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An investment analyst wants to examine the relationship between a mutual fund's return, its turnover rate, and its expense ratio. She randomly selects 10 mutual funds and estimates: Return = β0 + β1Turnover + β2Expense + ε, where Return is the average five-year return An investment analyst wants to examine the relationship between a mutual fund's return, its turnover rate, and its expense ratio. She randomly selects 10 mutual funds and estimates: Return = β<sub>0</sub> + β<sub>1</sub>Turnover + β<sub>2</sub>Expense + ε, where Return is the average five-year return , Turnover is the annual holdings turnover (in %), Expense is the annual expense ratio (in %), and ε is the random error component. A portion of the regression results is shown in the accompanying table. a. Predict the return for a mutual fund that has an annual holdings turnover of 60% and an annual expense ratio of 1.5%. B) Interpret the slope coefficient for the variable Expense. C) Calculate the standard error of the estimate. D) Calculate and interpret the coefficient of determination. , Turnover is the annual holdings turnover (in %), Expense is the annual expense ratio (in %), and ε is the random error component. A portion of the regression results is shown in the accompanying table. An investment analyst wants to examine the relationship between a mutual fund's return, its turnover rate, and its expense ratio. She randomly selects 10 mutual funds and estimates: Return = β<sub>0</sub> + β<sub>1</sub>Turnover + β<sub>2</sub>Expense + ε, where Return is the average five-year return , Turnover is the annual holdings turnover (in %), Expense is the annual expense ratio (in %), and ε is the random error component. A portion of the regression results is shown in the accompanying table. a. Predict the return for a mutual fund that has an annual holdings turnover of 60% and an annual expense ratio of 1.5%. B) Interpret the slope coefficient for the variable Expense. C) Calculate the standard error of the estimate. D) Calculate and interpret the coefficient of determination. a. Predict the return for a mutual fund that has an annual holdings turnover of 60% and an annual expense ratio of 1.5%. B) Interpret the slope coefficient for the variable Expense. C) Calculate the standard error of the estimate. D) Calculate and interpret the coefficient of determination.

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a. 39.75%
b. If the expense ratio goes u...

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A manager at a local bank analyzed the relationship between monthly salary (y, in $) and length of service (x, measured in months) for 30 employees. She estimates the model: Salary = β0 + β1 Service + ε. The following ANOVA table summarizes a portion of the regression results. A manager at a local bank analyzed the relationship between monthly salary (y, in $) and length of service (x, measured in months) for 30 employees. She estimates the model: Salary = β<sub>0</sub> + β<sub>1</sub> Service + ε. The following ANOVA table summarizes a portion of the regression results. How much of the variation in Salary is unexplained by the sample regression equation? A) 1% B) 2% C) 18.39% D) 77.94% How much of the variation in Salary is unexplained by the sample regression equation?


A) 1%
B) 2%
C) 18.39%
D) 77.94%

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A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $) , the number of bedrooms (x1) , the number of bathrooms (x2) , and its square footage (x3) . She estimates the following model as Rent = β0 + β1Bedroom + β2Bath + β3Sqft + ε. The following ANOVA table shows a portion of the regression results. A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $) , the number of bedrooms (x<sub>1</sub>) , the number of bathrooms (x<sub>2</sub>) , and its square footage (x<sub>3</sub>) . She estimates the following model as Rent = β<sub>0</sub> + β<sub>1</sub>Bedroom + β<sub>2</sub>Bath + β<sub>3</sub>Sqft + ε. The following ANOVA table shows a portion of the regression results. The coefficient of determination indicates that ________. A) 19.08% of the variation in Rent is explained by the sample regression equation B) 19.08% of the variation in square footage is explained by the sample regression equation C) 80.92% of the variation in Rent is explained by the sample regression equation D) 80.92% of the variation in square footage is explained by the sample regression equation The coefficient of determination indicates that ________.


A) 19.08% of the variation in Rent is explained by the sample regression equation
B) 19.08% of the variation in square footage is explained by the sample regression equation
C) 80.92% of the variation in Rent is explained by the sample regression equation
D) 80.92% of the variation in square footage is explained by the sample regression equation

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Given the augmented Phillips model: y = β0 + β1x1 + β2x2 + ε, where y = actual rate of inflation (%) , x1 = unemployment rate (%) , and x2 = anticipated inflation rate (%) . The response variable or variables in this model is (are) the ________.


A) unemployment rate
B) actual inflation rate
C) anticipated inflation rate
D) unemployment rate and anticipated inflation rate

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The following ANOVA table was obtained when estimating a multiple regression model. The following ANOVA table was obtained when estimating a multiple regression model. a. Calculate the standard error of the estimate. B) Calculate the coefficient of determination. C) Calculate adjusted R<sup>2</sup>. a. Calculate the standard error of the estimate. B) Calculate the coefficient of determination. C) Calculate adjusted R2.

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a. se = 1.7...

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When estimating When estimating = b<sub>0</sub> + b<sub>1</sub>x<sub>1</sub> + b<sub>2</sub>x<sub>2</sub>, the following regression results using ANOVA were obtained. Which of the following is the prediction of , if x<sub>1</sub> = 1 and x<sub>2</sub> = 2? A) −1.9 B) −0.3 C) 1.3 D) 1.9 = b0 + b1x1 + b2x2, the following regression results using ANOVA were obtained. When estimating = b<sub>0</sub> + b<sub>1</sub>x<sub>1</sub> + b<sub>2</sub>x<sub>2</sub>, the following regression results using ANOVA were obtained. Which of the following is the prediction of , if x<sub>1</sub> = 1 and x<sub>2</sub> = 2? A) −1.9 B) −0.3 C) 1.3 D) 1.9 Which of the following is the prediction of When estimating = b<sub>0</sub> + b<sub>1</sub>x<sub>1</sub> + b<sub>2</sub>x<sub>2</sub>, the following regression results using ANOVA were obtained. Which of the following is the prediction of , if x<sub>1</sub> = 1 and x<sub>2</sub> = 2? A) −1.9 B) −0.3 C) 1.3 D) 1.9 , if x1 = 1 and x2 = 2?


A) −1.9
B) −0.3
C) 1.3
D) 1.9

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The correlation coefficient can only range between 0 and 1.

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When estimating When estimating = β<sub>0</sub> + β<sub>1</sub>x<sub>1</sub> + β<sub>2</sub>x<sub>2 </sub>+<sub> </sub>ε, the following regression results using ANOVA were obtained. Which of the following is the coefficient of determination? A) 0.07 B) 0.10 C) 0.90 D) 0.93 = β0 + β1x1 + β2x2 + ε, the following regression results using ANOVA were obtained. When estimating = β<sub>0</sub> + β<sub>1</sub>x<sub>1</sub> + β<sub>2</sub>x<sub>2 </sub>+<sub> </sub>ε, the following regression results using ANOVA were obtained. Which of the following is the coefficient of determination? A) 0.07 B) 0.10 C) 0.90 D) 0.93 Which of the following is the coefficient of determination?


A) 0.07
B) 0.10
C) 0.90
D) 0.93

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Over the past 30 years, the sample standard deviations of the rates of return for stock X and Stock Y were 0.20 and 0.12, respectively. The sample covariance between the returns of X and Y is 0.0096. The correlation of the rates of return between X and Y is the closest to ________.


A) 0.20
B) 0.24
C) 0.36
D) 0.40

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A sample regression equation is given by A sample regression equation is given by = 155 - 34x<sub>1</sub> - 12x<sub>2. </sub>If x<sub>1 </sub>= 3 and x<sub>2 </sub>= 2, the predicted value of y would be ________. A) 29 B) 77 C) 233 D) 281 = 155 - 34x1 - 12x2. If x1 = 3 and x2 = 2, the predicted value of y would be ________.


A) 29
B) 77
C) 233
D) 281

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The covariance and correlation coefficient are measures that quantify the non-linear relationship between two variables.

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A multiple regression model with two explanatory variables is estimated using 20 observations resulting in SSE = 550 and SST = 1000. Which of the following is the correct value of R2?


A) 0.10
B) 0.45
C) 0.55
D) 0.90

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A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $) , the number of bedrooms (x1) , the number of bathrooms (x2) , and its square footage (x3) . She estimates the following model as Rent = β0 + β1Bedroom + β2Bath + β3Sqft + ε. The following ANOVA table shows a portion of the regression results. A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $) , the number of bedrooms (x<sub>1</sub>) , the number of bathrooms (x<sub>2</sub>) , and its square footage (x<sub>3</sub>) . She estimates the following model as Rent = β<sub>0</sub> + β<sub>1</sub>Bedroom + β<sub>2</sub>Bath + β<sub>3</sub>Sqft + ε. The following ANOVA table shows a portion of the regression results. Which of the following would be the rent for a 1,000-square-foot apartment that has two bedrooms and two bathrooms? A) $840 B) $1,130 C) $1,260 D) $1,335 Which of the following would be the rent for a 1,000-square-foot apartment that has two bedrooms and two bathrooms?


A) $840
B) $1,130
C) $1,260
D) $1,335

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The following portion of regression results was obtained when estimating a simple linear regression model. The following portion of regression results was obtained when estimating a simple linear regression model. a. What is the sample regression equation? B) Interpret the slope coefficient for x<sub>1</sub>. C) Find the predicted value for y if x<sub>1</sub> equals 200. D) Fill in the missing values A and B in the ANOVA table. E) Calculate the standard error of the estimate. F) Calculate R<sup>2</sup>. a. What is the sample regression equation? B) Interpret the slope coefficient for x1. C) Find the predicted value for y if x1 equals 200. D) Fill in the missing values A and B in the ANOVA table. E) Calculate the standard error of the estimate. F) Calculate R2.

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a. blured image = 80.30 - 0.28x
b. As x1 in...

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A statistics instructor wants to examine the relationship between the hours a student spends studying for the final exam (Hours) and a student's grade on the final exam (Grade). She takes a sample of five students. A statistics instructor wants to examine the relationship between the hours a student spends studying for the final exam (Hours) and a student's grade on the final exam (Grade). She takes a sample of five students. a. Compute the sample correlation coefficient. B) Specify the competing hypotheses to determine whether the hours spent studying and the final grade are correlated. C) Calculate the value of the test statistic and approximate the corresponding p-value. D) At the 10% significance level, what is the conclusion to the test? Explain. a. Compute the sample correlation coefficient. B) Specify the competing hypotheses to determine whether the hours spent studying and the final grade are correlated. C) Calculate the value of the test statistic and approximate the corresponding p-value. D) At the 10% significance level, what is the conclusion to the test? Explain.

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a. rxy = 0.92
b. H0: ρxy = 0; HA: ρxy ≠ 0.
c. t3 ...

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Consider the following simple linear regression model: y = β0 + β1x + ε. The random error term is ________.


A) y
B) x
C) ε
D) β0

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Consider the following data: Consider the following data: = 20, s<sub>x </sub>= 2, = −5, s<sub>y </sub>= 4, and b<sub>1</sub> = −0.8. Which of the following is the sample regression equation? A) = −21 − 0.80x B) = −21 + 0.80x C) = 11 − 0.80x D) = 11 + 0.80x = 20, sx = 2, Consider the following data: = 20, s<sub>x </sub>= 2, = −5, s<sub>y </sub>= 4, and b<sub>1</sub> = −0.8. Which of the following is the sample regression equation? A) = −21 − 0.80x B) = −21 + 0.80x C) = 11 − 0.80x D) = 11 + 0.80x = −5, sy = 4, and b1 = −0.8. Which of the following is the sample regression equation?


A) Consider the following data: = 20, s<sub>x </sub>= 2, = −5, s<sub>y </sub>= 4, and b<sub>1</sub> = −0.8. Which of the following is the sample regression equation? A) = −21 − 0.80x B) = −21 + 0.80x C) = 11 − 0.80x D) = 11 + 0.80x = −21 − 0.80x
B) Consider the following data: = 20, s<sub>x </sub>= 2, = −5, s<sub>y </sub>= 4, and b<sub>1</sub> = −0.8. Which of the following is the sample regression equation? A) = −21 − 0.80x B) = −21 + 0.80x C) = 11 − 0.80x D) = 11 + 0.80x = −21 + 0.80x
C) Consider the following data: = 20, s<sub>x </sub>= 2, = −5, s<sub>y </sub>= 4, and b<sub>1</sub> = −0.8. Which of the following is the sample regression equation? A) = −21 − 0.80x B) = −21 + 0.80x C) = 11 − 0.80x D) = 11 + 0.80x = 11 − 0.80x
D) Consider the following data: = 20, s<sub>x </sub>= 2, = −5, s<sub>y </sub>= 4, and b<sub>1</sub> = −0.8. Which of the following is the sample regression equation? A) = −21 − 0.80x B) = −21 + 0.80x C) = 11 − 0.80x D) = 11 + 0.80x = 11 + 0.80x

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Costco sells paperback books in their retail stores and wants to examine the relationship between the prices and sales. The price of a particular novel was adjusted each week and the weekly sales are in the following table. Management would like to use a simple linear regression model that uses prices to predict sales. Costco sells paperback books in their retail stores and wants to examine the relationship between the prices and sales. The price of a particular novel was adjusted each week and the weekly sales are in the following table. Management would like to use a simple linear regression model that uses prices to predict sales. The regression sum of squares for this sample is equal to ________. A) 4.17 B) 4.61 C) 5.16 D) 6.25 The regression sum of squares for this sample is equal to ________.


A) 4.17
B) 4.61
C) 5.16
D) 6.25

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Suppose a sample regression equation is given by Suppose a sample regression equation is given by = 11 − 0.80x. What is the predicted value of y and residual when x is 2 and y is observed to be 9? A) = 9.4, 0.4 B) = 9, -0.4 C) = 9, 0.4 D) - 9.4, -0.4 = 11 − 0.80x. What is the predicted value of y and residual when x is 2 and y is observed to be 9?


A) Suppose a sample regression equation is given by = 11 − 0.80x. What is the predicted value of y and residual when x is 2 and y is observed to be 9? A) = 9.4, 0.4 B) = 9, -0.4 C) = 9, 0.4 D) - 9.4, -0.4 = 9.4, 0.4
B) Suppose a sample regression equation is given by = 11 − 0.80x. What is the predicted value of y and residual when x is 2 and y is observed to be 9? A) = 9.4, 0.4 B) = 9, -0.4 C) = 9, 0.4 D) - 9.4, -0.4 = 9, -0.4
C) Suppose a sample regression equation is given by = 11 − 0.80x. What is the predicted value of y and residual when x is 2 and y is observed to be 9? A) = 9.4, 0.4 B) = 9, -0.4 C) = 9, 0.4 D) - 9.4, -0.4 = 9, 0.4
D) Suppose a sample regression equation is given by = 11 − 0.80x. What is the predicted value of y and residual when x is 2 and y is observed to be 9? A) = 9.4, 0.4 B) = 9, -0.4 C) = 9, 0.4 D) - 9.4, -0.4 - 9.4, -0.4

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The relationship between the response variable and the explanatory variables is ________ if the value of the response variable is uniquely determined by the explanatory variables.

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