59. C. influential A. quantity, percentage The primary method for associative forecasting is: A. sensitivity analysis B. regression analysis C. simple moving averages D. centered moving averages E. exponential smoothing. hk B*Uph h B*ph hK1 B*CJ aJ ph j hk B*Uph hK1 B*ph hd$ B*ph h hK1 B*ph $ ! Organizations that are capable of responding quickly to changing requirements can use a shorter forecast. 107 manager is using exponential smoothing to predict merchandise returns at a suburban branch of a C. Control Charts C. eliminating historical data / 2 A. E. 22. 124 is the forecast for this year using the least squares trend line for these data? C. quantity, quantity smoothed (averaged) values of time series data. Ed.). 47. True or false? B. expert opinions 2023, OReilly Media, Inc. All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners. E. none of the above. B. 82. E. Mean Absolute Deviation (MAD), The primary method for associative forecasting is: Delphi technique: exponential smoothing: Mean: Squared Error (MSE): Mean Absolute Deviation (MAD): leading variable. True False, The naive forecast is limited in its application to series that reflect no trend or seasonality. the following historical data: Copyright 2023 StudeerSnel B.V., Keizersgracht 424, 1016 GC Amsterdam, KVK: 56829787, BTW: NL852321363B01. The sales staff is least affected by changing customer needs. regression analysis Difficulty: Medium Stevenson - Chapter 03 #87TLO: 3 Taxonomy: Knowledge Farber/Larson Sullivan Triola Triola Solutions Triola D. centered moving average In exponential smoothing, an alpha of .30 will cause a forecast to react more quickly to a large error than True False, Forecasting techniques that are based on time series data assume that future values of the series will duplicate action to be taken to meet that demand. ? department store chain. Forecasts based on judgment and opinion don't include. True False, Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for What was the mean absolute deviation (MAD) for these forecasts?A.100B.200C.400D.500E.800 The dean of a school of business is forecasting total student enrollment for this year's summer session classes based on the following historical data: *141.What is this year's forecast using the naive approach?A.2,000B.2,200C.2,800D.3,000E.none of the above *142.What is this year's forecast using a three-year simple moving average?A.2,667B.2,600C.2,500D.2,400E.2,333 *143.What is this year's forecast using exponential smoothing with alpha = .4, if last year's smoothed forecast was 2600?A.2,600B.2,760C.2,800D.3,840E.3,000 144.What is the annual rate of change (slope) of the least squares trend line for these data?A.0B.200C.400D.180E.360 145.What is this year's forecast using the least squares trend line for these data?A.3,600B.3,500C.3,400D.3,300E.3,200 The owner of Darkest Tans Unlimited in a local mall is forecasting this month's (October's) demand for the one new tanning booth based on the following historical data: *146.What is this month's forecast using the naive approach?A.100B.160C.130D.140E.120 *147.What is this month's forecast using a four-month weighted moving average with weights of .4, .3, .2, and .1?A.120B.129C.141D.135E.140 *148.What is this month's forecast using exponential smoothing with alpha = .2, if August's forecast was 145?A.144B.140C.142D.148E.163 149.What is the monthly rate of change (slope) of the least squares trend line for these data?A.320B.102C.8D.-0.4E.-8 150.What is this month's forecast using the least squares trend line for these data?A.1,250B.128.6C.102D.158E.164 151.Which of the following mechanisms for enhancing profitability is most likely to result from improving short term forecast performance?A.increased inventoryB.reduced flexibilityC.higher-quality productsD.greater customer satisfactionE.greater seasonality 152.Which of the following changes would tend to shorten the time frame for short term forecasting?A.bringing greater variety into the product mixB.increasing the flexibility of the production systemC.ordering fewer weather-sensitive itemsD.adding more special-purpose equipmentE.none of the above 153.Which of the following helps improve supply chain forecasting performance?A.contracts that require supply chain members to formulate long term forecastsB.penalties for supply chain members that adjust forecastsC.sharing forecasts or demand data across the supply chainD.increasing lead times for critical supply chain membersE.increasing the number of suppliers at critical junctures in the supply chain 154.Inaccuracies in forecasts along the supply chain lead to:A.shortages or excesses of materialsB.reduced customer serviceC.excess capacityD.missed deliveriesE.all of the above 155.Which of the following is the most valuable piece of information the sales force can bring into forecasting situations?A.what customers are most likely to do in the futureB.what customers most want to do in the futureC.what customers' future plans areD.whether customers are satisfied or dissatisfied with their performance in the pastE.what the salesperson's appropriate sales quota should be Essay Questions *156.What is this year's forecast using the naive approach? *157.What is this year's forecast using a four-year simple moving average? *158.What is this year's forecast using exponential smoothing with alpha = .25, if last year's smoothed forecast was 45? 159.What are this and next year's forecasts using the least squares trend line for these data? 160.What is this year's forecast using trend adjusted (double) smoothing with alpha = 0.2 and beta = 0.1, if the forecast for last year was 56, the forecast for two years ago was 46, and the trend estimate for last year's forecast was 7? 161.What is the centered moving average for spring two years ago? 162.What is the spring's seasonal relative? 163.What is the linear regression trend line for these data (t = 0 for spring, three years ago)? 164.What is this year's seasonally adjusted forecast for each season? Chapter 03 - Forecasting 3- PAGE 18 O Q Get full access to Operations Management: Sustainability and Supply Chain Management, Twelfth Edition and 60K+ other titles, with a free 10-day trial of O'Reilly. E. none of the above, Given forecast errors of - 5, - 10, and +15, the MAD is: ago was 750? C. 21, What is the forecast for this year using the naive approach? 83. See Answer Question: toring Enal The primary method for associative forecasting is: 2 Multiple Choice 36 sensitivity analysis exponential smoothing. Once accepted by managers, forecasts should rarely be overridden. 11. C. measure forecast accuracy E. predictor variables, A. regression coefficient For new products in a strong growth mode, a low alpha will minimize forecast errors when using Variations around the line are random. Develop a forecast for the next period, given the data below, using a 3-period moving average. But we use any potential "cause-and-effect" - Selection from Operations Management: Sustainability and Supply Chain Management, Twelfth Edition [Book] (Gerard J. Tortora), In trend-adjusted exponential smoothing, the trend adjusted forecast (TAF) consists of: regression analysis. Larger value for (alpha constant) result in more responsive models. B. In exponential smoothing, an alpha of 1 will generate the same forecast that a nave forecast would yield. ago was 16,000? True False, Bias is measured by the cumulative sum of forecast errors. 18, Get Mark Richardss Software Architecture Patterns ebook to better understand how to design componentsand how they should interact. Given the following historical data, what is the simple three-period moving average forecast for period 6? 99. The best forecast is not necessarily the most accurate. Forecasts based on time series (historical) data are referred to as associative forecasts. Using the latest observation in a sequence of data to forecast the next period is: 8. C. establish a time horizon c. is a forecast that is classified on a numerical scale from 1 (poor quality) to 10 (perfect quality). B. MAPE C. an exponentially smoothed forecast D. an associative forecast B. regression analysis (a) executive opinions(b) sales force opinions(c) the Delphi method(d) time series analysis, A series of questionnaire is used in(a) expert opinion(b) sales force opinion(c) time series analysis(d) the Delphi method, In which of the following forecasting techniques, the last period actual demand is used as the forecasting for the current period? A. estimate of accuracy Is the forecast performing as well as it might? B. salesperson opinion E. prevent hurt feelings, A. MSEs A. True False, The purpose of the forecast should be established first so that the level of detail, amount of resources, and exponential smoothing. C. MAPE False Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for individual items don't include as many influencing factors. Explain. Convert each error into an absolute value then average. D. 65. following historical data: What is the forecast for this year using the naive approach? E. average people, A. Exponential smoothing 18,750: 21,000: 22,800: 19,500: 22,000. Unlike time-series forecasting, associative forecasting models usually consider several variables that are related to the quantity being predicted. A. P1=V73: P2=V68: P3=V65: P4=72: P5=67. True False, Correlation measures the strength and direction of a relationship between variables. Market Survey The association between two variations is summarized in the correlation coefficient. 58. Which of the following smoothing constants would make an exponential smoothing forecast equivalent to. C. quantity, quantity Version 1 8 sensitivity analysis. 3: 2: 4: 2: 5: 1. Variations around the line are random. False Organizations that are capable of responding quickly to changing requirements can use a shorter forecast horizon and D. predicted variable Simple exponential smoothing is being used to forecast demand. E. predictor regression, A. avoid premature consensus (bandwagon effect) This year's forecast would be last year's enrollment. Accuracy in forecasting can be measured by? @ A B ~qdU hS hK1 B*CJ aJ ph jiM hk B*Uph j- hk B*Uph hRI B*ph hK1 B*CJ aJ ph j hk B*Uph h#k B*CJ aJ ph j5 hk B*Uph hQG B*ph hQG hK1 B*CJ aJ ph j hk B*Uph hK1 B*CJ aJ ph hK1 B*ph hQG hK1 B*CJ aJ ph ! E. all of the above. 18,750: 21,000: 22,800: 19,500: 22,000. action to the manager. Given an actual demand of 59, a previous forecast of 64, and an alpha of .3, what would the forecast for the 92. 102 the following historical data and weights of .5, .3, and .2, what is the three-period moving average The primary method for associative forecasting is: simple moving averages. 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D. trend data: Copyright 2023 StudeerSnel B.V., Keizersgracht 424, 1016 GC Amsterdam, KVK: 56829787, BTW: NL852321363B01, Student: ___________________________________________________________________________, individual items don't include as many in, Introduction to Time Series Analysis and Forecasting. E. Strategies, Gradual, long-term movement in time series data is called: Forecasts help managers plan both the system itself and provide valuable information for using the system. False Gradual, long-term movement in time series data is called_____ trend 111 new car dealer has been using exponential smoothing with an alpha of .2 to forecast weekly new car He needs to forecast the D. requires only last period's forecast and actual data D. low cost When new products or services are introduced, focus forecasting models are an attractive option. The naive approach to forecasting requires a linear trend line. E. objective and subjective components, The degree of management involvement in short range forecasts is: A consumer survey is an easy and sure way to obtain accurate input from future costumers since most people enjoy participating in surveys. A. A. 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The previous forecast of 66 turned out to be A. avoid premature consensus (bandwagon effect) True False, If a pattern appears when a dependent variable is plotted against time, one should use time series analysis Simply responding to demand is a reactive approach. data. C. eliminating historical data C. Mean Squared Error (MSE) Forecasts based on an average tend to exhibit less variability than the original data. Which of the following might be used to indicate the cyclical component of a forecast? A. True False, Exponential smoothing adds a percentage (called alpha) of last period's forecast to estimate next period's D. MTM number of students who will seek appointments. Use linear regression to develop a predictive model for demand for burial vaults based on sales of caskets. Forecasts are seldom accurate. A) Predict demand for July using each of these methods: 120 manager wants to choose one of two forecasting alternatives. D. 101. D. seasonally adjust the forecast D. providing accuracy in forecasts A. cost and time horizon C. Historical data is available on which to base the forecast. Forecasting techniques generally assume an existing causal system that will continue to exist in the future. 116 the following data, develop a linear regression model for y as a function of x. Which phrase most closely describes the Delphi technique? B. Deviations around the line are normally distributed. False.. A forecast based on the previous forecast plus a percentage of the forecast error is: 10. C. the ability to attribute the pattern to a cause C. B. increased Forecasting techniques generally assume an existing causal system that will continue to exist in the future. 49. Forecasts are rarely perfect. A. The shorter the forecast period, the more accurately the forecasts tend to track what actually happens. Detecting non-randomness in errors can be done using: D. Correlation Coefficients forecast was -150? Top forecasting methods include Qualitative Forecasting (Delphi Method, Market Survey, Executive Opinion, Sales Force Composite) and Quantitative Forecasting (Time Series and Associative Models). But we use any potential cause-and-effect variable as x. E. qualitative, quantitative, Which technique is used in computing seasonal relatives? What is the forecast In order to increase the responsiveness of a forecast made using the moving average technique, the number E. Delphi methods, A. capacity planning for individual items don't include as many influencing factors. B.. B. B. Forecasting is the use of historic data to determine the direction of future trends. Case Study: Where did the first Catholic Mass take place in the Philippines? quickly to forecast errors? D. be able to replicate results centered moving averages. C. 51. Which term most closely relates to associative forecasting techniques?Predictor variable: Delphi technique: expert opinions: consumer survey: time series data. Forecast deliveries for period for July if t = 0 in April of this year? 101 the following historical data, what is the simple three-period moving average forecast for period 6? Predictor variable.. _ a b \ ^ _ c d e h B*ph hK1 B*H*ph h hK1 B*ph j hk B*Uph hd$ B*ph hP B*CJ aJ ph hK1 >*B*ph hK1 B*ph hP B*ph hK1 5B*CJ \aJ ph hK1 B*CJ aJ ph 7 O Q Associative Forecasting Methods: Regression and Correlation Analysis Student Tip We now deal with the same mathematical model that we saw earlier, the least-squares method. (Associative forecasting methods: Regression and correlation, moderate) Explain, in your own words, the meaning of the coefficient of determination. D. centered moving average D. quantity and quality horizon and therefore benefit from more accurate forecasts. 91. 22. Forecasts based on time series (historical) data are referred to as associative forecasts. E. 108. accuracy level can be understood. D. select a forecasting model MAPs Which of the following smoothing constants would make an exponential smoothing forecast equivalent toa naive forecast? 123 is the forecast for this year using exponential smoothing with alpha = 0, if the forecast for two years represent smoothed (averaged) values of time series data. f PRESENTATION OUTLINE COLLEGE OF BUSINESS EDUCATION f INTENDED LEARNING OUTCOMES List features common to all forecasts. C. Mean Squared Error (MSE) The previous forecast of 66 turned out to be four units less than actual demand. the forecast for last year was 310, the forecast for two years ago was 430, and the trend estimate for last year's Which of the following corresponds to the predictor variable in simple linear regression? B. True False, Bias exists when forecasts tend to be greater or less than the actual values of time series. pattern. / 0 UC bjbjZZ Dh 8h 8h ; 6 + + + + + ? D. trend 86. B. 40, He needs to forecast the number of students who will seek appointments. 34. A. executive opinions C. the old forecast adjusted by a trend factor The primary method for associative forecasting is: sensitivity analysis B. regression analysis C. simple moving averages D. centered moving averages. E. Strategies, A. seasonal variation C. consumer surveys A. reactive Explain why forecasts are generally wrong. True The time series techniques involve identification of explanatory variables that can be used to predict future demand. D. competition The primary method for associative forecasting is: A. sensitivity analysis B.regression analysis C. simple moving averages True False, Forecasting techniques such as moving averages, exponential smoothing, and the naive approach all represent Forecasts depend on the rules of the game remaining reasonably constant. B. budgeting D. positive correlation E. 65. Become Premium to read the whole document. Given the forecast errors of 5, 0, -4, and 3, what is the mean absolute deviation? for last year's forecast was 1,500? Over the past 8 periods, demand has been as.
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