Pearson eText Principles of Operations Management: Sustainability and Supply Chain Management -- Instant Access (Pearson+)
11th Edition
ISBN: 9780135639221
Author: Jay Heizer, Barry Render
Publisher: PEARSON+
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 4, Problem 46P
a)
Summary Introduction
To determine: Form linear regression relating the bar sales to guests.
Introduction:
b)
Summary Introduction
To determine: Form linear regression relating the bar sales to guests.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
1. The number of bushels of apples sold at a roadside fruit stand over a 12-day period were
PROBLEMS
as follows:
Day
Numbar Sold Day Number Sold
25
35
31
29
33
32
38
10
40
37
32
34
11
37
12
If a two-period moving average has been used to forecast sales, what were the daily
forecasts starting with the forecast for day 3?
If a four-period moving average has been used, what were the forecasts for eacn uay
starting with day 5?
Plot the original data and each set of forecasts on the same graph. Which forecast
has the greater tendency to smooth? Which forecast has the better ability to respond
quickly to changes?
What does use of the term sales instead of demand imply?
b.
C.
2. If exponential smoothing with a = .4 had been used to forecast daily sales for apples in
Problem 1, determine what the daily forecasts would have been. Then, plot the original
data, the exponential forecasts, and a set of naive forecasts on the same graph. Based
on a visual comparison, is the naive more accurate or…
The manager of the Salem police department motor poolwants to develop a forecast model for annual maintenanceon police cars based on mileage in the past year and age ofthe cars. The following data have been collected for eightdifferent cars:
a. Using Excel develop a multiple regression equationfor these data.b. What is the coefficient of determination for thisregression equation?c. Forecast the annual maintenance cost for a police carthat is four years old and will be driven 10,000 miles inone year.
Happy Lodge Ski Resorts tries to forecast monthlyattendance. Th e management has noticed a direct relationshipbetween the average monthly temperature and attendance.(a) Given fi ve months of average monthly temperatures andcorresponding monthly attendance, compute a linearregression equation of the relationship between the two.If next month’s average temperature is forecast to be 45degrees, use your linear regression equation to develop aforecast.
(b) Compute a correlation coefficient for the data anddetermine the strength of the linear relationship betweenaverage temperature and attendance. How good apredictor is temperature for attendance?
Chapter 4 Solutions
Pearson eText Principles of Operations Management: Sustainability and Supply Chain Management -- Instant Access (Pearson+)
Ch. 4 - Ethical Dilemma We live in a society obsessed with...Ch. 4 - What is a qualitative forecasting model, and when...Ch. 4 - Identify and briefly describe the two general...Ch. 4 - Identify the three forecasting time horizons....Ch. 4 - Briefly describe the steps that are used to...Ch. 4 - A skeptical manager asks what medium-range...Ch. 4 - Explain why such forecasting devices as moving...Ch. 4 - What is the basic difference between a weighted...Ch. 4 - What three methods are used to determine the...Ch. 4 - Research and briefly describe the Delphi...
Ch. 4 - What is the primary difference between a...Ch. 4 - Define time series.Ch. 4 - What effect does the value of the smoothing...Ch. 4 - Explain the value of seasonal indices in...Ch. 4 - Prob. 14DQCh. 4 - In your own words, explain adaptive forecasting.Ch. 4 - Prob. 16DQCh. 4 - Explain, in your own words, the meaning of the...Ch. 4 - Prob. 18DQCh. 4 - Give examples of industries that are affected by...Ch. 4 - Prob. 20DQCh. 4 - Prob. 21DQCh. 4 - CEO John Goodale, at Southern Illinois Power and...Ch. 4 - The following gives the number of pints of type B...Ch. 4 - a) Plot the above data on a graph. Do you observe...Ch. 4 - Refer to Problem 4.2. Develop a forecast for years...Ch. 4 - A check-processing center uses exponential...Ch. 4 - The Carbondale Hospital is considering the...Ch. 4 - The monthly sales for Yazici Batteries, Inc., were...Ch. 4 - Prob. 7PCh. 4 - Daily high temperatures in St. Louis for the last...Ch. 4 - Lenovo uses the ZX-81 chip in some of its laptop...Ch. 4 - Data collected on the yearly registrations for a...Ch. 4 - Use exponential smoothing with a smoothing...Ch. 4 - Prob. 12PCh. 4 - At you can see in the following table, demand for...Ch. 4 - Prob. 14PCh. 4 - Refer to Solved Problem 4.1 on page 144. a) Use a...Ch. 4 - Prob. 16PCh. 4 - Prob. 17PCh. 4 - Prob. 18PCh. 4 - Income at the architectural firm Spraggins and...Ch. 4 - Resolve Problem 4.19 with = .1 and =.8. Using...Ch. 4 - Prob. 21PCh. 4 - Refer to Problem 4.21. Complete the trend-adjusted...Ch. 4 - Prob. 23PCh. 4 - The following gives the number of accidents that...Ch. 4 - In the past, Peter Kelles tire dealership in Baton...Ch. 4 - George Kyparisis owns a company that manufactures...Ch. 4 - Attendance at Orlandos newest Disneylike...Ch. 4 - Prob. 28PCh. 4 - The number of disk drives (in millions) made at a...Ch. 4 - Prob. 30PCh. 4 - Emergency calls to the 911 system of Durham, North...Ch. 4 - Using the 911 call data in Problem 4.31, forecast...Ch. 4 - Storrs Cycles has just started selling the new...Ch. 4 - Prob. 35PCh. 4 - Prob. 36PCh. 4 - Prob. 37PCh. 4 - Prob. 38PCh. 4 - Prob. 39PCh. 4 - Prob. 40PCh. 4 - Prob. 41PCh. 4 - Prob. 42PCh. 4 - Mark Gershon, owner of a musical instrument...Ch. 4 - Prob. 44PCh. 4 - Cafe Michigans manager, Gary Stark, suspects that...Ch. 4 - Prob. 46PCh. 4 - The number of auto accidents in Athens, Ohio, is...Ch. 4 - Rhonda Clark, a Slippery Rock, Pennsylvania, real...Ch. 4 - Accountants at the Tucson firm, Larry Youdelman,...Ch. 4 - Prob. 50PCh. 4 - Using the data in Problem 4.30, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - Prob. 53PCh. 4 - Dave Fletcher, the general manager of North...Ch. 4 - Prob. 55PCh. 4 - Prob. 56PCh. 4 - Prob. 57PCh. 4 - Sales of tablet computers at Ted Glickmans...Ch. 4 - The following are monthly actual and forecast...Ch. 4 - Prob. 1CSCh. 4 - Prob. 2CSCh. 4 - Prob. 3CSCh. 4 - Prob. 1.1VCCh. 4 - Prob. 1.2VCCh. 4 - Using Perezs multiple-regression model, what would...Ch. 4 - Prob. 1.4VCCh. 4 - Prob. 2.1VCCh. 4 - Prob. 2.2VCCh. 4 - Prob. 2.3VCCh. 4 - Prob. 2.4VCCh. 4 - Prob. 2.5VC
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.Similar questions
- Under what conditions might a firm use multiple forecasting methods?arrow_forwardThe owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?arrow_forwardThe Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?arrow_forward
- The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.arrow_forwardPractice Problem: Usins the data on a hospital’s revenue: (1) Use simple exponential smoothing to make predictions for the hospital’s revenues during the next four quarters with α = 0.30. (2) Use Trend-Adjusted Exponential Smoothing(i.e. Holt’s method) to make forecasts for the hospital’s revenues during the next four quarters. Assume α = 0.05, β = 0.65, initial revenue forecast = 1209285.75 and initial trend forecast = 15714. (3) Using least-squares regression with seasonal index decomposing method, forecast the hospital’s revenues during the next four quarters.arrow_forwardWhat forecasting technique makes use of written surveys or telephone interviews? Historical analogy, Delphi method, Marketing research, Ad hoc forecasting, or Collaborative forecasting? 2 Which qualitative forecasting technique was developed to ensure that the input from every participant in the process is weighted equally? Historical analogy, Delphi method, Marketing research, Ad hoc forecasting, or Collaborative forecasting? 3 When forecasting demand for new products, sometimes firms will use demand data from similar existing products to help forecast demand for the new product. What technique is this an example of? Historical analogy, Delphi method, Marketing research, Ad hoc forecasting, or Collaborative forecastingarrow_forward
- The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized below. Month Nov 2019 Dec 2019 Demand 45 48 Jan 2020 50 Feb 2020 Mar 2020 Apr 2020 42 46 51 Consider the following three forecasting methods: • Two-month weighted moving average, with weights 6 and 2 (more weight assigned to more recent data) Exponential smoothing with a = 0.7. Let the initial forecast for Nov 2019 be 46. • A trend line projection in the form ŷ = a+bx . To simplify computations, transform the value of x (time) to simpler numbers – designate Nov 2019 as x=1, Dec 2019 as x= 2, etc. (a ) For each of the above methods, forecast the demand of Apple iPad for May 2020. (b) Consider only the two-month weighted moving average method, compute the MAD measure and the MSE measure using the data from Jan 2020. (c) Use the trend line to forecast the demand of Apple iPad for Dec 2020. Give your opinion regarding the reliability of the forecast.arrow_forward4. A local moving company has collected data on the number of moves they have been asked to perform over the past two years. Moving is highly seasonal, so the owner/operator, who is both burly and highly educated, decides to apply the multiplicative seasonal method to forecast the number of customers for the coming year. The equation for the trend line of yearly sales is F1 = 100 + 60t. Please forecast demand for each quarter in Year 3. (Round the forecasts to whole numbers and show all calculations t Complete the table below and forecast the sales of Year 3 by quarter. Copy the table below, paste to the answer box and fill in your answers. You need to take a picture of your work and upload the picture in next question. Year 1 Year 2 Year 3 Quarter Demand Quarter Demand Quarter Demand 1 28 1 45 1 43 60 2 120 140 4 49 55 4 Total 240 Total 300 Total Average Average Average For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).arrow_forwardThe following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 a) The forecasted demand for the week of October 12 using a 3-week moving average = 375 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.15, 0.25, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = 375.45 pints (round your response to two deamal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) c) If the forecasted demand for the week of August 31 is 360 and a = 0.30, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). Week Of Pints Used 360 389 410 381 366…arrow_forward
- 1. Compute three-period moving average and forecasting errors for the following time series: Period (t): 1 2 3 4 5 6 7 8 9 10 Value (Xt): 15 27 20 14 25 11 15 20 25 22 compute mean absolute deviation (MAD) and mean square error (MSE) and interpret the obtained results. 2. What do you understand by the analysis of time series, explain in details? Give a brief introduction of forecasting.arrow_forward3) Seasonality: The following data represent dinner sales at a busy restaurant. Use linear regression to predict sales for each day of week 5 and the total sales for week 5. Estimate the percentage of weekly sales that occur over the weekend (include Friday, Saturday, and Sunday). Finally, determine which days of the week are increasing and decreasing in sales, using the slopes of the LR lines. Week Mon Wed Fri Sat Sun Tue 177 170 Thu 190 Total 270 152 180 321 386 166 218 203 402 427 167 333 357 229 3 158 170 170 205 163 173 158 225 349 433 212 a) Graph the seasonal data and attach the graph to this page. b) Determine the slope for each day of the week. Mon Tue Wed Thu Fri Sat Sun Total Slope c) Estimate the percentage of weekend sales in week 5: d) For which day are sales increasing the fastest? e) For which day are sales decreasing the fastest?arrow_forwardThe monthly demand for units manufactured by the Acme Rocket Company has been as follows: a. Use the exponential smoothing method to forecast the number of units for June to January. Theinitial forecast for May was 105 units; a = 0.2.b. Calculate the absolute percentage error for each month from June through December and theMAD and MAPE of forecast error as of the end of December.c. Calculate the tracking signal as of the end of December. What can you say about the performanceof your forecasting method?arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,Contemporary MarketingMarketingISBN:9780357033777Author:Louis E. Boone, David L. KurtzPublisher:Cengage LearningMarketingMarketingISBN:9780357033791Author:Pride, William MPublisher:South Western Educational Publishing
Practical Management Science
Operations Management
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:Cengage,
Contemporary Marketing
Marketing
ISBN:9780357033777
Author:Louis E. Boone, David L. Kurtz
Publisher:Cengage Learning
Marketing
Marketing
ISBN:9780357033791
Author:Pride, William M
Publisher:South Western Educational Publishing
Single Exponential Smoothing & Weighted Moving Average Time Series Forecasting; Author: Matt Macarty;https://www.youtube.com/watch?v=IjETktmL4Kg;License: Standard YouTube License, CC-BY
Introduction to Forecasting - with Examples; Author: Dr. Bharatendra Rai;https://www.youtube.com/watch?v=98K7AG32qv8;License: Standard Youtube License