The repeated observations of demand for a product or service in the order of occurrence form a pattern known as a time series.
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The repeated observations of demand for a product or service in the order of occurrence form a pattern known as a time series.
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- What advantages does adjusted exponential smoothing have over a linear trend line for forecasted demand that exhibits a trend?Among these trend patterns, within the projection methods, choose the one that is most common when analyzing demand, and why?-Secular trend -Seasonal variation -Cyclical fluctuations -Irregular movementsGiven the following data, calculate the average demand and the standard deviation. Period Actual Demand Deviation Deviation Squared 1 1700 2 2100 3 1900 4 2200 5 2000 6 1800 7 2100 8 2300 9 2100 10 1800 Total
- The Saki motorcycle dealer in the Minneapolis–St. Paul area wants to make an accurate forecast of demand for the Saki Super TXII motorcycle during the next month. Because the manufacturer is in Japan, it is difficult to send motorcycles back or reorder if the proper number is not ordered a month ahead. From sales records, the dealer has accumulated the following data for the past year: Month Motorcycle Sales January 9 February 7 March 10 April 8 May 7 June 12 July 10 August 11 September 12 October 10 November 14 December 16 a. Compute a 3-month moving average forecast of demand for April through January (of the next year). b. Compute a 5-month moving average forecast for June through January. c. Compare the two forecasts computed in (a) and (b), using MAD. Which one should the dealer use for January of the next year?Causal relationships are potentially useful for which component of a time series?A company has the following demand history by seasons over a two-year period. The production planner deseasonalizes the data first. Then, using the exponential smoothing method with a = 0.30 and F= 80, she forecasts the demand for the first season of 2021. Finally, the planner reseasonalizes her forecast. What is her final forecast for the first season of 2021? 2019 2020 Season 1 84 88 Season 2 76 71 Season 3 93 97 Season 4 46 51 Season 5 77 73 O a. 87.50 O b. 77.57 Oc. 79.87 O d. 75.98 O e. 86.43
- Consider the following actual and forecast demand levels for Big Mac hamburgers at a local McDonald's restaurant: Day Actual Demand Forecast Demand Monday 90.00 90.00 Tuesday 73.00 90.00 Wednesday 66.00 85.75 Thursday 50.00 80.81 Friday - ? The forecast for Monday was derived by observing Monday's demand level and setting Monday's forecast level equal to this demand level. Subsequent forecasts were derived by using exponential smoothing with a smoothing constant of 0.25. Using this exponential smoothing method, the forecast for Big Mac demand for Friday is _____ Big Macs (round your response to one decimal place).Following data on the demand for sewing machines manufactured by Taylor and Son Co. have been compiled for the past 10 years. Year 1971 1972 1973 1974 1975 78 1976 1977 1978 1979 99 1980 106 Demand 58 65 73 76 87 88 93 in (1000 units) Please estimate the value of demand for next 3 years using trend analysis.What are the advantages of exponential smoothing over the moving average and the weighted moving average?
- In the demand forecast, which of the following cannot be predicted? Select one: a. seasonal fluctuations b. cycles c. random variations d. large increases in demandYear Sales 1) 123 2)118 3) 109 4) 112 5) 100 6) 110 7) 124 8)Determine the demand in Year 8 using a 3-month moving average using the sales table. Use weights of 0.40, 0.30 and 0.30Please help with correct answers in details: Step by step Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in Bennington, Vermont, over the past 12 weeks. Week Sales (1,000sof gallons) 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 (a) Compute four-week and five-week moving averages for the time series. Week Time SeriesValue 4-WeekMovingAverageForecast 5-WeekMovingAverageForecast 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 b) Compute the MSE for the four-week moving average forecasts. (Round your answer to two decimal places.) c) Compute the MSE for the five-week moving average forecasts. (Round your answer to two decimal places.) d) What appears to be the best number of weeks of past data (three, four, or five) to use in the moving average computation? MSE for the three-week moving average is 9.65.…