Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predictions from this method against the original data. c. What are the forecasts for each quarter in year 4 using this technique?
> WVTU is a television station that has 20 thirty-second advertising slots during their regularly scheduled programming each evening. The station is now selling advertising for the first few days in November. They could sell all the slots immediately for $
> Hometown Insurance sells 10-year annuities to retirees who are looking for stable sources of investment income. Hometown invests the annuity funds it receives in an equity index fund with annual returns that are normally distributed with a mean of 9% and
> Branch banks must keep enough money on hand to satisfy customers’ cash demands. Suppose that the daily demand for cash at a branch of University Bank follows a lognormal distribution with means and standard deviation summarized as follo
> Under what condition(s) is it appropriate to use simulation to analyze a model? That is, what characteristics should a model possess in order for simulation to be used?
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method versus the
> Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to determine the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the origi
> Create a double moving average model (with k 5 4) for the data set. a. Prepare a line graph comparing the double moving average predictions against the original data. b. What are the forecasts for the next 2 years using this technique?
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr
> Mac Brown knew something had to change. As the new Vice President of Sales & Marketing for the PB Chemical Company, Mac understood that when you sell a commodity product, where there is minimal difference between the quality and price, customer service a
> Use Solver to determine the weights for a three-period weighted moving average that minimizes the MSE for the data set. a. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the
> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti
> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against
> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr
> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti
> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against
> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> A used-car broker needs to transport his inventory of cars from locations 1 and 2 in Figure 5.39 to used-car auctions being held at locations 4 and 5. The costs of transporting cars along each of the routes are indicated on the arcs. The trucks used to c
> Use regression to estimate the parameters of a 6th order polynomial model for this data. That is, estimate the least squares estimates for the parameters in the following estimated regression equation: a. What are the optimal values of b0, b1, â
> Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the original data. b. Do the moving averages tend to overestimate or underestimate the actual da
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against the
> Create a Double Moving Average model (with k 5 4) for the data set. a. Prepare a line graph comparing the Double Moving Average predictions against the original data. b. What are the forecasts for the next 2 months using this technique?
> Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to estimate the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the original
> Use Solver to determine the weights for a four-period weighted moving average on the data set that minimizes the MSE. a. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the or
> Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the original data. b. Compute the MSE for each of the two moving averages. Which appears to provi
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Use regression analysis to answer the following questions. a. Fit a linear trend model to the data set. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions ag
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against the
> In the wake of the Enron scandal two public accounting firms, Oscar Anderson (OA) and TriceMilkhouse -Loopers (TML), merged (forming OATML) and are reviewing their methods for detecting management fraud during audits. The two firms had each developed the
> Create a Double Moving Average model (with k 5 4) for the data set. a. Prepare a line graph comparing the Double Moving Average predictions against the original data. b. What are the forecasts for the next 4 months using this technique?
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr
> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against th
> Use regression analysis to fit a quadratic trend model to the data set. a. What is the estimated regression function? b. Compare the adjusted-R2 value for this model to that of the linear trend model. What is implied by this comparison? c. Prepare a line
> Use regression analysis to fit a linear trend model to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions against the original data. d. Wha
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and b. a. What are the optimal values of a and b? b. Are these values surprising? Why or why not? Questions 35 through 39 refer to
> Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to estimate the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the original
> A company has three warehouses that supply four stores with a given product. Each warehouse has 30 units of the product. Stores 1, 2, 3, and 4 require 20, 25, 30, and 35 units of the product, respectively. The per unit shipping costs from each warehouse
> Use Solver to determine the weights for a four-period weighted moving average on the data set that minimizes the MSE. a. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the or
> Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the original data. b. Compute the MSE for each of the two moving averages. Which appears to prov
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Each month, Joe’s Auto Parts uses exponential smoothing (with a 5 0.25) to predict the number of cans of brake fluid that will be sold during the next month. In June, Joe forecast that he would sell 37 cans of brake fluid during July. Joe actually sold 4
> Use regression analysis to fit an additive seasonal model with linear trend to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Interpret the parameter estimates corresponding to the indicator varia
> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against th
> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against
> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or
> Nolan Banks is an auditor for the Public Service Commission for the state of Georgia. The Public Service Commission is a government agency responsible for ensuring that utility companies throughout the state manage their operations efficiently so that th
> Baldwin Enterprises is a large manufacturing company with operations and sales divisions located in the United States and several other countries. The CFO of the organization is concerned about the amount of money Baldwin has been paying in transaction c
> Use regression analysis to fit a quadratic trend model to the data set. a. What is the estimated regression function? b. Compare the adjusted-R2 value for this model to that of the linear trend model. What is implied by this comparison? c. Prepare a line
> Use regression analysis to fit a linear trend model to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions against the original data. d. Wha
> Use regression analysis to fit an additive seasonal model with linear trend to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Interpret the parameter estimates corresponding to the indicator varia
> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the p
> A manufacturing company uses a certain type of steel rod in one of its products. The design specifications for this rod indicate that it must be between 0.353 and 0.357 inches in diameter. The machine that manufactures these rods is set up to produce the
> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti
> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against
> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or
> Use regression analysis to fit a quadratic trend model to the data set. a. What is the estimated regression function? b. Compare the adjusted-R2 value for this model to that of the linear trend model. What is implied by this comparison? c. Prepare a line
> Use regression analysis to fit a linear trend model to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions against the original data. d. Wha
> Use Solver to create a Sensitivity Report for question 22 at the end of Chapter 3 and answer the following questions: a. Which of the constraints in the problem are binding? b. If the company was going to eliminate one of its products, which should it be
> Use regression analysis to answer the following questions. a. Fit a linear trend model to the data set. What is the estimated regression function? b. Interpret the R2value for your model. c. Prepare a line graph comparing the linear trend predictions aga
> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method versus the
> Create a double moving average model (with k 5 2) for the data set. a. Prepare a line graph comparing the double moving average predictions against the original data. b. What are the forecasts for the next 2 years using this technique?
> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?
> Use regression analysis to fit a linear trend model to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions against the original data. d. Wha
> What is the result of using regression analysis to estimate a linear trend model for a stationary time series?
> The manager of the commercial loan department for a bank wants to develop a rule to use in determining whether or not to approve various requests for loans. The manager believes that three key characteristics of a company’s performance
> The Royalty Gold Corporation prospects for undiscovered gold deposits around the world. The company is currently investigating a possible site on the island of Milos off the coast of Greece in the Mediterranean. When prospecting, the company drills to co
> The director of the MBA program at Salter dine University wants to develop a procedure to determine which applicants to admit to the MBA program. The director believes that an applicant’s undergraduate grade point average (GPA) and scor
> Refer to the Universal Bank example used to demonstrate the various classification techniques in this chapter. Suppose the Universal Bank data had included the home zip code for each customer. What issues might arise in using the customer’s zip code as a
> The 2000 U.S. presidential election was one of the most controversial in history with the final outcome ultimately being decided in a court of law rather than in the voting booth. At issue were the election results in Palm Beach, Florida. Palm Beach Coun
> Consider the file named EmployeeData.xlsx that accompanies this book. What errors (or potential errors) can you find in this data set?
> What would a lift chart look like for a classification technique with 100% accuracy?
> It can be argued that regression analysis and discriminate analysis both use a set of independent variables to predict the value of a dependent variable. What, then, is the difference between regression analysis and discriminate analysis?
> What is a centroid?
> Colleges and universities are often interested in identifying their peer institutions. The file named Colleges.xlsm that accompanies this book contains a number of (artificial) metrics for 307 higher education institutions in the United States. a. Use k-
> Home Basics is a home improvement retail store selling all manner of products that are needed by home owners to repair, remodel, and redecorate their homes. The management of Home Basics is analyzing buying patterns of its customers to evaluate the layou
> Explain the purpose of the training, validation, and test data sets in data mining.
> Prepare scatter plots of the values of X1 and X2 against Y. a. Do these relationships seem to be linear or nonlinear? b. Determine the parameter estimates for the regression function represented by: Ŷi 5 b0 1 b1X1i 1 b2X2i 1 b3X3i 1 b4X4i where X4i 5 X
> Roger Gallagher owns a used car lot that deals solely in used Corvettes. He wants to develop a regression model to help predict the price he can expect to receive for the cars he owns. He collected the data found in the file Corvettes.xlsx describing the
> The IRS wants to develop a method for detecting whether or not individuals have overstated their deductions for charitable contributions on their tax returns. To assist in this effort, the IRS supplied data found in the file IRS.xlsx that accompanies thi
> Use Solver to create a Sensitivity Report for question 19 at the end of Chapter 3 and answer the following questions: a. Is the solution degenerate? b. Would the solution change if the price of raisins was $2.80 per pound? c. Would the solution change if
> An accounting firm that specializes in auditing mining companies collected the data found in the file MiningAudit.xlsx that accompanies this book describing the long-term assets and long-term debt of its 12 clients. a. Prepare a scatter plot of the data.
> Members of the Roanoke Health and Fitness Club pay an annual membership fee of $250 plus $3 each time they use the facility. Let X denote the number of times a person visits the club during the year. Let Y denote the total annual cost for membership in t
> Least squares regression finds the estimated values for the parameters in a regression model to minimize ESS 5 o n i 5 1 (Yi 2 Ŷi ) 2 . Why is it necessary to square the estimation errors? What problem might be encountered if we attempt to minimize just
> Suppose the variable X is being used to predict Y using a linear regression function of the form Ŷi 5 b0 1 b1Xi. If there is no linear relation between X and Y, what is the optimal regression function (i.e., what are the optimal values of b0 and b1)? Exp
> Throughout our discussion of regression analysis, we used the Regression command to obtain the parameter estimates that minimize the sum of squared estimation errors. Suppose that we want to obtain parameter estimates that minimize the absolute value of
> Throughout our discussion of regression analysis, we used the Regression command to obtain the parameter estimates that minimize the sum of squared estimation errors. Suppose that we want to obtain parameter estimates that minimize the sum of the absolut
> Caveat Emptor, Inc. is a home inspection service that provides prospective homebuyers with a thorough assessment of the major systems in a house prior to the execution of the purchase contract. Prospective homebuyers often ask the company for an estimate
> The personnel director for a small manufacturing company has collected the data found in the file Manufacturing.xlsx describing the salary (Y) earned by each machinist in the factory along with the average performance rating (X1) over the past three year
> A cost estimator for a construction company has collected the data found in the file Construction.xlsx describing the total cost (Y) of 97 different projects and the following five independent variables thought to exert relevant influence on the total co
> Hydroxyethyl cellulose (HEC) is a gelling and thickening agent created from a molecular combination of cellulose, ethylene oxide (EO), and nitric acid. It is designed to mix with a water-based solution to increase the viscosity of the mixture. This added
> With Christmas coming, Ryan Bellison was searching for the perfect gift for his wife. After several years of marriage, Ryan leaned back in his chair at the office and tried to think of the one thing his wife has wanted during the years they pinched penni
> Chris Smith is a sports car enthusiast with a particular love for Mini Coopers. He downloaded data from eBay on completed auctions of Mini Coopers and used it to create the data set in file MiniCooper.xlsx showing the selling prices, age, mileage, and lo
> An appraiser collected the data found in file Appraiser.xlsx describing the auction selling price, diameter (in inches), and item type of several pieces of early 20th century metal tableware manufactured by a famous artisan. The item type variable is cod
