1. Use regression analysis to estimate the line of best fit -use the manual method with the formulas shown below. Month Demand Weighted Moving average forecast ErrorAbsolute errorSquare of error1145.5160371113.035 =99-113.035=-14.035100.13 =194.5-100.13=94.37141.99 =206-141.99364.01184.015 =135.5-184.015=-48.515 =abs(-48.515)=48.515 =(-48.515)^2=235168.795 =152.5-168.795=-16.295 =abs(-16.295)=16.295 =(-16.295)^2=265155.985 =246-155.985=90.015196.36 =259-196.36=62.64236.605 =181.5-236.605=-55.105 =abs(-55.105)=55.105 =(-55.105)^2=303218.04 =194-218.04=-24.04499=abs(-14.035)=14.035 =(-14.035)^2=1965194.5=abs(94.37)=94.37=(94.37)^2=8905.206=abs(64.01)=64.01=(64.01)^2=4097.7135.58152.5=abs(90.015)=90.015 =(90.015)^2=810:=abs(62.64)=62.64924610259=(62.64)^2=3923.11181.512194=abs(-24.04)=24.04=(-24.0413200.925weight for the most recent period would be=3/(3+2+1)=0.50weight for the second most recent period would be=2/(3+2+1)=0.33weight for the most third most recent period would be=1/(3+2+1)=0.17MAD =52.114MSE =3495.5714MAPE =0.27087=27.087% y= a+ bxwhere:nE xy – ExEyb =nE x² – (Ex}a = ÿ – bx

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Use regression analysis to estimate the line of best fit -use the manual method with the formulas shown below.

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter2: Matrices

Section2.2: Properties Of Matrrix Operations

Problem 14E: Solve for X in the Equation, given A=-2-1103-4 and B=0320-4-1 a X=3A2B b 2X=2AB c 2X+3A=B d...

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Question

1. Use regression analysis to estimate the line of best fit -use the manual method with the formulas shown below.

Month Demand Weighted Moving average forecast Error
Absolute error
Square of error
1
145.5
160
3
71
113.035 =99-113.035=-14.035
100.13 =194.5-100.13=94.37
141.99 =206-141.99364.01
184.015 =135.5-184.015=-48.515 =abs(-48.515)=48.515 =(-48.515)^2=235
168.795 =152.5-168.795=-16.295 =abs(-16.295)=16.295 =(-16.295)^2=265
155.985 =246-155.985=90.015
196.36 =259-196.36=62.64
236.605 =181.5-236.605=-55.105 =abs(-55.105)=55.105 =(-55.105)^2=303
218.04 =194-218.04=-24.04
4
99
=abs(-14.035)=14.035 =(-14.035)^2=196
5
194.5
=abs(94.37)=94.37
=(94.37)^2=8905.
206
=abs(64.01)=64.01
=(64.01)^2=4097.
7
135.5
8
152.5
=abs(90.015)=90.015 =(90.015)^2=810:
=abs(62.64)=62.64
9
246
10
259
=(62.64)^2=3923.
11
181.5
12
194
=abs(-24.04)=24.04
=(-24.04
13
200.925
weight for the most recent period would be=3/(3+2+1)=0.50
weight for the second most recent period would be=2/(3+2+1)=0.33
weight for the most third most recent period would be=1/(3+2+1)=0.17
MAD =52.114
MSE =3495.5714
MAPE =0.27087=27.087%

y= a+ bx
where:
nE xy – ExEy
b =
nE x² – (Ex}
a = ÿ – bx

Definition Definition Statistical method that estimates the relationship between a dependent variable and one or more independent variables. In regression analysis, dependent variables are called outcome variables and independent variables are called predictors.

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