The analytics department is researching the past five years of their company's sales to better prepare for the future. The company has experienced a variation in sales for no known reason and wants to develop a forecast using the exponential smoothing method. Usingdata from the previous 20 days, the following summary table was calculated. What is the MAD?DaySalesAt170ŷe=yt-Ŷte²le26969.770-11136768.8969.7-2.77.292.7200 2063.0363.03-2.89778.39682 2.8977208.066 53.3112.813.9010.9513.87Total0000

Step 1: Identify the formula for Mean Absolute Deviation (MAD)MAD = ∑|e|/nwhere:∑|e| = total of all…

Answered: The analytics department is researching…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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Jean and Dinah had been in business for two years producing umbrellas to be sold to the cruise ship passengers when they docked. They found that they are constantly out of umbrellas and had to rush producions which has resulted in the increase of their production cost. Jean has a nephew who is enrolled in the UWIOC and he advised her to prepare forecasted qualities using the sales that they made over the past months. The data below represents sales for the last 9 months. In order to assist Jean and Dinah you are asked to; a. plot the data on a graph showing the trend b. determine the equation of the trend line c. predict sales for month 10 and 11. Months Sales 1 44 2 52 3 50 4 54 5 55 6 55 7 60 8 56 9 62
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The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Jan Feb Mar AprMonth 1 2 3 4Number of Accidents 25 40 60 105 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): y = ? + ?x
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Develop two exponential smoothing forecasts for periods 2 through 11. For the first forecast, use a=0.1. For the second, use a=0.7. Assume that your forecast for period 1 was 205. Click the icon to view the time series data. Find the exponential smoothing forecast for each period when a=0:1 (enter your responses rounded to one decimal place). Period Forecast (0.1) 205 1 2 More Info Period 1 2 3 4 5 6 7 8 9 10 Print Demand 228 249 229 238 231 154 166 157 Demand 228 249 164 161 Done
Please do not give solution in image format thanku A small manufacturing firm has recorded a time series of the cost per unit for the firm’s leading product over the past eight years. Year 1 2 3 4 5 6 7 8 Cost/Unit ($) 20 24.5 28.2 27.5 26.6 30 31 36 a) If you are not given a base value or trend, what would be the forecast for the year 10 made at the end of year 8 (α=0.2, β=0.4). b) Forecast for the year 9 using 1) 5-month weighted average using 0.1,0.1,0.1,0.2,0.3, with the heaviest weight applied to the recent month 2) Exponential smoothing using α =0.2 and forecast of 21 for year 5 3) If α value was not provided in the question above, what value of α would you choose?
The number of patients coming to the Healthy Start Maternity clinic has been increasing steadilyover the past eight months. You are provided with some historical data as follows:Month Clinic attendance(in thousands)1 3.42 3.93 4.54 5.05 5.86 5.97 6.58 6.7b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:-i. Derive the values for the intercept and slope. ii. Derive the linear regression equation. iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23 Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?
Given the following original forecast and actual data: Month Actual Forecast Jan Feb Mar Apr May Jun Jul 600 475 550 575 688 649 ??? 400 —— 1 ??? Using exponential smoothing with a - = 0.64, what is the forecast for July. Round your answer to 2 decimal places.
tab s lock Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the month Ges collected the data shown in the following table V esc This exercise contains only parts b, c, and d. b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): c) The estimate for guitar sales if Maroon 5 performed on TV 9 times = d) The correlation coefficient (r) for this model The coefficient of determination (2) for this model= The percentage of variation in sales that can be explained by TV appearances = Q A N @ 2 W S 31/1 X ** 3 8.0 F3 E D C $ Maroon 5 TV Appearances Demand for Guitars sales (round your response to two decimal places). (round your response to four decimal places). (round your response to four decimal places). 4 889 R F % 5 V d Es FS Y = T G % (round your response to two decimal places). A 6…
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Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 Value 18 13 (a) Construct a time series plot. 20T 18 16- 14- Time Series Value O Week 1 2 3 4 5 6 What type of pattern exists in the data? O The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. 8 6 O The data appear to follow a seasonal pattern. O The data appear to follow a horizontal pattern. Week 1 2 0 1 3 4 5 6 18 13 15 12 (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Time Series Value 16 14 18 + 2 13 15 4 5 6 15 12 16 3 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? 12 16 4 14 Week (c) Use a = 0.2 to compute the exponential smoothing values for the time series. Time Series Value 5 14 Forecast 6 Forecast 7 20 18 16 14 12 WE 10 2 + 7 @o 20 18 0 1 2 3 4 Week 5 6 00 0 1 2 3 4 5 Week 6 7…

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