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Data Analysis And Decision Making 4th Edition Christian Albright, Wayne Winston, Christopher Zappe - Solutions

A power company located in southern Alabama wants to predict the peak power load (i.e., Y, the maximum amount of power that must be generated each day to meet demand) as a function of the daily high temperature (X). A random sample of 25 summer days is chosen, and the peak power load and the high
For 12 straight weeks you have observed the sales (in number of cases) of canned tomatoes at Mr. D’s supermarket. Each week you kept track of the following:• Was a promotional notice placed in all shopping carts for canned tomatoes?• Was a coupon given for canned tomatoes?• Was a price
The file P11_44.xlsx contains quarterly data on pork sales. Price is in dollars per hundred pounds, quantity sold is in billions of pounds, per capita income is in dollars, U.S. population is in millions, and GDP is in billions of dollars.a. Use the data to develop a regression equation that could
The file P11_45.xlsx contains monthly sales for a photography studio and the price charged per portrait during each month. Use regression to estimate an equation for predicting the current month’s sales from last month’s sales and the current month’s price. a. If the price of a portrait
The file P11_46.xlsx contains data on a motel chain’s revenue and advertising. Note that column C is simply column B “pushed down” a row.a. If the goal is to get the best-fitting regression equation for Revenue, which of the Advertising variables should be used? Or is it better to use both?b.
The file P11_47.xlsx contains the quarterly revenues (in millions of dollars) of a utility company for a seven-year period. The goal is to use these data to build a multiple regression model that can be used to forecast future revenues. a. Which variables should be included in the regression?
The belief that larger majorities for a president in a presidential election help the president’s party increase its representation in the House and Senate is called the coattail effect. The file P11_48.xlsx lists the percentage by which each president since 1948 won the election and the number
When potential workers apply for a job that requires extensive manual assembly of small intricate parts, they are initially given three different tests to measure their manual dexterity. The ones who are hired are then periodically given a performance rating on a 0 to 100 scale that combines their
Nicklaus Electronics manufactures electronic components used in the computer and space industries. The annual rate of return on the market portfolio and the annual rate of return on Nicklaus Electronics stock for the last 36 months are listed in the file P11_50.xlsx. The company wants to calculate
The auditor of Kaefer Manufacturing uses regression analysis during the analytical review stage of the firm’s annual audit. The regression analysis attempts to uncover relationships that exist between various account balances. Any such relationship is subsequently used as a preliminary test of
A company gives prospective managers four separate tests for judging their potential. For a sample of 30 managers, the test scores and the subsequent job effectiveness ratings (Rating) given one year later are listed in the file P11_52.xlsx.a. Look at scatter plots and the table of correlations for
Confederate Express is attempting to determine how its monthly shipping costs depend on the number of units shipped during a month. The file P11_53.xlsx contains the number of units shipped and total shipping costs for the last 15 months.a. Use regression to determine a relationship between units
The file P11_54.xlsx contains monthly data on fatal automobile crashes in the U.S. in each of eight three-hour intervals. Suppose you didn’t have the data on the midnight to 3AM time interval. How well could multiple regression be used to predict the data for this interval? Which time intervals
You want to determine the variables that influence bus usage in major American cities. For 24 cities, the following data are listed in the file P11_55.xlsx:• Bus travel (annual, in thousands of hours)• Income (average per capita income)• Population (in thousands)• Land area (in square
The file P11_56.xlsx contains data on 80 managers at a large (fictitious) corporation. The variables are Salary (current annual salary), YrsExper (years of experience in the industry), YrsHere (years of experience with this company), and MglLevel (current level in the company, coded 1 to 4). You
A toy company has assigned you to analyze the factors influencing the sales of its most popular doll. The number of these dolls sold during the last 23 years is given in the file P11_57.xlsx. The following factors are thought to influence sales of these dolls:• Was there a recession?• Were the
The file P11_58.xlsx shows the “yield curve” (at monthly intervals). For example, in January 1985 the annual rate on a three-month T-bill was 7.76% and the annual rate on a 30-year government bond was 11.45%. Use regression to determine which interest rates tend to move together most closely.
The Keynesian school of macroeconomics believes that increased government spending leads to increased growth. The file P11_59.xlsx contains the following annual data:• Government spending as percentage of GDP (gross domestic product)• Percentage annual growth in annual GDP Are these data
The June 1997 issue of Management Accounting gave the following rule for predicting your current salary if you are a managerial accountant. Take $31,865. Next, add $20,811 if you are top management, add $3604 if you are senior management, or subtract $11,419 if you are entry management. Then add
A business school committee was charged with studying admissions criteria to the school. Until that time, only juniors were admitted. Part of the committee’s task was to see whether freshman courses would be equally good predictors of success as freshman and sophomore courses combined. Here, we
The file P11_62.xlsx has (somewhat old) data on several countries. The variables are listed here.• Country: name of country• GNPCapita: GNP per capita• PopGrowth: average annual percentage change in population, 1980–1990• Calorie: daily per capita calorie content of food used for domestic
Suppose that an economist has been able to gather data on the relationship between demand and price for a particular product. After analyzing scatter plots and using economic theory, the economist decides to estimate an equation of the form Q = aPb, where Q is quantity demanded and P is price. An
A human resources analyst believes that in a particular industry, the wage rate ($/hr) is related to seniority by an equation of the form W = aebS, where W equals wage rate and S equals seniority (in years). However, the analyst suspects that both parameters, a and b, might depend on whether the
A company has recorded its overhead costs, machine hours, and labor hours for the past 60 months. The data are in the file P11_65.xlsx. The company decides to use regression to explain its overhead hours linearly as a function of machine hours and labor hours. However, recognizing good statistical
Pernavik Dairy produces and sells a wide range of dairy products. Because most of the dairy’s costs and prices are set by a government regulatory board, most of the competition between the dairy and its competitors takes place through advertising. The controller of Pernavik has developed the
The Pierce Company manufactures drill bits. The production of the drill bits occurs in lots of 1000 units. Due to the intense competition in the industry and the correspondingly low prices, Pierce has undertaken a study of the manufacturing costs of each of the products it manufactures. One part of
Danielson Electronics manufactures color television sets for sale in a highly competitive marketplace. Recently Ron Thomas, the marketing manager of Danielson Electronics, has been complaining that the company is losing market share because of a poor quality image, and he has asked that the
The file P11_69.xlsx contains data on gasoline consumption and several economic variables. The variables are gasoline consumption for passenger cars (GasUsed), service station price excluding taxes (SSPrice), retail price of gasoline including state and federal taxes (RPrice), Consumer Price Index
On October 30, 1995, the citizens of Quebec went to the polls to decide the future of their province. They were asked to vote “Yes” or “No” on whether Quebec, a predominantly French-speaking province, should secede from Canada and become a sovereign country. The “No” side was declared
Suppose you are trying to explain variations in salaries for technicians in a particular field of work. The file P11_71.xlsx contains annual salaries for 200 technicians. It also shows how many years of experience each technician has, as well as his or her education level. There are four education
The file P03_55.xlsx contains baseball data on all MLB teams from during the years 2004–2009. For each year and team, the total salary and the number of (regular-season) wins are listed.a. Rearrange the data so that there are six columns: Team, Year, Salary Last Year, Salary This Year, Wins Last
Do the previous problem, but use the basketball data on all NBA teams in the file P03_56.xlsx. a. Rearrange the data so that there are six columns: Team, Year, Salary Last Year, Salary This Year, Wins Last Year, and Wins This Year. You don’t need rows for 2004 rows, because the data for 2003
Do the previous problem, but use the football data on all NFL teams in the file P03_57.xlsx.a. Rearrange the data so that there are six columns: Team, Year, Salary Last Year, Salary This Year, Wins Last Year, and Wins This Year. You don’t need rows for 2004 rows, because the data for 2003 isn’t
The file P03_65.xlsx contains basketball data on all NBA teams for five seasons. The SRS (simple rating system) variable is a measure of how good a team is in any given year. a. Given the explanation of SRS, it makes sense to use multiple regression, with PTS and O_PTS as the explanatory variables,
Do the preceding problem, but now use the football data in the file P03_66.xlsx. a. Given the explanation of SRS, it makes sense to use multiple regression, with PTS and O_PTS as the explanatory variables, to predict SRS. Do you get a good fit?b. Suppose instead that the goal is to predict Wins.
The file P03_63.xlsx contains 2009 data on R&D expenses and many financial variables for 85 U.S. publicly traded companies in the computer and electronic product manufacturing industry. The question is whether R&D expenses can be predicted from any combination of the potential variables. Use
Dupree Fuels Company is facing a difficult problem. Dupree sells heating oil to residential customers. Given the amount of competition in the industry, both from other home heating oil suppliers and from electric and natural gas utilities, the price of the oil supplied and the level of service are
Wagner Printers performs all types of printing, including custom work, such as advertising displays, and standard work, such as business cards. Market prices exist for standard work, and Wagner Printers must match or better these prices to get the business. The key issue is whether the existing
The file S12_01.xlsx contains the monthly number of airline tickets sold by a travel agency. Is this time series random? Perform a runs test and find a few autocorrelations to support your answer.
The file P12_02.xlsx contains the weekly sales at a local bookstore for each of the past 25 weeks. Is this time series random? Perform a runs test and find a few autocorrelations to support your answer.
The number of employees on the payroll at a food processing plant is recorded at the start of each month. These data are provided in the file P12_03.xlsx. Perform a runs test and find a few auto-correlations to determine whether this time series is random.
The quarterly numbers of applications for home mortgage loans at a branch office of Northern Central Bank are recorded in the file P12_04.xlsx. Perform a runs test and find a few autocorrelations to determine whether this time series is random.
The number of reported accidents at a manufacturing plant located in Flint, Michigan, was recorded at the start of each month. These data are provided in the file P12_05.xlsx. Is this time series random? Perform a runs test and find a few autocorrelations to support your answer.
The file P12_06.xlsx contains the weekly sales at the local outlet of West Coast Video Rentals for each of the past 36 weeks. Perform a runs test and find a few autocorrelations to determine whether this time series is random.
Determine whether the RAND() function in Excel actually generates a random stream of numbers. Generate at least 100 random numbers to test their randomness with a runs test and with autocorrelations. Summarize your findings.
Use a runs test and calculate auto relations to decide whether the random series explained in each part of this problem (a–c) are random. For each part, generate at least 100 random numbers in the series. a. A series of independent normally distributed values, each with mean 70 and standard
The file P12_01.xlsx contains the monthly number of airline tickets sold by a travel agency.a. Does a linear trend appear to fit these data well? If so, estimate and interpret the linear trend model for this time series. Also, interpret the R2 and se values.b. Provide an indication of the typical
The file P12_10.xlsx contains the daily closing prices of Walmart stock for a one-year period. Does a linear or exponential trend fit these data well? If so, estimate and interpret the best trend model for this time series. Also, interpret the R2 and se values.
The file P12_11.xlsx contains monthly values of the U.S. national debt (in dollars) from 1993 to early 2010. Fit an exponential growth curve to these data. Write a short report to summarize your findings. If the U.S. national debt continues to rise at the exponential rate you find, approximately
The file P12_12.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future.a. Explain briefly
The file P12_13.xlsx contains quarterly data on GDP. a. Look at a time series plot of GDP. Does it suggest a linear relationship; an exponential relationship?b. Use regression to estimate a linear relationship between GDP and Time (starting with 1 for Q1-1966). Interpret the associated constant
The file P03_30.xlsx gives monthly exchange rates (units of local currency per U.S. dollar) for nine currencies. Technical analysts believe that by charting past changes in exchange rates, it is possible to predict future changes of exchange rates. After analyzing the autocorrelations for these
The unit sales of a new drug for the first 25 months after its introduction to the marketplace are recorded in the file P12_15.xlsx.a. Estimate a linear trend equation using the given data. How well does the linear trend fit these data? Are the residuals from this linear trend model random?b. If
The file P12_16.xlsx contains the daily closing prices of American Express stock for a one-year period. a. Use the random walk model to forecast the closing price of this stock on the next trading day.b. You can be about 95% certain that the forecast made in part a will be off by no more than how
The closing value of the AMEX Airline Index for each trading day during a one-year period is given in the file P12_17.xlsx.a. Use the random walk model to forecast the closing price of this stock on the next trading day.b. You can be about 68% certain that the forecast made in part a will be off by
The file P12_18.xlsx contains the daily closing prices of Chevron stock for a one-year period.a. Use the random walk model to forecast the closing price of this stock on the next trading day.b. You can be about 99.7% certain that the forecast made in part a will be off by no more than how many
The closing value of the Dow Jones Industrial Average for each trading day for a one-year period is provided in the file P12_19.xlsx.a. Use the random walk model to forecast the closing price of this index on the next trading day.b. Would it be wise to use the random walk model to forecast the
Continuing the previous problem, consider the differences between consecutive closing values of the Dow Jones Industrial Average for the given set of trading days. Do these differences form a random series? Demonstrate why or why not.
The closing price of a share of J.P. Morgan’s stock for each trading day during a one-year period is recorded in the file P12_21.xlsx.a. Use the random walk model to forecast the closing price of this stock on the next trading day.b. You can be about 68% certain that the forecast made in part a
The purpose of this problem is to get you used to the concept of autocorrelation in a time series. You could do this with any time series, but here you should use the series of Walmart daily stock prices in the file P12_10.xlsx.a. First, do it the quick way. Use the Autocorrelation procedure in
Consider a random walk model with the following equation: Yt = Yt -1 + 500 9 et, where et is a normally distributed random series with mean 0 and standard deviation 10.a. Use Excel to simulate a time series that behaves according to this random walk model.b. Use the time series you constructed in
The file P12_24.xlsx contains the daily closing prices of Procter & Gamble stock for a one-year period. Use only the 2003 data to estimate the trend component of the random walk model. Next, use the estimated random walk model to forecast the behavior of the time series for the 2004 dates in the
Consider the Consumer Price Index (CPI), which provides the annual percentage change in consumer prices. The data are in the file P02_19.xlsx. a. Find the first six autocorrelations of this time series.b. Use the results of part a to specify one or more promising auto regression models. Estimate
The Consumer Confidence Index (CCI) attempts to measure people’s feelings about general business conditions, employment opportunities, and their own income prospects. The file P02_20.xlsx contains the annual average values of the CCI.a. Find the first six autocorrelations of this time series.b.
Consider the proportion of Americans under the age of 18 living below the poverty level. The data are in the file P02_44.xlsx.a. Find the first six autocorrelations of this time series.b. Use the results of part a to specify one or more promising auto regression models. Estimate each model with the
The file P02_25.xlsx contains monthly values of two key interest rates, the federal funds rate and the prime rate.a. Specify one or more promising auto regression models based on autocorrelations of the federal funds rate series. Estimate each model with the available data. Which model provides the
The file P02_24.xlsx contains time series data on the percentage of the resident population in the United States who completed four or more years of college. a. Specify one or more promising auto regression models based on autocorrelations of this time series. Estimate each model with the available
Consider the average annual interest rates on 30-year fixed mortgages in the United States. The data are recorded in the file P02_21.xlsx.a. Specify one or more promising auto regression models based on autocorrelations of this time series. Estimate each model with the available data. Which model
The file P12_31.xlsx lists the monthly unemployment rates for several years. A common way to forecast time series is by using regression with lagged variables. a. Predict future monthly unemployment rates using some combination of the unemployment rates for the last four months. For example, you
The unit sales of a new drug for the first 25 months after its introduction to the marketplace are recorded in the file P12_15.xlsx. Specify one or more promising auto regression models based on autocorrelations of this time series. Estimate each model with the available data. Which model provides
The file P12_02.xlsx contains the weekly sales at a local bookstore for each of the past 25 weeks.a. Specify one or more promising auto regression models based on autocorrelations of this time series. Estimate each model with the available data. Which model provides the best fit to the data?b. What
The file P12_24.xlsx contains the daily closing prices of Procter & Gamble stock for a one-year period.a. Use only the 2003 data to estimate an appropriate auto regression model.b. Next, use the estimated auto regression model from part a to forecast the behavior of this time series for the 2004
The file P12_16.xlsx contains the daily closing prices of American Express stock for a one-year period. a. Using a span of 3, forecast the price of this stock for the next trading day with the moving average method. How well does this method with span 3 forecast the known observations in this
The closing value of the AMEX Airline Index for each trading day during a one-year period is given in the file P12_17.xlsx.a. How well does the moving average method track this series when the span is 4; when the span is 12?b. Using the more appropriate span, forecast the closing value of this
The closing value of the Dow Jones Industrial Average for each trading day during a one-year period is provided in the file P12_19.xlsx.a. Using a span of 2, forecast the price of this index on the next trading day with the moving average method. How well does the moving average method with span 2
The file P12_10.xlsx contains the daily closing prices of Walmart stock during a one-year period. Use the moving average method with a carefully chosen span to forecast this time series for the next three trading days. Defend your choice of the span used.
The Consumer Confidence Index (CCI) attempts to measure people’s feelings about general business conditions, employment opportunities, and their own income prospects. The file S02_20.xlsx contains the annual average values of the CCI. Use the moving average method with a carefully chosen span to
The file S02_28.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your
Consider a random walk model with the following equation: Yt = Yt - 1 + et, where et is a random series with mean 0 and standard deviation 1. Specify a moving average model that is equivalent to this random walk model. In particular, what is the appropriate span in the equivalent moving average
Consider the airline ticket data in the file S12_01.xlsx. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think should be used for forecasting? Why?b. Use simple exponential smoothing to forecast these data, using no holdout period
Consider the applications for home mortgages data in the file S12_04.xlsx.a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think should be used for forecasting? Why?b. Use simple exponential smoothing to forecast these data, using no
Consider the American Express closing price data in the file S12_16.xlsx. Focus only on the closing prices. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think should be used for forecasting? Why?b. Use Holt’s exponential
Consider the poverty level data in the file S02_44.xlsx.a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think should be used for forecasting? Why?b. Use simple exponential smoothing to forecast these data, using no holdout period
An automobile dealer is using Holt’s method to forecast weekly car sales. Currently, the level is estimated to be 50 cars per week, and the trend is estimated to be six cars per week. During the current week, 30 cars are sold. After observing the current week’s sales, forecast the number of
You have been assigned to forecast the number of aircraft engines ordered each month from an engine manufacturing company. At the end of February, the forecast is that 100 engines will be ordered during April. Then during March, 120 engines are actually ordered.a. Using α = 0.3, determine a
Simple exponential smoothing with α = 0.3 is being used to forecast sales of SLR (single lens reflex) cameras at an appliance store. Forecasts are made on a monthly basis. After August camera sales are observed, the forecast for September is 100 cameras. a. During September, 120 cameras are sold.
Holt’s method assumes an additive trend. For example, a trend of five means that the level will increase by five units per period. Suppose that there is actually a multiplicative trend. For example, if the current estimate of the level is 50 and the current estimate of the trend is 1.2, the
A version of simple exponential smoothing can be used to predict the outcome of sporting events. To illustrate, consider pro football. Assume for simplicity that all games are played on a neutral field. Before each day of play, assume that each team has a rating. For example, if the rating for the
The University Credit Union is open Monday through Saturday. Winters’ method is being used to predict the number of customers entering the bank each day. After incorporating the arrivals on Monday, October 16, the seasonal indexes are: Monday, 0.90; Tuesday, 0.70; Wednesday, 0.80; Thursday, 1.1;
A local bank is using Winters’ method with α = 0.2, β = 0.1, and γ = 0.5 to forecast the number of customers served each day. The bank is open Monday through Friday. At the end of the previous week, the following seasonal indexes have been estimated: Monday, 0.80; Tuesday, 0.90; Wednesday,
Suppose that Winters’ method is used to forecast quarterly U.S. retail sales (in billions of dollars). At the end of the first quarter of 2010, the seasonal indexes are: quarter 1, 0.90; quarter 2, 0.95; quarter 3, 0.95; quarter 4, 1.20. Also, the current estimates of level and trend are 300 and
The file S02_55.xlsx contains monthly retail sales of beer, wine, and liquor at U.S. liquor stores.a. Is seasonality present in these data? If so, characterize the seasonality pattern and then de-seasonalize this time series using the ratio-to-moving-average method.b. If you decided to
Continuing the previous problem, how do your responses to the questions change if you employ Winters’ method to handle seasonality in this time series? Explain. Which forecasting method do you prefer, Winters’ method or one of the methods used in the previous problem? Defend your choice.
The file S12_56.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers).a. Is seasonality present in these data? If so, characterize the seasonality
The file S12_57.xlsx consists of the monthly retail sales levels of U.S. gasoline service stations.a. Is there a seasonal pattern in these data? If so, how do you explain this seasonal pattern? Also, if necessary, de-seasonalize these data using the ratio-to-moving-average method.b. Forecast this
The number of employees on the payroll at a food processing plant is recorded at the start of each month. These data are provided in the file S12_03.xlsx.a. Is there a seasonal pattern in these data? If so, how do you explain this seasonal pattern? Also, if necessary, de-seasonalize these data
The file S12_59.xlsx contains total monthly U.S. retail sales data. Compare the effectiveness of Winters’ method with that of the ratio-to-moving-average method in de-seasonalizing this time series. Using the de-seasonalized time series generated by each of these two methods, forecast U.S. retail
Suppose that a time series consisting of six years (2005-2010) of quarterly data exhibits obvious seasonality. In fact, assume that the seasonal indexes turn out to be 0.75, 1.45, 1.25, and 0.55.a. If the last four observations of the series (the four quarters of 2010) are 2502, 4872, 4269, and
The file S12_61.xlsx contains monthly data on the number of nonfarm hires in the U.S. since 2000.a. What evidence is there that seasonality is important in this series? Find seasonal indexes (by any method you like) and state briefly what they mean.b. Forecast the next 12 months by using a linear
Quarterly sales for a department store over a six-year period are given in the file S12_62.xlsx.a. Use multiple regression to develop an equation that can be used to predict future quarterly sales. b. Letting Yt be the sales during quarter t, discuss how to estimate the following equation for this

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