A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function: $\hat { y }$ = 7 - 3x1 + 5x2 For this model, SSR = 3500, SSE = 1500, and the sample size is 18.If we want to test for the significance of the regression model, the critical value of F at the 5% level of significance 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.

Below you are given a partial computer output from a multiple regression analysis based on a sample of 16 observations. \[\begin{array}{l} \begin{array} { l l } \text { Coefficients } & \text { Standard Error } \\ 12.924 & 4.425 \\ - 3.682 & 2.630 \\ 45.216 & 12.560 \end{array}\\ \text { Analysis of Variance }\\ \begin{array} { l l l l l } \text { Source of } & \text { Degrees of } & \text { Sum of } & \text { Mean } \\ \text { Variation } & \text { Freedom } & \text { Squares } & \text { Square } \end{array} \quad F \end{array}\] The test statistic used to determine if there is a relationship among the variables equals

A) 1.40. B) .2. C) .77. D) 5. A) 1.40. B) .2. C) .77. D) 5.

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x1 - 3x2 + 8x3 + 8x4 For this model, SSR = 700 and SSE = 100.The multiple coefficient of determination for the above model is

A) .934. B) .875. C) .125. D) .144. A) .934. B) .875. C) .125. D) .144.

The following estimated regression equation was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female). $\hat { y }$ = 30 + .7x1 + 3x2 Also provided are SST = 1200 and SSE = 384.The test statistic for testing the significance of the model is

A) .73. B) 1.47. C) 28.69. D) 5.22. A) .73. B) 1.47. C) 28.69. D) 5.22.

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. \[\begin{array} { c l l } & \text { Coefficients } & \text { Standard Error } \\ \text { Intercept } & 40.00 & 7.00 \\ \mathrm { x } _ { 1 } & 8.00 & 2.50 \\ \mathrm { x } _ { 2 } & 6.00 & 3.00 \end{array}\] a. If the company uses $40,000 in advertisement and has 30 salespeople, what are the expected sales? Give your answer in dollars. b. At α = .05, test for the significance of the coefficient of advertising. c. At α = .05, test for the significance of the coefficient of the number of salespeople.

a. $540,000,000 b. t = 3.2 > critical

Below you are given a partial computer output from a multiple regression analysis based on a sample of 16 observations. \[\begin{array}{l} \begin{array} { l l } \text { Coefficients } & \text { Standard Error } \\ 12.924 & 4.425 \\ - 3.682 & 2.630 \\ 45.216 & 12.560 \end{array}\\ \text { Analysis of Variance }\\ \begin{array} { l l l l l } \text { Source of } & \text { Degrees of } & \text { Sum of } & \text { Mean } \\ \text { Variation } & \text { Freedom } & \text { Squares } & \text { Square } \end{array} \quad F \end{array}\] We want to test whether the parameter $\beta$1 is significant.The test statistic equals

A) -1.4. B) 1.4. C) 3.6. D) -5.0. A) -1.4. B) 1.4. C) 3.6. D) -5.0.

The following estimated regression equation was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female). $\hat { y }$ = 30 + .7x1 + 3x2 Also provided are SST = 1200 and SSE = 384.The multiple coefficient of determination is

A) .32. B) .42. C) .68. D) .50. A) .32. B) .42. C) .68. D) .50.

A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function: $\hat { y }$ = 7 - 3x1 + 5x2 For this model, SSR = 3500, SSE = 1500, and the sample size is 18.The adjusted multiple coefficient of determination for this problem is

A) .70. B) .8367. C) .66. D) .2289. A) .70. B) .8367. C) .66. D) .2289.

Exam 15: Multiple Regression

A regression model involving 8 independent variables for a sample of 69 observations resulted in the following sum of squares. =306 =1800 a. Compute the multiple coefficient of determination. b. At α = .05, test to determine whether or not the model is significant.

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Question 61

A regression model between sales (y in $1000), unit price (x₁ in dollars), and television advertisement (x₂ in dollars) resulted in the following function: $\hat { y }$ = 7 - 3x₁ + 5x₂ For this model, SSR = 3500, SSE = 1500, and the sample size is 18.If we want to test for the significance of the regression model, the critical value of F at the 5% level of significance is?

(Multiple Choice)

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Question 62

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 The test statistic obtained from the information provided is

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Question 63

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 The multiple coefficient of determination is

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Question 64

The multiple coefficient of determination is

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Question 65

Below you are given a partial computer output from a multiple regression analysis based on a sample of 16 observations. Coefficients Standard Error 12.924 4.425 -3.682 2.630 45.216 12.560 Analysis of Variance Source of Degrees of Sum of Mean Variation Freedom Squares Square F The test statistic used to determine if there is a relationship among the variables equals

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Question 66

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model, SSR = 700 and SSE = 100.The multiple coefficient of determination for the above model is

(Multiple Choice)

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Question 67

In order to test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

(Multiple Choice)

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Question 68

The following estimated regression equation was developed relating yearly income (y in $1000s) of 30 individuals with their age (x₁) and their gender (x₂) (0 if male and 1 if female). $\hat { y }$ = 30 + .7x₁ + 3x₂ Also provided are SST = 1200 and SSE = 384.The test statistic for testing the significance of the model is

(Multiple Choice)

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Question 69

In logistic regression,

(Multiple Choice)

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Question 70

A multiple regression model has

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Question 71

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. Coefficients Standard Error Intercept 40.00 7.00 8.00 2.50 6.00 3.00 a. If the company uses $40,000 in advertisement and has 30 salespeople, what are the expected sales? Give your answer in dollars. b. At α = .05, test for the significance of the coefficient of advertising. c. At α = .05, test for the significance of the coefficient of the number of salespeople.

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Question 72

A regression analysis involved 6 independent variables and 27 observations.The critical value of t for testing the significance of each of the independent variable's coefficients will have

(Multiple Choice)

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Question 73

Below you are given a partial computer output from a multiple regression analysis based on a sample of 16 observations. Coefficients Standard Error 12.924 4.425 -3.682 2.630 45.216 12.560 Analysis of Variance Source of Degrees of Sum of Mean Variation Freedom Squares Square F We want to test whether the parameter $\beta$ ₁ is significant.The test statistic equals

(Multiple Choice)

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Question 74

In a multiple regression analysis, SSR = 1000 and SSE = 200.The F statistic for this model is

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Question 75

The following estimated regression equation was developed relating yearly income (y in $1000s) of 30 individuals with their age (x₁) and their gender (x₂) (0 if male and 1 if female). $\hat { y }$ = 30 + .7x₁ + 3x₂ Also provided are SST = 1200 and SSE = 384.The multiple coefficient of determination is

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Question 76

A regression model between sales (y in $1000), unit price (x₁ in dollars), and television advertisement (x₂ in dollars) resulted in the following function: $\hat { y }$ = 7 - 3x₁ + 5x₂ For this model, SSR = 3500, SSE = 1500, and the sample size is 18.The adjusted multiple coefficient of determination for this problem is

(Multiple Choice)

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Question 77

In order to test for the significance of a regression model involving 4 independent variables and 36 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

(Multiple Choice)

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Question 78

In a multiple regression analysis involving 12 independent variables and 166 observations, SSR = 878 and SSE = 122.The multiple coefficient of determination is

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Question 79

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model, SSR = 700 and SSE = 100.The critical F value at $\alpha$ = .05 is

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Question 80

Showing 61 - 80 of 113

A regression model involving 8 independent variables for a sample of 69 observations resulted in the following sum of squares. =306 =1800 a. Compute the multiple coefficient of determination. b. At α = .05, test to determine whether or not the model is significant.

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 The test statistic obtained from the information provided is

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 The multiple coefficient of determination is

The multiple coefficient of determination is

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model, SSR = 700 and SSE = 100.The multiple coefficient of determination for the above model is

In order to test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

In logistic regression,

A multiple regression model has

A regression analysis involved 6 independent variables and 27 observations.The critical value of t for testing the significance of each of the independent variable's coefficients will have

In a multiple regression analysis, SSR = 1000 and SSE = 200.The F statistic for this model is

In order to test for the significance of a regression model involving 4 independent variables and 36 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

In a multiple regression analysis involving 12 independent variables and 166 observations, SSR = 878 and SSE = 122.The multiple coefficient of determination is

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model, SSR = 700 and SSE = 100.The critical F value at $\alpha$ = .05 is

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Exam 15: Multiple Regression

A regression model involving 8 independent variables for a sample of 69 observations resulted in the following sum of squares. =306 =1800 ​ a. Compute the multiple coefficient of determination. b. At α = .05, test to determine whether or not the model is significant.

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 ​ The test statistic obtained from the information provided is

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 ​ The multiple coefficient of determination is

The multiple coefficient of determination is

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: y^\hat { y }y^​ = 17 + 4x1 - 3x2 + 8x3 + 8x4 For this model, SSR = 700 and SSE = 100.The multiple coefficient of determination for the above model is

In order to test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

In logistic regression,

A multiple regression model has

A regression analysis involved 6 independent variables and 27 observations.The critical value of t for testing the significance of each of the independent variable's coefficients will have

In a multiple regression analysis, SSR = 1000 and SSE = 200.The F statistic for this model is

In order to test for the significance of a regression model involving 4 independent variables and 36 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

In a multiple regression analysis involving 12 independent variables and 166 observations, SSR = 878 and SSE = 122.The multiple coefficient of determination is

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: y^\hat { y }y^​ = 17 + 4x1 - 3x2 + 8x3 + 8x4 For this model, SSR = 700 and SSE = 100.The critical F value at α\alphaα = .05 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

Simple Linear Regression

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A regression model involving 8 independent variables for a sample of 69 observations resulted in the following sum of squares. =306 =1800 a. Compute the multiple coefficient of determination. b. At α = .05, test to determine whether or not the model is significant.

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 The test statistic obtained from the information provided is

A regression model involving 4 independent variables and a sample of 15 observations resulted in the following sum of squares. SSR = 165 SSE = 60 The multiple coefficient of determination is

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model, SSR = 700 and SSE = 100.The multiple coefficient of determination for the above model is

In a multiple regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { y }$ = 17 + 4x₁ - 3x₂ + 8x₃ + 8x₄ For this model, SSR = 700 and SSE = 100.The critical F value at $\alpha$ = .05 is