eBookProblem 6-05Consider the following time series data.316Week 1Week2Value 18 13a. Choose the correct time series plot(1)€(!!!)Time Series ValueTime Series Value28642986420284H2G8642014112{B}2TH3Week (t)Week (t)56€(iv)Time Series ValueTime Series Value28642 NO28642 NO12243₁Week (t)Week (t)56 d. Compare the three-week moving average forecast with the exponential smoothing forecast using a 0.2. Which appears to provide the better forecast based on MSE?Explain.The input in the box below will not be graded, but may be reviewed and considered by your instructor.e. Use trial and error to find a value of the exponential smoothing coefficient a that results in a smaller MSE than what you calculated for a = 0.2.

Answered: Problem 6-05 Consider the following…

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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Dic 2 - Time Series Analysis and F eBook Problem 6-01 (Algorithmic) Consider the following time series data. Thm Week 1 2 3 4 5 6 Value 20 13 15 11 19 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. a. Mean absolute error. If required, round your answer to one decimal place. b. Mean squared error. If required, round your answer to one decimal place. c. Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places. % d. What is the forecast for week 7? If required, round your answer to two decimal place.
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Using exponential smoothing with alpha = .2, and assuming the forecast for period 11 was 80, what would the forecast for period 14 be?
Sales of industrial vacuum cleaners at Yarena Supply CO. over the past 13 months are as follows: Sales in P1,000 Month Sales in P1,000 Month 11 January 14 August 14 February 17 September 15 March 12 October 10 April 14 November 15 May 16 December 17 June 11 January 11 July Required suing a moving average with three periods, determine the demand for vacuum cleaners for next February?
QUESTION 4 Suppose the following are the seasonal indices for the first three quarters of the year for a quarterly series: Quarter Seasonal Index Q1 72.4 Q2 85.3 Q3 109.6 Remember that the seasonal indices should average 100 so you should be able to infer the seasonal index for Q4. Furthermore, suppose that the estimated coeffcients from a regression of the deseasonalized series on Time are given below: Coefficients Intercept 2,506 Time 71.3 If the original value of the series in a Q1 was 2,040, then what is the seasonally adjusted value? (please round your answer to 1 decimal place)
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Q2: An economist who estimated the Keynesian money demand function in logarithmic form using data from Sri Lankan economy, obtained the graph on the left by using predicted and actual money demand. While the model was very successful in predicting money demand until 2010 (small forecast errors), it predicts a consistently higher money demand than actually occurred since then (growing forecast errors each period). 48 Ln(M) 4.75 4.7 4.65 4.6 4.55 Actual 4.5 Predicted ...... 4.45 Help this economist who has trouble explaining this situation, even if you do not know anything about the economy in question. Can you answer this question with details please? 6toz Stor
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Problem 6-05 Consider the following time series data. Week Value (1) 18 € a. Choose the correct time series plot. Time Series Value Time Series Value 20 13 20 16 M 11 2 3 5 17 14 64 5 9 € € Time Series Value Time Series Value 284H2G86420 313 Week (t)