Exam 12: Simple Linear Regression

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The Regression Sum of Squares (SSR)can never be greater than the Total Sum of Squares (SST).

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TABLE 12-1 A large national bank charges local companies for using their services. A bank official reported the results of a regression analysis designed to predict the bank's charges (Y) measured in dollars per month for services rendered to local companies. One independent variable used to predict service charges to a company is the company's sales revenue (X) measured in millions of dollars. Data for 21 companies who use the bank's services were used to fit the model: Y1 - β0 + β1X1 + εi The results of the simple linear regression are provided below. Y = -2,700 + 20 X, SYX = 65, two-tail p-value = 0.034 (for testing β1) -Referring to Table 12-1, interpret the p-value for testing whether β₁ exceeds 0.

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TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, what percentage of the variation in the amount of time needed can be explained by the variation in the number of invoices processed? Note: 4.3946E-15 is 4.3946 x 10-15. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, what percentage of the variation in the amount of time needed can be explained by the variation in the number of invoices processed? TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, what percentage of the variation in the amount of time needed can be explained by the variation in the number of invoices processed? -Referring to Table 12-12, what percentage of the variation in the amount of time needed can be explained by the variation in the number of invoices processed?

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TABLE 12-13 In this era of tough economic conditions, voters increasingly ask the question: "Is the educational achievement level of students dependent on the amount of money the state in which they reside spends on education?" The partial computer output below is the result of using spending per student ($) as the independent variable and composite score, which is the sum of the math, science, and reading scores, as the dependent variable on 35 states that participated in a study. The table includes only partial results. TABLE 12-13 In this era of tough economic conditions, voters increasingly ask the question: Is the educational achievement level of students dependent on the amount of money the state in which they reside spends on education? The partial computer output below is the result of using spending per student ($) as the independent variable and composite score, which is the sum of the math, science, and reading scores, as the dependent variable on 35 states that participated in a study. The table includes only partial results.    -Referring to Table 12-13, what is the standard deviation of the composite score around the regression line? -Referring to Table 12-13, what is the standard deviation of the composite score around the regression line?

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TABLE 12-4 The managers of a brokerage firm are interested in finding out if the number of new clients a broker brings into the firm affects the sales generated by the broker. They sample 12 brokers and determine the number of new clients they have enrolled in the last year and their sales amounts in thousands of dollars. These data are presented in the table that follows. TABLE 12-4 The managers of a brokerage firm are interested in finding out if the number of new clients a broker brings into the firm affects the sales generated by the broker. They sample 12 brokers and determine the number of new clients they have enrolled in the last year and their sales amounts in thousands of dollars. These data are presented in the table that follows.    -Referring to Table 12-4, suppose the managers of the brokerage firm want to construct a 99% prediction interval for the sales made by a broker who has brought into the firm 18 new clients. The t critical value they would use is ________. -Referring to Table 12-4, suppose the managers of the brokerage firm want to construct a 99% prediction interval for the sales made by a broker who has brought into the firm 18 new clients. The t critical value they would use is ________.

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TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, the model appears to be adequate based on the residual analyses. Note: 4.3946E-15 is 4.3946 x 10-15. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, the model appears to be adequate based on the residual analyses. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, the model appears to be adequate based on the residual analyses. -Referring to Table 12-12, the model appears to be adequate based on the residual analyses.

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TABLE 12-10 The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousand of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results: TABLE 12-10 The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousand of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results:    -Referring to Table 12-10, the value of the F test statistic equals the square of the t test statistic when testing whether the number of customers who make purchases is a good predictor for weekly sales. -Referring to Table 12-10, the value of the F test statistic equals the square of the t test statistic when testing whether the number of customers who make purchases is a good predictor for weekly sales.

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The coefficient of determination represents the ratio of SSR to SST.

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TABLE 12-7 An investment specialist claims that if one holds a portfolio that moves in the opposite direction to the market index like the S&P 500, then it is possible to reduce the variability of the portfolio's return. In other words, one can create a portfolio with positive returns but less exposure to risk. A sample of 26 years of S&P 500 Index and a portfolio consisting of stocks of private prisons, which are believed to be negatively related to the S&P 500 Index, is collected. A regression analysis was performed by regressing the returns of the prison stocks portfolio (Y) on the returns of S&P 500 Index (X) to prove that the prison stocks portfolio is negatively related to the S&P 500 Index at a 5% level of significance. The results are given in the following Microsoft Excel output. TABLE 12-7 An investment specialist claims that if one holds a portfolio that moves in the opposite direction to the market index like the S&P 500, then it is possible to reduce the variability of the portfolio's return. In other words, one can create a portfolio with positive returns but less exposure to risk. A sample of 26 years of S&P 500 Index and a portfolio consisting of stocks of private prisons, which are believed to be negatively related to the S&P 500 Index, is collected. A regression analysis was performed by regressing the returns of the prison stocks portfolio (Y) on the returns of S&P 500 Index (X) to prove that the prison stocks portfolio is negatively related to the S&P 500 Index at a 5% level of significance. The results are given in the following Microsoft Excel output.     Note: 2.94942E-07 = 2.94942 * 10-7 -Referring to Table 12-7, to test whether the prison stocks portfolio is negatively related to the S&P 500 Index, the p-value of the associated test statistic is ________. Note: 2.94942E-07 = 2.94942 * 10-7 -Referring to Table 12-7, to test whether the prison stocks portfolio is negatively related to the S&P 500 Index, the p-value of the associated test statistic is ________.

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TABLE 12-13 In this era of tough economic conditions, voters increasingly ask the question: "Is the educational achievement level of students dependent on the amount of money the state in which they reside spends on education?" The partial computer output below is the result of using spending per student ($) as the independent variable and composite score, which is the sum of the math, science, and reading scores, as the dependent variable on 35 states that participated in a study. The table includes only partial results. TABLE 12-13 In this era of tough economic conditions, voters increasingly ask the question: Is the educational achievement level of students dependent on the amount of money the state in which they reside spends on education? The partial computer output below is the result of using spending per student ($) as the independent variable and composite score, which is the sum of the math, science, and reading scores, as the dependent variable on 35 states that participated in a study. The table includes only partial results.    -Referring to Table 12-13, if the state decides to spend 1,000 dollars more per student, the estimated change in mean composite score is ________. -Referring to Table 12-13, if the state decides to spend 1,000 dollars more per student, the estimated change in mean composite score is ________.

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TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    . -Referring to Table 12-2, what is ∑ (X -   )² for these data? . -Referring to Table 12-2, what is ∑ (X - TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    . -Referring to Table 12-2, what is ∑ (X -   )² for these data? )² for these data?

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TABLE 12-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel to analyze the last four years of quarterly data (i.e., n = 16) with the following results: TABLE 12-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel to analyze the last four years of quarterly data (i.e., n = 16) with the following results:    -If the Durbin-Watson statistic has a value close to 0, which assumption is violated? -If the Durbin-Watson statistic has a value close to 0, which assumption is violated?

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TABLE 12-9 It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Microsoft Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown. TABLE 12-9 It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Microsoft Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown.     Note: 2.051E-05 = 2.051 * 10-0.5 and 5.944E-18 = 5.944 * 10-18. -Referring to Table 12-9, the error sum of squares (SSE)of the above regression is ________. Note: 2.051E-05 = 2.051 * 10-0.5 and 5.944E-18 = 5.944 * 10-18. -Referring to Table 12-9, the error sum of squares (SSE)of the above regression is ________.

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TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    . -Referring to Table 12-2, if the price of the candy bar is set at $2, the predicted sales will be . -Referring to Table 12-2, if the price of the candy bar is set at $2, the predicted sales will be

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TABLE 12-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel to analyze the last four years of quarterly data (i.e., n = 16) with the following results: TABLE 12-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel to analyze the last four years of quarterly data (i.e., n = 16) with the following results:    -Referring to Table 12-5, the correlation coefficient is ________. -Referring to Table 12-5, the correlation coefficient is ________.

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TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, you can be 95% confident that the mean amount of time needed to record one additional loan application is somewhere between 0.0109 and 0.0143 hours. Note: 4.3946E-15 is 4.3946 x 10-15. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, you can be 95% confident that the mean amount of time needed to record one additional loan application is somewhere between 0.0109 and 0.0143 hours. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, you can be 95% confident that the mean amount of time needed to record one additional loan application is somewhere between 0.0109 and 0.0143 hours. -Referring to Table 12-12, you can be 95% confident that the mean amount of time needed to record one additional loan application is somewhere between 0.0109 and 0.0143 hours.

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What do we mean when we say that a simple linear regression model is "statistically" useful?

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TABLE 12-1 A large national bank charges local companies for using their services. A bank official reported the results of a regression analysis designed to predict the bank's charges (Y) measured in dollars per month for services rendered to local companies. One independent variable used to predict service charges to a company is the company's sales revenue (X) measured in millions of dollars. Data for 21 companies who use the bank's services were used to fit the model: Y1 - β0 + β1X1 + εi The results of the simple linear regression are provided below. Y = -2,700 + 20 X, SYX = 65, two-tail p-value = 0.034 (for testing β1) -Referring to Table 12-1, interpret the estimate of σ, the standard deviation of the random error term (standard error of the estimate)in the model.

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TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: TABLE 12-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses six small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    . -Referring to Table 12-2, what is the percentage of the total variation in candy bar sales explained by the regression model? . -Referring to Table 12-2, what is the percentage of the total variation in candy bar sales explained by the regression model?

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TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, the p-value of the measured F test statistic to test whether the number of loan applications record affects the amount of time is ________. Note: 4.3946E-15 is 4.3946 x 10-15. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, the p-value of the measured F test statistic to test whether the number of loan applications record affects the amount of time is ________. TABLE 12-12 The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:     Note: 4.3946E-15 is 4.3946 x 10-15.        -Referring to Table 12-12, the p-value of the measured F test statistic to test whether the number of loan applications record affects the amount of time is ________. -Referring to Table 12-12, the p-value of the measured F test statistic to test whether the number of loan applications record affects the amount of time is ________.

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