2. The manager of a fabric company needs to accurately forecast the demand for fabric. If the customers do not order enough fabric (in 10,000 yards), they will buy their fabric from one of the company's major competitors. The company has collected the following demand data for the past 10 months. Compute a weighted three-month moving average forecast using weights of (a) 10%, 30 %, 60 %, and (b) 25% 30% 45% for the most distant data, next recent, and the most recent respectively. Feb Mar Apr May Jun Jul Month Jan Demand 37 Aug Sep Oct 63 65 45 47 50 52 54 58 60 Forecast Table: Month Actual WMA (10%, 30%, 60%) WMA (25%, 30%, 45%) January February March April May June July August September October Graph:
2. The manager of a fabric company needs to accurately forecast the demand for fabric. If the customers do not order enough fabric (in 10,000 yards), they will buy their fabric from one of the company's major competitors. The company has collected the following demand data for the past 10 months. Compute a weighted three-month moving average forecast using weights of (a) 10%, 30 %, 60 %, and (b) 25% 30% 45% for the most distant data, next recent, and the most recent respectively. Feb Mar Apr May Jun Jul Month Jan Demand 37 Aug Sep Oct 63 65 45 47 50 52 54 58 60 Forecast Table: Month Actual WMA (10%, 30%, 60%) WMA (25%, 30%, 45%) January February March April May June July August September October Graph:
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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Transcribed Image Text:Solve the problem by completing the table with the help of MS Excel. Label the final answers.
2. The manager of a fabric company needs to accurately forecast the demand for fabric. If the customers do
not order enough fabric (in 10,000 yards), they will buy their fabric from one of the company's major
competitors. The company has collected the following demand data for the past 10 months. Compute a
weighted three-month moving average forecast using weights of (a) 10%, 30 %, 60 %, and (b) 25% 30%
45% for the most distant data, next recent, and the most recent respectively.
Feb
Mar
Apr
May
Jun
Jul
Aug Sep
Oct
Month Jan
Demand 37
45
47
50
52
54
58
60
63
65
Forecast Table:
Month
Actual
WMA (10%, 30%, 60%)
WMA (25%, 30%, 45%)
January
February
March
April
May
June
July
August
September
October
Graph:
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