Description
Please do not bid if you cannot provide and guarantee excellent results.
Spring 2019
Important Notice: All team members must do all parts of the project and compare results. DO NOT divide up parts of the project as many parts are related. Teams must submit a copy of Word file and Excel file of their work through Blackboard Dropbox. Do not submit any file until all team members agree on the deliverables. Only one team member will submit the files. There is no second chance on submittal.
Unformatted Attachment Preview
Purchase answer to see full attachment
Explanation & Answer
Attached.
Forecasting Dataset
Spring 2019
PERIOD
PRICE
AIP
DIFF
ADV
DEMAND
PERIOD
PRICE
1
-0.38396
0.290259
0.426187
0.814258
0.691026
AIP
DIFF
1
-0.23374
1
-0.76244 0.807343
1
-0.55717 0.299438 0.537413
-0.64098 0.299191 0.588114
ADV
1
0.783047
DEMAND
1
Forecasting Dataset
Spring 2019
Month/Yr.
June 2016
Jan. 2017
Jan. 2018
Jan. 2019
PERIOD
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
PRICE
6.1
5.75
5.7
5.7
5.6
5.6
5.6
6.3
6.4
6.2
5.9
5.9
5.7
5.75
5.75
5.8
5.7
5.8
5.7
5.8
5.8
5.75
5.7
5.55
5.6
5.65
5.7
5.75
5.8
5.3
5.4
5.7
AIP
5.8
6
6.3
5.7
5.85
5.8
5.75
5.85
5.65
6
6.1
6
6.1
6.2
6.1
6.1
6.2
6.3
6.1
5.75
5.75
5.65
5.9
5.65
6.1
6.25
5.65
5.75
5.85
6.25
6.3
6.4
33
34
35
36
5.9
6.5
Time Series Plot of
25
Demand
20
15
10
5
0
0
5
Time Series Plot of
10
Demand
Feb. 2019
Mar-19
Apr-19
May-19
8
6
4
2
0
0
5
Time Series Plo
Demand
Time Series Plo
1.2
1
0.8
0.6
0.4
0.2
0
-0.2 0
-0.4
-0.6
-0.8
-1
5
Demand
Demand Vs.
Vs. Adv
Adv
18
18
16
16
14
14
12
12
10
10
0
0
1
1
2
2
3
3
4
4
5
5
Advertising
Advertising
Demand Vs. DIff
25
20
Demand
Demand
Demand
22
22
20
20
15
Demand
15
10
5
0
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
Diff
DIFF
-0.3
0.25
0.6
0
0.25
0.2
0.15
-0.45
-0.75
-0.2
0.2
0.1
0.4
0.45
0.35
0.3
0.5
0.5
0.4
-0.05
-0.05
-0.1
0.2
0.1
0.5
0.6
-0.05
0
0.05
0.95
0.9
0.7
ADV
5.3
6.75
7.25
7.3
7.2
6.5
6.75
6.89
5.8
5.5
6.5
6.25
7
6.9
6.8
6.8
7.1
7
6.8
6.5
8.1
7.7
7.3
7.5
8.1
8.3
8.7
9.2
8.4
8.8
9.5
9.3
DEMAND
14.4
15.3
16.5
16.1
16
15.5
15.2
13.9
13.3
13.12
13.8
14.8
15.3
16.3
17.5
17.4
17.1
16.8
16.5
16
15.2
15.3
15.9
16.2
17.5
18.4
19.4
19.1
18.7
18.2
18.4
17.5
0.6
9.1
17.1
Time Series Plot of DEMAND
y = 0.1173x + 14.3
R² = 0.4775
6.7
Demand
6.5
6.3
6.1
5.9
5.7
5.5
10
15
20
25
30
0
35
5
Time Period
Time Series Plot of Advertising
Demand
y = 0.0916x + 5.8024
R² = 0.663
10
15
20
25
30
35
Time Period
Time Series Plot of Diff
7
6
5
4
3
2
1
0
0
y = 0.0163x - 0.0552
5
y = 0.0163x - 0.0552
R² = 0.1816
Time Series Plot of Diff
c
10
15
20
25
30
35
Time Period
Vs.
Vs. Adv
Adv
Demand Vs. Price
Demand
20
18
16
14
12
6
6
7
7
8
8
9
9
10
10
5
5.2
5.4
5.6
5.8
Price
y = 2.6166x + 15.716
R² = 0.3459
Demand Vs. AIP
25
20
Demand
nd Vs. DIff
yy == 1.181x
1.181x ++ 7.6018
7.6018
R²
R² == 0.6132
0.6132
15
Demand
15
10
5
0
5.5
0.2
0.4
0.6
0.8
1
5.7
1.2
c
5.9
y = 0.0074x + 5.8641
R² = 0.0843
Time Series Plot of AIP
5
10
15
20
25
30
35
Time Period
c
Time Series Plot of Price
5
10
15
20
Time Period
y = -0.0089x + 5.9193
R² = 0.1474
25
30
35
y = -4.6991x + 43.4
R² = 0.4109
Demand Vs. Price
5.8
6
6.2
6.4
6.6
Price
Demand Vs. AIP
y = 2.0003x + 4.3142
R² = 0.0895
6.1
AIP
6.3
6.5
6.7
Month/Yr.
June 2015
Jan. 2016
Jan. 2017
Jan. 2018
Feb. 2018
Mar-18
PERIOD PRICE
1
6.1
2
5.75
3
5.7
4
5.7
5
5.6
6
5.6
7
5.6
8
6.3
9
6.4
10
6.2
11
5.9
12
5.9
13
5.7
14
5.75
15
5.75
16
5.8
17
5.7
18
5.8
19
5.7
20
5.8
21
5.8
22
5.75
23
5.7
24
5.55
25
5.6
26
5.65
27
5.7
28
5.75
29
5.8
30
5.3
31
5.4
32
5.7
33
5.9
AIP
5.8
6
6.3
5.7
5.85
5.8
5.75
5.85
5.65
6
6.1
6
6.1
6.2
6.1
6.1
6.2
6.3
6.1
5.75
5.75
5.65
5.9
5.65
6.1
6.25
5.65
5.75
5.85
6.25
6.3
6.4
6.5
DIFF
-0.3
0.25
0.6
0
0.25
0.2
0.15
-0.45
-0.75
-0.2
0.2
0.1
0.4
0.45
0.35
0.3
0.5
0.5
0.4
-0.05
-0.05
-0.1
0.2
0.1
0.5
0.6
-0.05
0
0.05
0.95
0.9
0.7
0.6
Ft=f(f-1
Month/Yr.
June 2016
Jan. 2017
Jan. 2018
PERIOD PRICE
1
6.1
2
5.75
3
5.7
4
5.7
5
5.6
6
5.6
7
5.6
8
6.3
9
6.4
10
6.2
11
5.9
12
5.9
13
5.7
14
5.75
15
5.75
16
5.8
17
5.7
18
5.8
19
5.7
20
5.8
21
5.8
22
5.75
23
5.7
24
5.55
25
5.6
26
5.65
27
5.7
AIP
5.8
6
6.3
5.7
5.85
5.8
5.75
5.85
5.65
6
6.1
6
6.1
6.2
6.1
6.1
6.2
6.3
6.1
5.75
5.75
5.65
5.9
5.65
6.1
6.25
5.65
DIFF
-0.3
0.25
0.6
0
0.25
0.2
0.15
-0.45
-0.75
-0.2
0.2
0.1
0.4
0.45
0.35
0.3
0.5
0.5
0.4
-0.05
-0.05
-0.1
0.2
0.1
0.5
0.6
-0.05
Jan. 2019
Feb. 2019
28
29
30
31
32
33
5.75
5.8
5.3
5.4
5.7
5.9
5.75
5.85
6.25
6.3
6.4
6.5
0
0.05
0.95
0.9
0.7
0.6
2017
13.9
13.3
13.12
13.8
14.8
15.3
16.3
17.5
17.4
17.1
16.8
16.5
2018
16
15.2
15.3
15.9
16.2
17.5
18.4
19.4
19.1
18.7
18.2
18.4
2019
17.5
17.1
Mar-18
Month
2016
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
14.4
15.3
16.5
16.1
16
15.5
15.2
Grand Avg =
ADV
5.3
6.75
7.25
7.3
7.2
6.5
6.75
6.89
5.8
5.5
6.5
6.25
7
6.9
6.8
6.8
7.1
7
6.8
6.5
8.1
7.7
7.3
7.5
8.1
8.3
8.7
9.2
8.4
8.8
9.5
9.3
9.1
DEMAND
14.4
15.3
16.5
16.1
16
15.5
15.2
13.9
13.3
13.12
13.8
14.8
15.3
16.3
17.5
17.4
17.1
16.8
16.5
16
15.2
15.3
15.9
16.2
17.5
18.4
19.4
19.1
18.7
18.2
18.4
17.5
17.1
3m MA Forc.
3m MA
15.4
15.96666667
16.2
Abs. Dev.
6m MA
0.7
0.033333333
0.7
15.86666667
0.666666667
15.63333333
15.56666667
1.666666667
15.76666667
14.86666667
1.566666667
15.53333333
14.13333333
1.013333333
15
0.36
14.50333333
13.40666667
1.393333333
14.13666667
13.90666667
1.393333333
14.02
14.63333333
1.666666667
14.03666667
15.46666667
2.033333333
14.43666667
16.36666667
1.033333333
15.13666667
17.06666667
0.033333333
15.85
17.33333333
0.533333333
16.4
17.1
0.6
16.73333333
16.8
0.8
16.93333333
1.233333333
16.88333333
15.9
0.6
16.5
15.5
0.4
16.15
0.733333333
15.95
1.7
15.85
16.53333333
1.866666667
16.01666667
17.36666667
2.033333333
16.41666667
18.43333333
0.666666667
17.11666667
18.96666667
0.266666667
17.75
19.06666667
0.866666667
18.21666667
18.66666667
0.266666667
18.55
18.43333333
0.933333333
18.7
18.03333333
17.66666667
0.933333333
18.55
18.16666667
13.44
16.43333333
15.46666667
15.8
6m MA Forc.
MAD =
Alpha =
MAD =
ADV
5.3
6.75
7.25
7.3
7.2
6.5
6.75
6.89
5.8
5.5
6.5
6.25
7
6.9
6.8
6.8
7.1
7
6.8
6.5
8.1
7.7
7.3
7.5
8.1
8.3
8.7
DEMAND
14.4
15.3
16.5
16.1
16
15.5
15.2
13.9
13.3
13.12
13.8
14.8
15.3
16.3
17.5
17.4
17.1
16.8
16.5
16
15.2
15.3
15.9
16.2
17.5
18.4
19.4
0.956444444
MAD =
0.3
0.946974412
Exp. Forecast
14.4
Abs. Dev.
0
14.4
0.9
14.67
1.83
15.219
0.881
15.4833
0.5167
15.63831
0.13831
15.596817
0.396817
15.4777719
1.5777719
15.00444033
1.70444033
14.49310823
1.373108231
14.08117576
0.281175762
13.99682303
0.803176967
14.23777612
1.062223877
14.55644329
1.743556714
15.0795103
2.4204897
15.80565721
1.59434279
16.28396005
0.816039953
16.52877203
0.271227967
16.61014042
0.110140423
16.5770983
0.577098296
16.40396881
1.203968807
16.04277817
0.742778165
15.81994472
0.080055284
15.8439613
0.356038699
15.95077291
1.549227089
16.41554104
1.984458963
17.01087873
2.389121274
1.319135802
9.2
8.4
8.8
9.5
9.3
9.1
19.1
18.7
18.2
18.4
17.5
17.1
Forecast
Monthly Avg.
Seas index
15.8
0.976849626
15.2
0.93975407
14.21
0.878546404
14.85
0.918114996
15.5
0.958301848
15.73333333
0.972727897
16.66666667
1.030432095
17.8
1.100501477
17.53333333
1.084014563
17.26666667
1.06752765
16.83333333
1.040736415
16.7
1.032492959
16.17444444
12
17.72761511
1.372384892
18.13933058
0.560669424
18.3075314
0.107531403
18.27527198
0.124728018
18.31269039
0.812690388
18.06888327
17.77821829
0.968883271
Abs. Dev.
0.433333333
1.866666667
2.233333333
1.88
0.703333333
0.663333333
1.28
2.263333333
3.063333333
2.263333333
1.25
0.4
0.233333333
0.933333333
1.683333333
1.2
0.25
0.25
1.65
2.383333333
2.983333333
1.983333333
0.95
0.016666667
0.15
1.2
1.45
Alpha
0.1
0.2
Forecast
17.20939938
17.73848457
MAD
1.225115131
1.043501296
0.3
17.77821829
0.946974412
0.4
17.67187061
0.872781154
0.5
17.53410079
0.812573061
0.6
17.40670466
0.749029652
0.7
17.30053463
0.690568869
0.8
17.21533139
0.643282505
0.9
17.14885419
0.604965484
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
0.94405524
0.891240296
0.887731919
0.422078124
33
ANOVA
df
Regression
Residual
Total
1
31
32
SS
MS
F
45.25579318 45.25579318 254.0320383
5.522648238 0.178149943
50.77844141
Coefficients
Standard Error
t Stat
14.08367946
0.150353411 93.67050208
0.122986175
0.007716352 15.93838255
Demand = 14.08 + .1229(Period)
Intercept
PERIOD
RESIDUAL OUTPUT
MAD =
Observation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Predicted Des. Demand
14.20666564
14.32965181
14.45263799
14.57562417
14.69861034
14.82159652
14.94458269
15.06756887
15.19055504
15.31354122
15.43652739
15.55951357
15.68249974
15.80548592
15.92847209
16.05145827
16.17444444
16.29743062
16.4204168
16.54340297
16.66638915
16.78937532
Residuals
0.597063174
0.518488186
0.540526804
0.276574821
0.289291847
0.071703814
-0.222932658
-0.838152551
-1.037916153
-0.379782518
-0.405730535
-0.115527905
0.046462121
0.013120748
-0.026630646
-1.34022E-05
-0.156123981
-0.155014778
-0.439678272
-0.164218723
-0.491944701
0.625754869
0.312893159
Abs. Res.
0.597063174
0.518488186
0.540526804
0.276574821
0.289291847
0.071703814
0.222932658
0.838152551
1.037916153
0.379782518
0.405730535
0.115527905
0.046462121
0.013120748
0.026630646
1.34022E-05
0.156123981
0.155014778
0.439678272
0.164218723
0.491944701
0.625754869
P-value
1.33707E-39
1.7435E-16
23
24
25
26
27
28
29
30
31
32
33
16.9123615
17.03534767
17.15833385
17.28132002
17.4043062
17.52729237
17.65027855
17.77326472
17.8962509
18.01923707
18.14222325
0.405730535
-0.130444446
0.832308808
0.575266644
0.224020893
0.092397107
-0.133167866
-0.285647562
-0.075306122
-0.104504304
0.05402675
0.405730535
0.130444446
0.832308808
0.575266644
0.224020893
0.092397107
0.133167866
0.285647562
0.075306122
0.104504304
0.05402675
Significance F
1.7435E-16
Lower 95%
Upper 95% Lower 95.0% Upper 95.0%
13.77703166 14.39032727 13.77703166 14.39032727
0.107248571 0.13872378 0.107248571
0.13872378
Ses. For.
Mar Demand =
18.26520943 0.878546404 16.04683405
Apr Demand =
18.3881956 0.918114996 16.88247813
May Demand = 18.51118178 0.958301848
17.7392997
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
0.830062691
0.689004071
0.678971945
0.713733675
33
ANOVA
df
Regression
Residual
Total
1
3...