following.Use the simple linear regression model.

Accepted Answer

\[\begin{array} { l } 
\sum X = 21.57 \

Question 11

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

\[\begin{array} { l l l l l } 
\text { P

Question 12

The range for r2 is between 0 and 1,and the range for r is between ____________.

Accepted Answer

A) 0 and 1 
B) -1 and 1 
C) -1 and 0 
D) no limit 
A) 0 and 1 
B) -1 and 1 
C) -1 and 0 
D) no limit

Question 13

If the Durbin-Watson statistic is less than dL,then we conclude that:

Accepted Answer

A) There is significant positive autocorrelation. 
B) There is significant negative autocorrelation. 
C) There is significant autocorrelation,but we cannot identify whether it is positive or negative. 
D) The test results are inconclusive. 
A) There is significant positive autocorrelation. 
B) There is significant negative autocorrelation. 
C) There is significant autocorrelation,but we cannot identify whether it is positive or negative. 
D) The test results are inconclusive.

Question 14

The _____ distribution is used for testing the significance of the slope term.

Accepted Answer

A) t 
B) z 
C) r 
D) r2 
A) t 
B) z 
C) r 
D) r2

Question 15

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The sample size consists of 10 metal sheets.The simple linear regression equation is

Accepted Answer

@#LAT-DLM& 
The time is in minutes and the strengt

Question 16

The least squares point estimates of the simple linear regression model minimize the ____________.

Accepted Answer

A) SS Error 
B) Total variance 
C) MS Error 
D) Explained variance 
A) SS Error 
B) Total variance 
C) MS Error 
D) Explained variance

Question 17

In simple regression analysis,r2 is a percentage measure and measures the proportion of the variation explained by the simple linear regression model.

Accepted Answer

A) True 
 B)False

Question 18

Consider the following partial computer output from a simple linear regression analysis.

Accepted Answer

\[\begin{array} { l l l l l } 
\text { P

Question 19

The following results were obtained from a simple regression analysis:
Ŷ = 37.2895 - 1.2024X
r2 = .6744 sb = .2934
When X (independent variable)is equal to zero,what is the estimated value of Y (dependent variable)?

Accepted Answer

37.2895
Feedback:In

Question 20

In simple linear regression analysis,we assume that the variance of the independent variable (X)is equal to the variance of the dependent variable (Y).

Accepted Answer

A) True 
 B)False

The dependent variable is the variable that is being described,predicted,or controlled.

Consider the following partial computer output from a simple linear regression analysis.

A data set with 7 observations yielded the following.Use the simple linear regression model.

In simple regression analysis,the quantity that gives the amount by which Y (dependent variable)changes for a unit change in X (independent variable)is called the:

After plotting the data points on a scatter diagram,we have observed an inverse relationship between the independent variable (X)and the dependent variable (Y).Therefore,we can expect both the sample _ and the sample ___ to be negative values.

The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.

Consider the following partial computer output from a simple linear regression analysis.

A data set with 7 observations yielded the following.Use the simple linear regression model.

Consider the following partial computer output from a simple linear regression analysis.

The range for r² is between 0 and 1,and the range for r is between ____________.

If the Durbin-Watson statistic is less than d_L,then we conclude that:

The _____ distribution is used for testing the significance of the slope term.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The sample size consists of 10 metal sheets.The simple linear regression equation is

The least squares point estimates of the simple linear regression model minimize the ____________.

In simple regression analysis,r² is a percentage measure and measures the proportion of the variation explained by the simple linear regression model.

Consider the following partial computer output from a simple linear regression analysis.

The following results were obtained from a simple regression analysis: Ŷ = 37.2895 - 1.2024X r² = .6744 s_b = .2934 When X (independent variable)is equal to zero,what is the estimated value of Y (dependent variable)?

In simple linear regression analysis,we assume that the variance of the independent variable (X)is equal to the variance of the dependent variable (Y).

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 14: Simple Linear Regression Analysis

The dependent variable is the variable that is being described,predicted,or controlled.

Consider the following partial computer output from a simple linear regression analysis.

A data set with 7 observations yielded the following.Use the simple linear regression model.

In simple regression analysis,the quantity that gives the amount by which Y (dependent variable)changes for a unit change in X (independent variable)is called the:

After plotting the data points on a scatter diagram,we have observed an inverse relationship between the independent variable (X)and the dependent variable (Y).Therefore,we can expect both the sample ___________ and the sample _____________ to be negative values.

The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.

Consider the following partial computer output from a simple linear regression analysis.

A data set with 7 observations yielded the following.Use the simple linear regression model.

Consider the following partial computer output from a simple linear regression analysis.

The range for r2 is between 0 and 1,and the range for r is between ____________.

If the Durbin-Watson statistic is less than dL,then we conclude that:

The _____ distribution is used for testing the significance of the slope term.

An experiment was performed on a certain metal to determine if the strength is a function of heating time.The sample size consists of 10 metal sheets.The simple linear regression equation is

The least squares point estimates of the simple linear regression model minimize the ____________.

In simple regression analysis,r2 is a percentage measure and measures the proportion of the variation explained by the simple linear regression model.

Consider the following partial computer output from a simple linear regression analysis.

The following results were obtained from a simple regression analysis: Ŷ = 37.2895 - 1.2024X r2 = .6744 sb = .2934 When X (independent variable)is equal to zero,what is the estimated value of Y (dependent variable)?

In simple linear regression analysis,we assume that the variance of the independent variable (X)is equal to the variance of the dependent variable (Y).

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

After plotting the data points on a scatter diagram,we have observed an inverse relationship between the independent variable (X)and the dependent variable (Y).Therefore,we can expect both the sample _ and the sample ___ to be negative values.

The range for r² is between 0 and 1,and the range for r is between ____________.

If the Durbin-Watson statistic is less than d_L,then we conclude that:

In simple regression analysis,r² is a percentage measure and measures the proportion of the variation explained by the simple linear regression model.

The following results were obtained from a simple regression analysis: Ŷ = 37.2895 - 1.2024X r² = .6744 s_b = .2934 When X (independent variable)is equal to zero,what is the estimated value of Y (dependent variable)?