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Basic Business Statistics Concepts And Applications 12th Edition Mark L. Berenson, David M. Levine, Timothy C. Krehbiel - Solutions

The marketing manager of a large supermarket chain faced the business problem of determining the effect on the sales of pet food of shelf space and whether the product was placed at the front (= 1) or back (= 0) of the aisle. Data are collected from a random sample of 12 equal-sized stores. The
In mining engineering, holes are often drilled through rock, using drill bits. As a drill hole gets deeper, additional rods are added to the drill bit to enable additional drilling to take place. It is expected that drilling time increases with depth. This increased drilling time could be caused by
The owner of a moving company typically has his most experienced manager predict the total number of labor hours that will be required to complete an upcoming move. This approach has proved useful in the past, but the owner has the business objective of developing a more accurate method of
In Problem 14.4 on page 583, you used sales and orders to predict distribution cost (stored in WareCost). Develop a regression model to predict distribution cost that includes sales, orders, and the interaction of sales and orders. a. At the 0.05 level of significance, is there evidence that the
Zagat's publishes restaurant ratings for various locations in the United States. The file Restaurants contains the Zagat rating for food, décor, service, and cost per person for a sample of 50 restaurants located in a city and 50 restaurants located in a suburb. Develop a regression model to
In Problem 14.6 on page 583, you used radio advertising and newspaper advertising to predict sales (stored in Advertise). Develop a regression model to predict sales that includes radio advertising, newspaper advertising, and the interaction of radio advertising and newspaper advertising. a. At the
In Problem 14.5 on page 583, horsepower and weight were used to predict miles per gallon (stored in Auto2010). Develop a regression model that includes horsepower, weight, and the interaction of horsepower and weight to predict miles per gallon. a. At the 0.05 level of significance, is there
In Problem 14.7 on page 584, you used total staff present and remote hours to predict standby hours (stored in Standby). Develop a regression model to predict standby hours that includes total staff present, remote hours, and the interaction of total staff present and remote hours. a. At the 0.05
The director of a training program for a large insurance company has the business objective of determining which training method is best for training underwriters. The three methods to be evaluated are traditional, CD-ROM based, and Web based. The 30 trainees are divided into three randomly
How does horsepower and weight affect the mileage of family sedans? Data from a sample of twenty 2010 family sedans were collected and organized and stored in Auto2010. (Data extracted from "Top 2010 Cars," Consumer Reports, April 2010, pp. 38-70.) Develop a regression model to predict mileage (as
Interpret the meaning of a slope coefficient equal to 2.2 in logistic regression.
Consider the following logistic regression equation:In(Estimated odds ratio) = 0.1 + 0.5X1t + 0.2X2ta. Interpret the meaning of the logistic regression coefficients.b. If X1 = 2 and X2 = 1.5, compute the estimated odds ratio and interpret its meaning.c. On the basis of the results of (b), compute
Refer to Figure 14.14 on page 611.a. Predict the probability that a cardholder who charged $36,000 last year and does not have any additional credit cards for members of the household will purchase the premium card during the marketing campaign.b. Compare the results in (a) with those for a person
Undergraduate students at Miami University in Oxford, Ohio, were surveyed in order to evaluate the effect of price on the purchase of a pizza from Pizza Hut. The students were asked to suppose that they were going to have a large two-topping pizza delivered to their residence. Then they were asked
The director of graduate studies at a college of business wants to predict the success of students in anMBA program using two independent variables, undergraduate grade point average (GPA) and GMAT score.A random sample of 30 students (stored in MBA) indicates that 20 successfully completed the
A hotel has designed a new system for room service delivery of breakfast that allows the customer to select a specific delivery time. The difference between the actual and requested delivery times was recorded (a negative time means that the breakfast was delivered before the requested time) for 30
What is the difference between r2 and adjusted r2?
How does the interpretation of the regression coefficients differ in multiple regression and simple linear regression? Discuss.
The business problem facing a consumer products company is to measure the effectiveness of different types of advertising media in the promotion of its products. Specifically, the company is interested in the effectiveness of radio advertising and newspaper advertising (including the cost of
How does testing the significance of the entire multiple regression model differ from testing the contribution of each independent variable?
How do the coefficients of partial determination differ from the coefficient of multiple determination?
Why and how do you use dummy variables?
Under what circumstances do you include an interaction term in a regression model?
Increasing customer satisfaction typically results in increased purchase behavior. For many products, there is more than one measure of customer satisfaction. In many of these instances, purchase behavior can increase dramatically with an increase in any one of the customer satisfaction measures,
The owner of a moving company typically has his most experienced manager predict the total number of labor hours that will be required to complete an upcoming move. This approach has proved useful in the past, but the owner has the business objective of developing a more accurate method of
Professional basketball has truly become a sport that generates interest among fans around the world. More and more players come from outside the United States to play in the National Basketball Association (NBA). You want to develop a regression model to predict the number of wins achieved by each
The business problem facing the director of broadcasting operations for a television station was the issue of standby hours (i.e., hours in which unionized graphic artists at the station are paid but are not actually involved in any activity) and what factors were related to standby hours. The
A sample of 30 recently sold single-family houses in a small city is selected. Develop a model to predict the selling price (in thousands of dollars), using the assessed value (in thousands of dollars) as well as time (in months since reassessment). The houses in the city had been reassessed at
Measuring the height of a California redwood tree is very difficult because these trees grow to heights over 300 feet. People familiar with these trees understand that the height of a California redwood tree is related to other characteristics of the tree, including the diameter of the tree at the
Develop a model to predict the assessed value (in thousands of dollars), using the size of the houses (in thousands of square feet) and the age of the houses (in years) from the following table (stored in House2):a. State the multiple regression equation.b. Interpret the meaning of the slopes in
Crazy Dave, a well-known baseball analyst, wants to determine which variables are important in predicting a team's wins in a given season. He has collected data related to wins, earned run average (ERA), and runs scored for the 2009 season (stored in BB2009). Develop a model to predict the number
Referring to Problem 14.73, suppose that in addition to using ERA to predict the number of wins, Crazy Dave wants to include the league (0 = American, 1 = National) as an independent variable. Develop a model to predict wins based on ERA and league. For (a) through (k), do not include an
You are a real estate broker who wants to compare property values in Glen Cove and Roslyn (which are located approximately 8 miles apart). In order to do so, you will analyze the data in GCResiyn, a file that includes samples of houses from Glen Cove and Roslyn. Making sure to include the dummy
A recent article discussed a metal deposition process in which a piece of metal is placed in an acid bath and an alloy is layered on top of it. The business objective of engineers working on the process was to reduce variation in the thickness of the alloy layer. To begin, the temperature and the
Nassau County is located approximately 25 miles east of NewYork City. The data organized and stored in GlenCove include the appraised value, land area of the property in acres, and age, in years, for a sample of 30 single-family homes located in Glen Cove, a small city in Nassau County. Develop a
The following ANOVA summary table is for a multiple regression model with two independent variables:a. Determine the regression mean square (MSR) and the mean square error (MSE). b. Compute the overall FSTAT test statistic. c. Determine whether there is a significant relationship between Y and the
The following is the quadratic regression equation for a sample of n = 25:a. Predict Y for b. Suppose that the computed tSTAT test statistic for the quadratic regression coefficient is 2.35. At the 0.05 level of significance, is there evidence that the quadratic model is better than the linear
Using the data of Problem 15.4 on page 637, stored in Domesticbeer, perform a square-root transformation on each of the independent variables (percentage alcohol and number of carbohydrates). Using calories as the dependent variable and the transformed independent variables, perform a multiple
Using the data of Problem 15.4 on page 637, stored in DomesticBeer, perform a natural logarithmic transformation of the dependent variable (calories). Using the transformed dependent variable and the percentage of alcohol and the number of carbohydrates as the independent variables, perform a
Using the data of Problem 15.6 on page 637, stored in Tomato, perform a natural logarithm transformation of the dependent variable (yield). Using the transformed dependent variable and the fertilizer application rate as the independent variable, perform a regression analysis.a. State the regression
Using the data of Problem 15.6 on page 637, stored in Tomato, perform a square-root transformation of the independent variable (fertilizer application rate). Using yield as the dependent variable and the transformed independent variable, perform a regression analysis.a. State the regression
Refer to Problem 14.4 on page 583. Perform a multiple regression analysis using the data in WareCost and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity?
Refer to Problem 14.6 on page 583. Perform a multiple regression analysis using the data in Advertise and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity?
Refer to Problem 14.7 on page 584. Perform a multiple regression analysis using the data in Standby and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity?
Businesses actively recruit business students with well-developed higher-order cognitive skills (HOCS) such as problem identification, analytical reasoning, and content integration skills. Researchers conducted a study to see if improvement in students'HOCS was related to the students' GPA. (Data
You are considering four independent variables for inclusion in a regression model. You select a sample of n = 30, with the following results:1. The model that includes independent variables A and B has a Cp value equal to 4.6.2. The model that includes independent variables A and C has a Cp value
You are considering six independent variables for inclusion in a regression model. You select a sample of with the following results:a. Compute the Cp value for this two-independent-variable model.b. Based on your answer to (a), does this model meet the criterion for further consideration as the
In Problems 13.85 through 13.89 on page 568, you constructed simple linear regression models to investigate the relationship between demographic information and monthly sales for a chain of sporting goods stores using the data in Sporting. Develop the most appropriate multiple regression model to
You need to develop a model to predict the selling price of houses in a small city, based on assessed value, time in months since the house was reassessed, and whether the house is new (0 = no, 1 = yes). A sample of 30 recently sold single-family houses that were reassessed at full value one year
The human resources (HR) director for a large company that produces highly technical industrial instrumentation devices has the business objective of improving recruiting decisions concerning sales managers.The company has 45 sales regions, each headed by a sales manager. Many of the sales managers
What is the difference between stepwise regression and best-subsets regression?
How do you choose among models according to the Cp statistic in best-subsets regression?
Crazy Dave has expanded his analysis, presented in Problem 14.73 on page 619, of which variables are important in predicting a team's wins in a given baseball season. He has collected data in related to wins, ERA, saves, runs scored, hits allowed, walks allowed, and errors for the 2009 season.a.
A national chain of consumer electronics stores had the business objective of determining the effectiveness of newspaper advertising. To promote sales, the chain relies heavily on local newspaper advertising to support its modest exposure in nationwide television commercials. A sample of 20 cities
Professional basketball has truly become a sport that generates interest among fans around the world. More and more players come from outside the United States to play in the National Basketball Association (NBA). Many factors could impact the number of wins achieved by each NBA team. In addition
Hemlock Farms is a community located in the Pocono Mountains area of eastern Pennsylvania. The file HemlockFarms contains information on homes that were recently for sale. The variables included wereList Price-Asking price of the houseHot Tub-Whether the house has a hot tub, with 0 = No and 1 =
Nassau County is located approximately 25 miles east of NewYork City. Data in GlenCove are from a sample of 30 single-family homes located in Glen Cove. Variables included are the appraised value, land area of the property (acres), interior size of the house (square feet), age (years), number of
You are a real estate broker who wants to compare property values in Glen Cove and Roslyn (which are located approximately 8 miles apart). Use the data in GCRosiyn. Make sure to include the dummy variable for location (Glen Cove or Roslyn) in the regression model.a. Develop the most appropriate
You are a real estate broker who wants to compare property values in Glen Cove, Freeport, and Roslyn. Use the data in GCFreeRosiyn. a. Develop the most appropriate multiple regression model to predict appraised value. b. What conclusions can you reach concerning the differences in appraised value
Over the past 30 years, public awareness and concern about air pollution have escalated dramatically. Venturi scrubbers are used for the removal of submicron particulate matter from smoke stacks. An experiment was conducted to determine the effect of air flow rate, water flow rate (liters/minute),
A recent article (J. Conklin, "It's a Marathon, Not a Sprint," Quality Progress, June 2009, pp. 46-49) discussed a metal deposition process in which a piece of metal is placed in an acid bath and an alloy is layered on top of it. The key quality characteristic is the thickness of the alloy layer.
A headline in The New York Times on March 4, 1990, read: "Wine equation puts some noses out of joint." The article explained that Professor Orley Ashenfelter, a Princeton University economist, had developed a multiple regression model to predict the quality of French Bordeaux, based on the amount
Is the number of calories in a beer related to the number of carbohydrates and/or the percentage of alcohol in the beer? Data concerning 139 of the best-selling domestic beers in the United States are stored in Domesticbeer. The values for three variables are included: the number of calories per 12
The file Bond Funds contains information regarding eight variables from a sample of 184 bond mutual funds:Type-Type of bonds comprising the bond mutual fund(intermediate government or short-term corporate)Assets-In millions of dollarsFees-Sales charges (no or yes)Expense ratio-Ratio of expenses to
The per-store daily customer count (i.e., the mean number of customers in a store in one day) for a nationwide convenience store chain that operates nearly 10,000 stores has been steady, at 900, for some time. To increase the customer count, the chain is considering cutting prices for coffee
An agronomist designed a study in which tomatoes were grown using six different amounts of fertilizer: 0, 20, 40, 60, 80, and 100 pounds per 1,000 square feet. These fertilizer application rates were then randomly assigned to plots of land. The results including the yield of tomatoes (in pounds)
An auditor for a county government would like to develop a model to predict county taxes, based on the age of single-family houses. She selects a random sample of 19 single-family houses, and the results are stored in Taxes.1. Construct a scatter plot of age and county taxes.2. Fit a quadratic
Consider the following regression equation:a. Predict the value of Y when X1 = 8.5 and X2 = 5.2. b. Interpret the meaning of the regression coefficients b0, b1, and b2.
Consider the following regression equation:a. Predict the value of Y when X1 = 8.5 and X2 = 5.2. b. Interpret the meaning of the regression coefficients b0, b1, and b2.
The linear trend forecasting equation for an annual time series containing 22 values (from 1989 to 2010) on total revenues (in millions of dollars) isa. Interpret the Y intercept,b. Interpret the slope,c. What is the fitted trend value for the fifth year?d. What is the fitted trend value for the
The linear trend forecasting equation for an annual time series containing 42 values (from 1969 to 2010) on net sales (in billions of dollars) isa. Interpret the Y intercept, b0.b. Interpret the slope, b1.c. What is the fitted trend value for the tenth year?d. What is the fitted trend value for the
Bed Bath & Beyond is a nationwide chain of retail stores that sell a wide assortment of merchandise, including domestics merchandise and home furnishings, as well as food, giftware, and health and beauty care items. The following data (stored in Bed & Bath) show the number of stores open at
Gross domestic product (GDP) is a major indicator of a nation's overall economic activity. It consists of personal consumption expenditures, gross domestic investment, net exports of goods and services, and government consumption expenditures. The GDP (in billions of current dollars) for the United
The data in FedReceipt represent federal receipts from 1978 through 2009, in billions of current dollars, from individual and corporate income tax, social insurance, excise tax, estate and gift tax, customs duties, and federal reserve deposits.a. Plot the series of data.b. Compute a linear trend
The data in Strategic represent the amount of oil, in billions of barrels, held in the U.S. strategic oil reserve, from 1981 through 2009. a. Plot the data. b. Compute a linear trend forecasting equation and plot the trend line. c. Compute a quadratic trend forecasting equation and plot the
The data shown in the following table (and stored in Solar Power) represent the yearly amount of solar power installed (in megawatts) in the United States from 2000 through 2008:Year Amount of Solar Power
Electronics are being recycled more and more due to increased requirements of states and the availability of more companies doing the recycling. The data in the following table (and stored in E-Cycling) represent the tons of electronic items recycled from 1999 to 2007 (the last year for which data
The data in the following table (and stored in BBSalaries) represent the average salary of Major League Baseball players on opening day from 2000 to 2010:Year Salary
The following data (stored in Silver) represent the price in London for an ounce of silver (in U.S. $) on the last day of the year from 1999 to 2009:Year Price
Consider a nine-year moving average used to smooth a time series that was first recorded in 2002. a. Which year serves as the first centered value in the smoothed series? b. How many years of values in the series are lost when computing all the nine-year moving averages?
The data in CPI-U reflect the annual values of the consumer price index (CPI) in the United States over the 45-year period 1965 through 2009, using 1982 through 1984 as the base period. This index measures the average change in prices over time in a fixed "market basket" of goods and services
Although you should not expect a perfectly fitting model for any time-series data, you can consider the first differences, second differences, and percentage differences for a given series as guides in choosing an appropriate model. For this problem, use each of the time series presented in the
A time-series plot often helps you determine the appropriate model to use. For this problem, use each of the time series presented in the following table and stored in TsModel2.a. Plot the observed data (Y) over time (X) and plot the logarithm of the observed data (log Y) over time (X) to determine
You are given an annual time series with 40 consecutive values and asked to fit a fifth-order autoregressive model.1. How many comparisons are lost in developing the autoregressive model?2. How many parameters do you need to estimate?3. Which of the original 40 values do you need for forecasting?4.
A third-order autoregressive model is fitted to an annual time series with 17 values and has the following estimated parameters and standard errors:At the 0.05 level of significance, test the appropriateness of the fitted model.
Refer to Problem 16.24. The three most recent values areY15 = 23 Y16 = 28 Y17 = 34Forecast the values for the next year and the following year.
Refer to Problem 16.24. Suppose, when testing for the appropriateness of the fitted model, the standard errors are Sa1 = 0.45 Sa2 = 0.35 Sa3 = 0.15 a. What conclusions can you reach? b. Discuss how to proceed if forecasting is still your main objective.
Refer to the data given in Problem 16.15 on page 682 that represent the amount of oil (in billions of barrels) held in the U.S. strategic reserve from 1981 through 2009 (stored in Strategic).a. Fit a third-order autoregressive model to the amount of oil and test for the significance of the
Refer to the data given in Problem 16.12 on page 681 that represent the number of stores open for Bed Bath & Beyond from 1993 through 2010 (stored in Bed & Bath).a. Fit a third-order autoregressive model to the number of stores and test for the significance of the third-order autoregressive
Refer to the data given in Problem 16.17 on page 682 that represent the tons of electronic items recycled from 1999 to 2007 (stored in E-Cycling).a. Fit a third-order autoregressive model to the tons of electronic items recycled and test for the significance of the third-order autoregressive
You are using exponential smoothing on an annual time series concerning total revenues (in millions of dollars). You decide to use a smoothing coefficient of W = 0.20, and the exponentially smoothed value for 2010 is E2010 = (0.20) (12.1) + (0.80) (9.4). a. What is the smoothed value of this series
Refer to the data given in Problem 16.18 on page 682 (stored in BBSalaries) that represent the average baseball salary from 2000 through 2010.a. Fit a third-order autoregressive model to the average baseball salary and test for the significance of the third-order autoregressive parameter. (Use α =
Refer to the data given in Problem 16.16 on page 682 (and stored in SolarPower) that represent the yearly amount of solar power installed (in megawatts) in the United States from 2000 through 2008.a. Fit a third-order autoregressive model to the amount of solar power installed and test for the
The following residuals are from a linear trend model used to forecast sales:a. Compute SYX and interpret your findings. b. Compute the MAD and interpret your findings.
Refer to Problem 16.32. Suppose the first residual is 12.0 (instead of 2.0) and the last residual is -11.0 (instead of -1.0). a. Compute Syx and interpret your findings b. Compute the MAD and interpret your findings.
Refer to the results in Problem 16.13 on page 681 (see GDP).a. Perform a residual analysis.b. Compute the standard error of the estimate (Syx)c. Compute the MAD.d. On the basis of (a) through (c), are you satisfied with your linear trend forecasts in Problem 16.13? Discuss.
Refer to the results in Problem 16.15 on page 682 and Problem 16.27 on page 692 concerning the number of barrels of oil in the U.S. strategic oil reserve (stored in Strategic). a. Perform a residual analysis for each model. b. Compute the standard error of the estimate (Syx) for each model. c.
Refer to the results in Problem 16.12 on page 681 and Problem 16.28 on page 692 concerning the number of Bed Bath & Beyond stores open (stored in Bed & Bath).a. Perform a residual analysis for each model.b. Compute the standard error of the estimate (Syx) for each model.c. Compute the MAD
Refer to the results in Problem 16.17 on page 682 and Problem 16.29 on page 692 concerning the amount of electronic items recycled (stored in E-Cycling). a. Perform a residual analysis for each model. b. Compute the standard error of the estimate (Syx) for each model. c. Compute the MAD for each
Refer to the results in Problem 16.18 on page 682 and Problem 16.30 on page 692 concerning the average baseball salary (stored in BBSalaries).a. Perform a residual analysis for each model.b. Compute the standard error of (Syx) the estimate for each model.c. Compute the MAD for each model.d. On the

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