Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4xS1U1B11S1U1B0 - 3xS1U1B12S1U1B0 + 8xS1U1B13S1U1B0 + 8xS1U1B14S1U1B0 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

A) model is not significant B) model is significant C) slope of x1 is significant D) slope of x2 is significant A) model is not significant B) model is significant C) slope of x1 is significant D) slope of x2 is significant

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 gives the estimated regression line?

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

A regression was performed on a sample of 16 observations. The estimated equation is = 23.5 - 14.28x1 + 6.72x2 + 15.68x3. The standard errors for the coefficients are Sb1 = 4.2, Sb2 = 5.6, and Sb3 = 2.8. For this model, SST = 3809.6 and SSR = 3285.4. a.Compute the appropriate t ratios. b.Test for the significance of F1F1F1S1F1F1F101, F1F1F1S1F1F1F102, and F1F1F1S1F1F1F103 at the 5% level of significance. c.Do you think that any of the variables should be dropped from the model? Explain. d.Compute R2 and Ra2. Interpret R2. e.Test the significance of the relationship among the variables at the 5% level of significance.

a.t 1 = -3.4, t 2 = 1.2, t 3 = 5.6 b.t .025 = 2.179

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4xS1U1B11S1U1B0 - 3xS1U1B12S1U1B0 + 8xS1U1B13S1U1B0 + 8xS1U1B14S1U1B0 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The computed F statistic for testing the significance of the above model is

A) 43.75 B) 0.875 C) 50.19 D) 7.00 A) 43.75 B) 0.875 C) 50.19 D) 7.00

Exhibit 13-2 A regression model between sales (y in $1,000), unit price (xS1U1B11S1U1B0 in dollars) and television advertisement (xS1U1B12S1U1B0 in dollars) resulted in the following function: = 7 - 3xS1U1B11S1U1B0 + 5xS1U1B12S1U1B0 For this model SSR = 3500, SSE = 1500, and the sample size is 18. -Refer to Exhibit 13-2. The coefficient of x2 indicates that if television advertising is increased by $1 (holding the unit price constant), sales are expected to

A) increase by $5 B) increase by $12,000 C) increase by $5,000 D) decrease by $2,000 A) increase by $5 B) increase by $12,000 C) increase by $5,000 D) decrease by $2,000

Exhibit 13-2 A regression model between sales (y in $1,000), unit price (xS1U1B11S1U1B0 in dollars) and television advertisement (xS1U1B12S1U1B0 in dollars) resulted in the following function: = 7 - 3xS1U1B11S1U1B0 + 5xS1U1B12S1U1B0 For this model SSR = 3500, SSE = 1500, and the sample size is 18. -Refer to Exhibit 13-2. If we want to test for the significance of the regression model, the critical value of F at 95% confidence is

A) 3.68 B) 3.29 C) 3.24 D) 4.54 A) 3.68 B) 3.29 C) 3.24 D) 4.54

Exam 13: Multiple Regression

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

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Question 21

The numerical value of the coefficient of determination

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Question 22

The following regression model has been proposed to predict monthly sales at a shoe store. = 40 - 3x₁ + 12x₂ + 10x₃ where x₁ = competitor's previous month's sales (in $1,000s) x₂ = Stores previous month's sales (in $1,000s) = sales (in $1000s) a.Predict sales (in dollars) for the shoe store if the competitor's previous month's sales were $9,000, the store's previous month's sales were $30,000, and no radio advertisements were run. b.Predict sales (in dollars) for the shoe store if the competitor's previous month's sales were $9,000, the store's previous month's sales were $30,000, and 10 radio advertisements were run.

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Question 23

Below you are given a partial ANOVA table relating the price of a company's stock (y in dollars), the Dow Jones industrial average (x₁), and the stock price of the company's major competitor (x₂ in dollars). a.What has been the sample size for this regression analysis? b.At  = 0.05 level of significance, test to determine if the model is significant. That is, determine if there exists a significant relationship between the independent variables and the dependent variable. c.Determine the multiple coefficient of determination.

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Question 24

In regression analysis, an outlier is an observation whose

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Question 25

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 gives the estimated regression line?

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Question 26

The correct relationship between SST, SSR, and SSE is given by

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Question 27

In a residual plot that does not suggest we should challenge the assumptions of our regression model, we would expect to see

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Question 28

A student used multiple regression analysis to study how family spending (y) is influenced by income (x₁), family size (x₂), and additions to savings (x₃). The variables y, x₁, and x₃ are measured in thousands of dollars. The following results were obtained. Coefficient of determination = 0.946 a.Write out the estimated regression equation for the relationship between the variables. b.What can you say about the strength of this relationship? c.Carry out a test of whether y is significantly related to the independent variables. Use a .05 level of significance. d.Carry out a test to see if x₃ and y are significantly related. Use a .05 level of significance. e.Why would a coefficient of determination very close to 1.0 be expected here?

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Question 29

A measure of goodness of fit for the estimated regression equation is the

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Question 30

A regression was performed on a sample of 16 observations. The estimated equation is = 23.5 - 14.28x₁ + 6.72x₂ + 15.68x₃. The standard errors for the coefficients are S_b1 = 4.2, S_b2 = 5.6, and S_b3 = 2.8. For this model, SST = 3809.6 and SSR = 3285.4. a.Compute the appropriate t ratios. b.Test for the significance of ₁, ₂, and ₃ at the 5% level of significance. c.Do you think that any of the variables should be dropped from the model? Explain. d.Compute R² and R_a². Interpret R². e.Test the significance of the relationship among the variables at the 5% level of significance.

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Question 31

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The computed F statistic for testing the significance of the above model is

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Question 32

In order to test for the significance of a regression model involving 14 independent variables and 255 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

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Question 33

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called

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Question 34

Exhibit 13-2 A regression model between sales (y in $1,000), unit price (x₁ in dollars) and television advertisement (x₂ in dollars) resulted in the following function: = 7 - 3x₁ + 5x₂ For this model SSR = 3500, SSE = 1500, and the sample size is 18. -Refer to Exhibit 13-2. The coefficient of x₂ indicates that if television advertising is increased by $1 (holding the unit price constant), sales are expected to

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Question 35

Exhibit 13-2 A regression model between sales (y in $1,000), unit price (x₁ in dollars) and television advertisement (x₂ in dollars) resulted in the following function: = 7 - 3x₁ + 5x₂ For this model SSR = 3500, SSE = 1500, and the sample size is 18. -Refer to Exhibit 13-2. If we want to test for the significance of the regression model, the critical value of F at 95% confidence is

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Question 36

A regression model involving 8 independent variables for a sample of 69 periods resulted in the following sum of squares. SSE = 306 SST = 1800 a.Compute the coefficient of determination. b.At  = 0.05, test to determine whether or not the model is significant.

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Question 37

The following regression model has been proposed to predict sales at a fast food outlet. = 18 - 2x₁ + 7x₂ + 15x₃ where x₁ = the number of competitors within 1 mile x₂ = the population within 1 mile (in 1,000s) x₃ = 1 if drive-up windows are present, 0 otherwise = sales (in $1,000s) a.What is the interpretation of 15 (the coefficient of x₃) in the regression equation? b.Predict sales for a store with 2 competitors, a population of 10,000 within one mile, and one drive-up window (give the answer in dollars). c.Predict sales for the store with 2 competitors, a population of 10,000 within one mile, and no drive-up window (give the answer in dollars).

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Question 38

In order to determine whether or not the number of automobiles sold per day (y) is related to price (x₁ in $1,000), and the number of advertising spots (x₂), data were gathered for 7 days. Part of the Excel output is shown below. a.Determine the least squares regression function relating y to x₁ and x₂. b.If the company charges $20,000 for each car and uses 10 advertising spots, how many cars would you expect them to sell in a day? c.At  = 0.05, test to determine if the fitted equation developed in Part a represents a significant relationship between the independent variables and the dependent variable. d.At  = 0.05, test to see if ₁ is significantly different from zero. e.Determine the multiple coefficient of determination.

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Question 39

The following is part of the results of a regression analysis involving sales (y in millions of dollars), advertising expenditures (x₁ in thousands of dollars), and number of salespeople (x₂) for a corporation. The regression was performed on a sample of 10 observations. a.Write the regression equation. b.Interpret the coefficients of the estimated regression equation found in Part (a). c.At  =0.05, test for the significance of the coefficient of advertising. d.At  =0.05, test for the significance of the coefficient of number of salespeople. e.If the company uses $50,000 in advertisement and has 800 salespersons, what are the expected sales? Give your answer in dollars.

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Question 40

Showing 21 - 40 of 111

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

The numerical value of the coefficient of determination

In regression analysis, an outlier is an observation whose

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 gives the estimated regression line?

The correct relationship between SST, SSR, and SSE is given by

In a residual plot that does not suggest we should challenge the assumptions of our regression model, we would expect to see

A measure of goodness of fit for the estimated regression equation is the

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The computed F statistic for testing the significance of the above model is

In order to test for the significance of a regression model involving 14 independent variables and 255 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called

A regression model involving 8 independent variables for a sample of 69 periods resulted in the following sum of squares. SSE = 306 SST = 1800 a.Compute the coefficient of determination. b.At  = 0.05, test to determine whether or not the model is significant.

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

Exam 13: Multiple Regression

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x1 - 3x2 + 8x3 + 8x4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

The numerical value of the coefficient of determination

In regression analysis, an outlier is an observation whose

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 gives the estimated regression line?

The correct relationship between SST, SSR, and SSE is given by

In a residual plot that does not suggest we should challenge the assumptions of our regression model, we would expect to see

A measure of goodness of fit for the estimated regression equation is the

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x1 - 3x2 + 8x3 + 8x4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The computed F statistic for testing the significance of the above model is

In order to test for the significance of a regression model involving 14 independent variables and 255 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called

A regression model involving 8 independent variables for a sample of 69 periods resulted in the following sum of squares. SSE = 306 SST = 1800 a.Compute the coefficient of determination. b.At  = 0.05, test to determine whether or not the model is significant.

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

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

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 gives the estimated regression line?

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The computed F statistic for testing the significance of the above model is