a) Plot the monthly sales data. b) Forecast January sales using each of the following: i) Naive method. ü) A 3-month moving average. iii) A 6-month weighted average using .1, .1, .1, .2, .2, and . with the heaviest weights applied to the most recent month iv) Exponential smoothing using an a = .3 and a Septenb-

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Case Study for Forecasting
4.6
The monthly sales for Telco Batteries, Inc., were as
follows:
Month
Sales
20
January
February
March
21
15
14
April
May
13
June
16
17
July
August
September
October
18
20
20
November
21
December
23
F teta
a) Plot the monthly sales data.
b) Forecast January sales using each of the following:
i) Naive method.
ü) A 3-month moving average.
iii) A 6-month weighted average using .1, .1, .1, .2, .2, and .3,
with the heaviest weights applied to the most recent months.
iv) Exponential smoothing using an a = .3 and a September
forecast of 18.
v) A trend projection.
c) With the data given, which method would allow you to forecast
next March's sales?
Transcribed Image Text:Case Study for Forecasting 4.6 The monthly sales for Telco Batteries, Inc., were as follows: Month Sales 20 January February March 21 15 14 April May 13 June 16 17 July August September October 18 20 20 November 21 December 23 F teta a) Plot the monthly sales data. b) Forecast January sales using each of the following: i) Naive method. ü) A 3-month moving average. iii) A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. iv) Exponential smoothing using an a = .3 and a September forecast of 18. v) A trend projection. c) With the data given, which method would allow you to forecast next March's sales?
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