Using an alpha of 0.50 and $2,927.92 as the forecast for week 52, what is the exponential smoothing forecast for week 53 for Small Town Restaurant (see downloaded file for actual demand)? Exponential smoothing equation is provided below. Provide two decimal places and use normal rounding. F₁ = F₁_₁ + α(A₂_₁ − F₁-₁) 1-1
Using an alpha of 0.50 and $2,927.92 as the forecast for week 52, what is the exponential smoothing forecast for week 53 for Small Town Restaurant (see downloaded file for actual demand)? Exponential smoothing equation is provided below. Provide two decimal places and use normal rounding. F₁ = F₁_₁ + α(A₂_₁ − F₁-₁) 1-1
MATLAB: An Introduction with Applications
6th Edition
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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Problem 1P
Related questions
Question
Use data to solve for week 53
What happens if we use a larger alpha value in our exponential smoothing forecast, such as 0.80 opposed to 0.50?
Group of answer choices
It would be more accurate because it includes more of the forecast error.
There would be no change.
It would be more sensitive to changes.
It would smooth out the variation more.

Transcribed Image Text:¶
¶
Situation: The "Small Town Restaurant" uses a forecast of weekly sales revenue to plan their
inventory ordering and staffing for the upcoming week. They have been using a regression
forecast for the past year and wonder if it is the most accurate method. You have been brought in
to determine if another forecasting technique would be more accurate. Data for their weekly
sales for the past year is below:
¶
Week Revenue. X Week
1
2 $3,016
3 $3,062.¤ ¤
4
$ 3,074. X
5
$3,002.
6
----3,054-¤¤
7 $3,002.¤ ¤
8
9
$3,078¤ ¤
10 $3,010- X
11 $3,148.
12
$3,146
$3,198.
13
X
¶
$3,157.**
$
Forecasting S
$ 2,984-¤¤
A
- Small Town Restaurant
Revenue.
14 $3,157 ¤
$3,016
¤
15
16 $3,019
¤
17 $3,045
¤
18
19
$3,046 ¤
$3,157 ¤
$3,016 ¤
$3,078 ¤
22 $2,984
20
21
¤
23 $3,002 ¤
24 $3,054 ¤
25 $3,002 ¤
26 $2,941 X
A
Week
Revenue.
27 $2,899 ¤
28 $2,942
¤
29 $3,062 X
¤
30 $3,074
31 $3,013 ¤
¤
32 $3,067
33 $3,148 ¤
34 $3,146
¤
35 $3,198 ¤
36 $3,082 ¤
37 $3,146 ¤
38 $3,150 ¤
39 $3,221 ¤
X
B
Week Revenue. ¤
40 $3,298.
41 $3,201.
42 $3,156.
43 $3,017. X
44 $3,156.
45 $3,097.
46 $ 2,978. X
47 $3,120
48 $3,156.
49 $3,048.
50 $2,948.
51 $ 2,840.
52 $2,921.
X
$ 159,532 Annual total
You will use this data in the next few steps to complete various time series forecasts and
compare them to determine the most accurate method.
¤¤¤¤¤¤¤¤¤¤¤¤¤¤¤
X{
X{
X{
X{

Transcribed Image Text:Using an alpha of 0.50 and $2,927.92 as the forecast for week 52, what is the exponential
smoothing forecast for week 53 for Small Town Restaurant (see downloaded file for actual
demand)? Exponential smoothing equation is provided below. Provide two decimal places and
use normal rounding.
F₁ = F₁_₁ + a(A₁_₁ − F₁-₁)
-
t
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