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National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below:     Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19   2 March 18   3 April 15   4 May 20   5 June 18   6 July 22   7 August 20   8 September    ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19

National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below:     Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19   2 March 18   3 April 15   4 May 20   5 June 18   6 July 22   7 August 20   8 September    ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19

Practical Management Science
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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  1. National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below:

 

 

Sales (1000 units)

Forecast

Observation

Month

Yt

Ft

1

February

19

 

2

March

18

 

3

April

15

 

4

May

20

 

5

June

18

 

6

July

22

 

7

August

20

 

8

September

 

 ?

Use Excel to plot the data and forecast September sales using the following methods:

  1. The naïve forecast
  2. A three-month moving average
  3. Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19
  4. A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.

 

 

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