Business Forecasting 8th Edition John Hanke, Dean Wichern - Solutions

How does an autoregressive model work?
Suggest ways to solve the problem of serial correlation.
You test for serial correlation at the .05 level with 61 residuals from a regression with one independent variable. If the calculated Durbin-Watson statistic is equal to 1.6. what is your conclusion?
You test for serial correlation at the .01 level with 32 residuals from a regression with two independent variables. If the calculated Durbin-Watson statistic is equal to 1.0. what is your conclusion?
Which statistic is commonly used to detect serial correlation?
Which underlying regression assumption is violated most frequently when time series variables are analyzed?
What is a major cause of serial correlation?
Why is serial correlation a problem when time series data are analyzed?
Develop a model to forecast Br/IP.
Are there any nonlinear relationships between the predictor variables and earned run aver- age? If so, develop a new model including the appropriate variable transformation.
Comment on the model that Dr. Hanke developed to forecast earned run average (ERA). Examine the residual plots shown in Figure 7-4 and determine whether this model is valid.
Recall Example 7.12. The full data set related to CEO compensation is contained in Appendix D. (See p. 517.) Use stepwise regression to select the "best" model with k 3 predictor variables. Fit the stepwise model and interpret the estimated coefficients. Examine the residuals. Identify and explain
Refer to the data in Table P-18. Find the "best" regression model using the stepwise regression procedure and the all possible regressions procedure. Compare the results. Are you confident using a regression model to predict the final exam score with fewer than the original three independent
The scores X1 and X2 for two within-term examinations, the current grade point average (GPA) X1, and the final exam score Y for 20 students in a business statistics class are listed in Table P-18.a. Fit a multiple regression model to predict the final exam score from the scores on the within-term
Ms. Haight, a real estate broker, wishes to forecast the importance of four factors in determining the prices of lots. She accumulates data on price, area, elevation.
Cindy Lawson just bought a major league baseball team. She has been receiving a lot of advice concerning what she should do to create a winning ballclub. Cindy asks you to study this problem and write a report. You decide to use multiple regression analysis to determine which statistics are
We might expect credit card purchases to differ from cash purchases at the same store. Table P-15 contains daily gross cash sales and number of items sold for cash purchases, and daily gross credit card sales and number of items sold for credit card purchases at the same consignment store for 25
The Nelson Corporation decides to develop a multiple regression equation to forecast sales performance. A random sample of 14 salespeople is interviewed and given an aptitude test. In addition, an index of effort expended is calculated for each salesperson on the basis of a ratio of the mileage on
The sales manager of Hartman Auto Supplies decides to investigate a new independent variable. personal income by region (see Problem 12). The data for this new variable are presented in Table P-13,a. Does personal income by region make a contribution to the forecasting of sales?b. Forecast annual
The sales manager of a large automotive parts distributor, Hartman Auto Supplies. wants to develop a model to forecast as early as May the total annual sales of a region. If regional sales can be forecast, then the total sales for the company can be forecast. The number of retail outlets in the
A taxi company is interested in the relationship between mileage, measured in miles per gallon, and the age of cars in its fleet. The 12 fleet cars are the same make and size and in good operating condition as a result of regular maintenance. The company employs both male and female drivers, and it
Beer sales at the Shapiro One-Stop Store are analyzed by using temperature and number of people (age 21 or over) on the street as independent variables. A random sample of 20 days is selected and three variables are measured.
Table P-9 contains data on food expenditures, annual income, and family size for a sample of 10 families.
Jennifer Dahl, supervisor of the Circle O discount chain. would like to forecast the time it takes to check out a customer. She decides to use the following independent variables: number of purchased items and the total amount of the purchase. She collects data for a sample of 18 customers, shown
4. 5, or 6) will be the first to enter the regression function?
Most computer solutions for multiple regression begin with a correlation matrix. Examining this matrix is often the first step when analyzing a regression problem that involves more than one independent variable. Answer the following questions concerning the correlation matrix given in Table P-7.a.
Explain each of the following concepts:a. Correlation matrixb. Rc. Multicollinearityd. Residuale. Dummy variablef. Stepwise regression
Your estimated multiple regression equation is = 7.52+3x-12.2X2. Predict the value of Y if X = 20 and X2 = 7.
What does the standard error of the estimate measure in multiple regression?
What does the partial, or net, regression coefficient measure in multiple regression?
What are the assumptions associated with the multiple regression model?
What are the characteristics of a good predictor variable?
Assume that you developed a good regression equation. Would you be able to use this equation to forecast for the rest of 1993? Explain your answer.
The data consist of a time series: does this mean the independence assumption has been violated?
Would the business activity index be a good predictor of the number of new clients?
Compare the results of your forecast with the actual observations for the first 3 months of 1993.
Develop a regression equation and use it to forecast the number of new clients for the first 3 months of 1993.
Determine whether there is a significant rela- tionship between the number of new clients seen and the number of people on food stamps and/or the business activity index. Don't forget the possibility of data transformations.
How do John's data violate one of the assump- tions of regression analysis?
What is your opinion regarding the adequacy of John's forecasting method?
Comment on John's belief that his monthly sales are highly seasonal and, therefore, lead to a "low" r-squared value.
Has an effective forecasting method been developed?
Should Bill McGone proceed to take a large sample of company employees based on the preliminary results of his sample?
Suppose a newly hired person is 24 years old. How many absent days would you forecast for this person during the fiscal year?
Is there a significant relation between absent days and age? In answering this question. use proper statistical procedures to support your answer.
What percentage of the variability in absent days can be explained through knowledge of age?
What is the forecasting equation for absent days using age as a predictor variable?
How well are absent days and age correlated? Can this correlation be generalized to the entire workforce?
Do you think Gene has developed an effective forecasting tool?
Based on the results of the regression anal- ysis as shown earlier, what action would you advise Gene to take in order to increase daily output?
How many units would you forecast for a day in which the high temperature is 41 degrees?
How many units would you forecast for a day in which the high temperature is 89 degrees?
On The Double, a chain of campus copy centers, began operations with a single store in 1990. The number of copy centers in operation, Y. is recorded for fourteen consecutive years in Table P-a. Plot number of copy centers versus year. Has On The Double experienced linear or exponential growth?b.
Outback Steakhouse grew explosively during its first years of operation. The number of Outback Steakhouse locations for the period 1988-1993 are given in the following chart.
Table P-16 contains data on newsprint consumption (Y) during a particular year and number of families in the city (X) for a sample of n = 23 cities.a. Plot newsprint consumptions against number of families as a scatter diagram.b. Is a simple linear regression model appropriate for the data in Table
Player costs (X) and operating expenses (Y) for n = 26 major league baseball teams for the 1990-1991 season are given in Table P-15. (All data are in millions of dollars.)a. Assuming a simple linear regression model, determine the equation for the fitted straight line.b. Determine and comment on
The data in Table P-14 were collected as part of a study of real estate property evaluation. The numbers are observations on X = assessed value (in thousands of dollars) on the city assessor's books and Y = market value (selling price in thousands of dollars) for n = 30 parcels of land that sold in
Harry Daniels is a quality control engineer for the Specific Electric Corporation. Specific manufactures electric motors. One of the steps in the manufacturing process involves the use of an automatic milling machine to produce slots in the shafts of the motors. Each batch of shafts is tested, and
Consider the population of 140 observations that are presented in Table P-12. The Marshall Printing Company wishes to estimate the relationship between the number of copies produced by an offset printing technique (X) and the associated direct labor cost (Y). Select a random sample of 20
Ed Bogdanski, owner of the American Precast Company, has hired you as a part-time analyst. Ed was extremely pleased when you determined that there is a positive relationship between the number of building permits issued and the amount of work available to his company. Now he wonders if it is
Evaluate the following statements:a. A high means a significant regression.b. A very large sample size in a regression problem will always produce useful results.
The ABC Investment Company is in the business of making bids on investments offered by various firms that desire additional financing. ABC has tabulated its bid on the last 25 issues bid in terms of the bid's percentage of par value. The bid of ABC's major competitor, as a percentage of par value,
In a study of investments and interest rates, the data in Table P-8 were observed during 10 years.a. Is the relationship between these variables significant?b. Can an effective prediction equation be developed?c. If 5 years from now the average interest rate is 4%, can yearly investment be
Information supplied by a mail-order business for 12 cities is shown in Table P-7.a. Determine whether a significant linear relationship exists between these two variables. (Test at the .05 significance level.)b. Determine the fitted regression line.c. Calculate the standard error of estimate.d.
Andrew Vazsonyi is the manager of the Spendwise supermarket chain. He would like to be able to forecast paperback book sales (books per week) based on the amount of shelf display space (feet) provided. Andrew gathers data for a sample of 11 weeks as shown in Table P-6.a. Plot a scatter diagram.b.
Lori Franz, maintenance supervisor for the Baltimore Transit Authority, would like to determine whether there is a positive relationship between the annual maintenance cost of a bus and its age. If a relationship exists. Lori feels that she can do a better job of forecasting the annual bus
The times required to check out customers in a supermarket and the corresponding values of purchases are shown in Table P-4. Answer partsa, b.e. and f of Problem 3 by using these data. Give a point estimate and a 99% interval estimate for Y if X = 3.0.
Consider the data in Table P-3, where X = weekly advertising expenditures and Y = weekly sales.a. Does a significant relationship exist between advertising expenditures and sales?b. State the prediction equation.c. Forecast sales for an advertising expenditure of $50.d. What percentage of the
AT&T (American Telephone and Telegraph) earnings in billions are estimated using GNP (gross national product). The regression equation is Y = .078+.06X where GNP is measured in billions of dollars.a. Interpret the slope.b. Interpret the Y intercept.
Which of the following situations is inconsistent?a. Yb. Y =c. 499+21X and r = .75 100+9X and r=-,70 =-20+1X and r = .40d. -7-4X and r = -.90
Write a memo to Mr. DeCoria summarizing the important insights into changes in emergency road service call volume that you discovered from your time series decomposition analysis.
Perform a time series decomposition on the AAA emergency road service calls data.
Disregarding Seattle, how much volume would John have to realize from his shirt-making machine to make both January and February "average"?
Assume that John will do exactly twice as much business in Seattle as in Spokane next year. Determine the Seattle seasonal indices that would be ideal to balance out the monthly revenues for Mr. Tux.
Suppose John's banker asked for two sentences to show his boss that would justify John's request to make extra loan payments in some months and no payments in others. Write these two. sentences.
identify the model you would use for your business planning in 2004, and discuss why you selected that model over the others.
If you had to limit your choice to one of the models in questions 2 and
Calculate MAD values for the two models that visually appear to give the best fits (most accurate one-step-ahead forecasts).
Smooth the time series using trend-adjusted exponential smoothing with three sets of smoothing constants: (a = .1. = 1), (a = === 25. B .25), and (a=.5.8.5). Plot the three sets of smoothed values on the time series graph. Generate forecasts through the end of the third year for each of the
Estimate the seasonal adjustment factors for each month by dividing the average demand for corresponding months by the average of the corresponding trend-line forecasts. Plot a seasonally adjusted trend line.
Develop a trend-line equation using linear regression and plot the results.
Plot the data on a 2-year time horizon from 2002 through 2003. Connect the data points to make a time series plot.
Deflate the dollar sales volumes using the commodity price index values, shown in Table P-24. These indices are for all commodities with 1992 = 100.
In the base period of June, the price of a selected quantity of goods was $1,289.73. In the most recent month, the price index for these goods was 284.7. How much would the selected goods cost if purchased in the most recent month?
What is the purpose of deflating a time series that is measured in dollars?
What is the present position of the business cycle? Is it expanding or contracting? When will the next turning point occur?
Discuss the performance of the composite index of leading indicators as a barom- eter of business activity in recent years.
The adjusted seasonal indices presented in Table P-19 reflect the changing volume of business of the Mt. Spokane Resort Hotel, which caters to family tourists in the summer and skiing enthusiasts during the winter months. No sharp cyclical variations are expected during 2003.
Table P-18 contains data values that represent the monthly sales of all retail stores in the United States in billions of dollars. Using the data through 1994, perform a decomposition analysis of this series. Comment on all three components of the series. Forecast retail sales for 1995 and compare
The monthly gasoline demand (thousands of barrels/day) for Yukong Oil Company of South Korea for the period January 1986 to September 1996 is contained in Table P-17.
Table P-16 contains the quarterly sales ($ millions) for the Disney Company from January 1980 to March 1995.a. Perform a multiplicative decomposition of the time series consisting of Disney's quarterly sales.b. Does there appear to be a significant trend? Discuss the nature of the seasonal
Construct a table similar to Table P-14 with the natural logarithms of monthly sales. For example, the value for January 1996 is In(154) = 5.037.a. Perform an additive decomposition of In(sales) assuming the model Y=T+S+1.b. Would you use the trend, seasonal, or both components to forecast?c.
The monthly sales of the Cavanaugh Company, listed in Table P-14 and pictured in Figure 5-1, are given next.a. Perform a multiplicative decomposition of the Cavanaugh Company sales time series assuming trend, seasonal, and irregular components.b. Would you use the trend, seasonal, or both
The quarterly sales levels measured in millions of dollars for Goodyear Tire are shown in Table P-13. Does there appear to be a significant seasonal effect in these sales levels? Analyze this time series to get the four seasonal indices, and determine the extent of the seasonal component in
In preparing a report for June Bancock, manager of the Kula Department Store. you include the following statistics (Table P-12) from last year's sales. Upon seeing them. Ms. Bancock says. "This report confirms what I've been telling you: Business is getting better and better." Is this statement
A large resort near Portland, Maine. has been tracking its monthly sales for several years but has never analyzed these data. The resort computes the seasonal indices for its monthly sales. Which of the following statements about the index are correct?a. The sum of the 12 monthly index numbers,
The following specific percentage seasonal indices are given for the month of December: 75.4 86.8 96.9 72.6 80.0 85.4 Assume a multiplicative decomposition model. If the expected trend for December is $900, and the median seasonal adjustment is used, what is the forecast for December?
The expected trend value for October is $850. Assuming an October seasonal index of 1.12 (112%) and the multiplicative model given by Equation 5.2. what would be the forecast for October?
Assume the following specific percentage seasonal indices for March based on the ratio-to-moving-average method: 102.2 105.9 114.3 122.4 109.8 98.9 What is the seasonal index for March using the median?
A large company is considering cutting back on its TV advertising in favor of business videos to be given to its customers. This action is being considered after?

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Business Forecasting 8th Edition John Hanke, Dean Wichern - Solutions

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