Statistics

profiletcj9
lostsalescaseanswer2.xls
Home>Mathematics homework help>Statistics homework help>Statistics

carlson data

sales tp m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 m11
1.71 1 0 0 0 0 0 0 0 0 1 0 0
1.9 2 0 0 0 0 0 0 0 0 0 1 0
2.74 3 0 0 0 0 0 0 0 0 0 0 1
4.2 4 0 0 0 0 0 0 0 0 0 0 0
1.45 5 1 0 0 0 0 0 0 0 0 0 0
1.8 6 0 1 0 0 0 0 0 0 0 0 0
2.03 7 0 0 1 0 0 0 0 0 0 0 0
1.99 8 0 0 0 1 0 0 0 0 0 0 0
2.32 9 0 0 0 0 1 0 0 0 0 0 0
2.2 10 0 0 0 0 0 1 0 0 0 0 0
2.13 11 0 0 0 0 0 0 1 0 0 0 0
2.43 12 0 0 0 0 0 0 0 1 0 0 0
1.9 13 0 0 0 0 0 0 0 0 1 0 0
2.13 14 0 0 0 0 0 0 0 0 0 1 0
2.56 15 0 0 0 0 0 0 0 0 0 0 1
4.16 16 0 0 0 0 0 0 0 0 0 0 0
2.31 17 1 0 0 0 0 0 0 0 0 0 0
1.89 18 0 1 0 0 0 0 0 0 0 0 0
2.02 19 0 0 1 0 0 0 0 0 0 0 0
2.23 20 0 0 0 1 0 0 0 0 0 0 0
2.39 21 0 0 0 0 1 0 0 0 0 0 0
2.14 22 0 0 0 0 0 1 0 0 0 0 0
2.27 23 0 0 0 0 0 0 1 0 0 0 0
2.21 24 0 0 0 0 0 0 0 1 0 0 0
1.89 25 0 0 0 0 0 0 0 0 1 0 0
2.29 26 0 0 0 0 0 0 0 0 0 1 0
2.83 27 0 0 0 0 0 0 0 0 0 0 1
4.04 28 0 0 0 0 0 0 0 0 0 0 0
2.31 29 1 0 0 0 0 0 0 0 0 0 0
1.99 30 0 1 0 0 0 0 0 0 0 0 0
2.42 31 0 0 1 0 0 0 0 0 0 0 0
2.45 32 0 0 0 1 0 0 0 0 0 0 0
2.57 33 0 0 0 0 1 0 0 0 0 0 0
2.42 34 0 0 0 0 0 1 0 0 0 0 0
2.4 35 0 0 0 0 0 0 1 0 0 0 0
2.5 36 0 0 0 0 0 0 0 1 0 0 0
2.09 37 0 0 0 0 0 0 0 0 1 0 0
2.54 38 0 0 0 0 0 0 0 0 0 1 0
2.97 39 0 0 0 0 0 0 0 0 0 0 1
4.35 40 0 0 0 0 0 0 0 0 0 0 0
2.56 41 1 0 0 0 0 0 0 0 0 0 0
2.28 42 0 1 0 0 0 0 0 0 0 0 0
2.69 43 0 0 1 0 0 0 0 0 0 0 0
2.48 44 0 0 0 1 0 0 0 0 0 0 0
2.73 45 0 0 0 0 1 0 0 0 0 0 0
2.37 46 0 0 0 0 0 1 0 0 0 0 0
2.31 47 0 0 0 0 0 0 1 0 0 0 0
2.23 48 0 0 0 0 0 0 0 1 0 0 0
2.43375
13.3949666153

carlson regression

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.9732535814 n
R Square 0.9472225338 0.7291666667
Adjusted R Square 0.9291274025 0.0193611111
Standard Error 0.1629490134
Observations 48
ANOVA
df SS MS F Significance F
Regression 12 16.6791916667 1.3899326389 52.3468174617 1.0140863305894E-18
Residual 35 0.9293333333 0.026552381
Total 47 17.608525
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 3.9430555556 0.0901416678 43.7428732987 3.82118155719256E-32 3.7600580174 4.1260530937 3.7600580174 4.1260530937
tp 0.0111111111 0.0017530523 6.338151657 0.0000002776 0.0075522215 0.0146700008 0.0075522215 0.0146700008
m1 -2.0411111111 0.1152356875 -17.7124912932 4.74293526143494E-19 -2.2750522797 -1.8071699425 -2.2750522797 -1.8071699425
m2 -2.2197222222 0.1152756837 -19.2557714827 3.32128233705371E-20 -2.4537445875 -1.9856998569 -2.4537445875 -1.9856998569
m3 -1.9308333333 0.1153423132 -16.7400261044 2.79352110356657E-18 -2.1649909639 -1.6966757028 -2.1649909639 -1.6966757028
m4 -1.9444444444 0.1154355299 -16.8444191052 2.3004306059146E-18 -2.1787913151 -1.7100975738 -2.1787913151 -1.7100975738
m5 -1.7405555556 0.1155552694 -15.0625373023 7.25375974965738E-17 -1.9751455107 -1.5059656004 -1.9751455107 -1.5059656004
m6 -1.9716666667 0.1157014494 -17.0409850233 1.59995459628575E-18 -2.2065533834 -1.7367799499 -2.2065533834 -1.7367799499
m7 -1.9877777778 0.1158739699 -17.1546532825 1.29887938176797E-18 -2.2230147301 -1.7525408254 -2.2230147301 -1.7525408254
m8 -1.9338888889 0.1160727133 -16.6610121658 3.23791168708285E-18 -2.1695293124 -1.6982484654 -2.1695293124 -1.6982484654
m9 -2.2566666667 0.1153423132 -19.564950665 1.99163807035119E-20 -2.4908242972 -2.0225090361 -2.4908242972 -2.0225090361
m10 -1.9502777778 0.1152756837 -16.9183796246 2.00586797429729E-18 -2.1843001431 -1.7162554125 -2.1843001431 -1.7162554125
m11 -1.4013888889 0.1152356875 -12.1610667629 0 -1.6353300575 -1.1674477203 -1.6353300575 -1.1674477203
carlson regression
RESIDUAL OUTPUT
Observation Predicted sales Residuals 3.9430555556 yintercept
1 1.6975 0.0125 0.0111111111 tp
2 2.015 -0.115 49 -2.2566666667 m9 2.2308333333
3 2.575 0.165 50 -1.9502777778 m10 2.5483333333
4 3.9875 0.2125 51 -1.4013888889 m11 3.1083333333
5 1.9575 -0.5075 52 0 m12 4.5208333333
6 1.79 0.01
7 2.09 -0.06
8 2.0875 -0.0975
9 2.3025 0.0175
10 2.0825 0.1175
11 2.0775 0.0525
12 2.1425 0.2875
13 1.8308333333 0.0691666667
14 2.1483333333 -0.0183333333
15 2.7083333333 -0.1483333333
16 4.1208333333 0.0391666667
17 2.0908333333 0.2191666667
18 1.9233333333 -0.0333333333
19 2.2233333333 -0.2033333333
20 2.2208333333 0.0091666667
21 2.4358333333 -0.0458333333
22 2.2158333333 -0.0758333333
23 2.2108333333 0.0591666667
24 2.2758333333 -0.0658333333
25 1.9641666667 -0.0741666667
26 2.2816666667 0.0083333333
27 2.8416666667 -0.0116666667
28 4.2541666667 -0.2141666667
29 2.2241666667 0.0858333333
30 2.0566666667 -0.0666666667
31 2.3566666667 0.0633333333
32 2.3541666667 0.0958333333
33 2.5691666667 0.0008333333
34 2.3491666667 0.0708333333
35 2.3441666667 0.0558333333
36 2.4091666667 0.0908333333
37 2.0975 -0.0075
38 2.415 0.125
39 2.975 -0.005
40 4.3875 -0.0375
41 2.3575 0.2025
42 2.19 0.09
43 2.49 0.2
44 2.4875 -0.0075
45 2.7025 0.0275
46 2.4825 -0.1125
47 2.4775 -0.1675
48 2.5425 -0.3125

carlson regression

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
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
tp
Residuals
tp Residual Plot

Sheet1

0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
m1
Residuals
m1 Residual Plot

county data

0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
m2
Residuals
m2 Residual Plot

county regression

0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
m3
Residuals
m3 Residual Plot

evaluation

0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
m4
Residuals
m4 Residual Plot
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
m5
Residuals
m5 Residual Plot
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
m6
Residuals
m6 Residual Plot
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
m7
Residuals
m7 Residual Plot
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
m8
Residuals
m8 Residual Plot
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
m9
Residuals
m9 Residual Plot
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
m10
Residuals
m10 Residual Plot
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
m11
Residuals
m11 Residual Plot
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
30 30
31 31
32 32
33 33
34 34
35 35
36 36
37 37
38 38
39 39
40 40
41 41
42 42
43 43
44 44
45 45
46 46
47 47
48 48
sales
Predicted sales
tp
sales
tp Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
sales
Predicted sales
m1
sales
m1 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
sales
Predicted sales
m2
sales
m2 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
sales
Predicted sales
m3
sales
m3 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
sales
Predicted sales
m4
sales
m4 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
sales
Predicted sales
m5
sales
m5 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
sales
Predicted sales
m6
sales
m6 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
sales
Predicted sales
m7
sales
m7 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
sales
Predicted sales
m8
sales
m8 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
sales
Predicted sales
m9
sales
m9 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
sales
Predicted sales
m10
sales
m10 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
sales
Predicted sales
m11
sales
m11 Line Fit Plot
1.71
1.9
2.74
4.2
1.45
1.8
2.03
1.99
2.32
2.2
2.13
2.43
1.9
2.13
2.56
4.16
2.31
1.89
2.02
2.23
2.39
2.14
2.27
2.21
1.89
2.29
2.83
4.04
2.31
1.99
2.42
2.45
2.57
2.42
2.4
2.5
2.09
2.54
2.97
4.35
2.56
2.28
2.69
2.48
2.73
2.37
2.31
2.23
month sales 12-Qtr MA Centered MA SxI Seasonal Index Sales/ seasonal tp trend Forecast Error
1 9 1.71 0.797249179 2.1448752096 1
2 10 1.9 0.9362628522 2.0293446392 2
3 11 2.74 1.1197942445 2.4468780882 3
4 12 4.2 1.6784453362 2.5023156307 4
5 1 1.45 0.9571993096 1.5148360278 5
6 2 1.8 0.8199722675 2.195196193 6
7 3 2.03 2.2416666667 2.2495833333 0.9023893314 0.907694174 2.2364360797 7
8 4 1.99 2.2575 2.2670833333 0.8777798199 0.9300082293 2.139766012 8
9 5 2.32 2.2766666667 2.2691666667 1.0224017628 1.0119167178 2.2926787938 9
10 6 2.2 2.2616666667 2.26 0.9734513274 0.9378242468 2.3458553216 10
11 7 2.13 2.2583333333 2.2941666667 0.9284417 0.9362999804 2.2749119347 11
12 8 2.43 2.33 2.33375 1.0412426352 0.9750253216 2.4922429666 12
9 1.9 2.3375 2.3370833333 0.8129791407 0.797249179 2.3831946774 13
10 2.13 2.3366666667 2.3466666667 0.9076704545 0.9362628522 2.2750021481 14
11 2.56 2.3566666667 2.3595833333 1.0849373124 1.1197942445 2.2861342721 15
12 4.16 2.3625 2.36 1.7627118644 1.6784453362 2.4784840533 16
1 2.31 2.3575 2.3633333333 0.9774330042 0.9571993096 2.4132904995 17
2 1.89 2.3691666667 2.36 0.8008474576 0.8199722675 2.3049560027 18
3 2.02 2.3508333333 2.3504166667 0.8594220883 0.907694174 2.2254191532 19
4 2.23 2.35 2.3566666667 0.946251768 0.9300082293 2.3978282446 20
5 2.39 2.3633333333 2.3745833333 1.0064923671 1.0119167178 2.3618544471 21
6 2.14 2.3858333333 2.3808333333 0.8988449422 0.9378242468 2.2818774492 22
7 2.27 2.3758333333 2.3758333333 0.9554542266 0.9362999804 2.4244366628 23
8 2.21 2.3758333333 2.38 0.9285714286 0.9750253216 2.2666078009 24
9 1.89 2.3841666667 2.4008333333 0.7872266574 0.797249179 2.3706515475 25
10 2.29 2.4175 2.4266666667 0.9436813187 0.9362628522 2.4458943283 26
11 2.83 2.4358333333 2.4433333333 1.1582537517 1.1197942445 2.5272499962 27
12 4.04 2.4508333333 2.4625 1.6406091371 1.6784453362 2.406989321 28
1 2.31 2.4741666667 2.4795833333 0.9316081331 0.9571993096 2.4132904995 29
2 1.99 2.485 2.4970833333 0.7969297514 0.8199722675 2.4269113467 30
3 2.42 2.5091666667 2.5175 0.9612711023 0.907694174 2.6660962132 31
4 2.45 2.5258333333 2.53625 0.9659931 0.9300082293 2.6343852912 32
5 2.57 2.5466666667 2.5525 1.0068560235 1.0119167178 2.5397346984 33
6 2.42 2.5583333333 2.57125 0.9411764706 0.9378242468 2.5804408538 34
7 2.4 2.5841666667 2.5945833333 0.9250040148 0.9362999804 2.5632810532 35
8 2.5 2.605 2.6170833333 0.955261901 0.9750253216 2.5640359739 36
9 2.09 2.6291666667 2.6404166667 0.791541739 0.797249179 2.6215141451 37
10 2.54 2.6516666667 2.6529166667 0.9574367834 0.9362628522 2.7129133597 38
11 2.97 2.6541666667 2.6608333333 1.1161916693 1.1197942445 2.6522729642 39
12 4.35 2.6675 2.6654166667 1.632015007 1.6784453362 2.5916840461 40
1 2.56 2.6633333333 2.6595833333 0.9625567915 0.9571993096 2.674469125 41
2 2.28 2.6558333333 2.6445833333 0.8621395935 0.8199722675 2.7805818445 42
3 2.69 2.6333333333 0.907694174 2.9635532287 43
4 2.48 0.9300082293 2.6666430703 44
5 2.73 1.0119167178 2.6978504772 45
6 2.37 0.9378242468 2.5271259601 46
7 2.31 0.9362999804 2.4671580137 47
8 2.23 0.9750253216 2.2871200887 48
3 4 5 6 7 8 9 10 11 12 1 2
0.9023893314 0.8777798199 1.0224017628 0.9734513274 0.9284417 1.0412426352 0.8129791407 0.9076704545 1.0849373124 1.7627118644 0.9774330042 0.8008474576
0.8594220883 0.946251768 1.0064923671 0.8988449422 0.9554542266 0.9285714286 0.7872266574 0.9436813187 1.1582537517 1.6406091371 0.9316081331 0.7969297514
0.9612711023 0.9659931 1.0068560235 0.9411764706 0.9250040148 0.955261901 0.791541739 0.9574367834 1.1161916693 1.632015007 0.9625567915 0.8621395935
average 0.907694174 0.9300082293 1.0119167178 0.9378242468 0.9362999804 0.9750253216 0.797249179 0.9362628522 1.1197942445 1.6784453362 0.9571993096 0.8199722675
sales tp m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 m11
55.8 1 0 0 0 0 0 0 0 0 1 0 0
56.4 2 0 0 0 0 0 0 0 0 0 1 0
71.4 3 0 0 0 0 0 0 0 0 0 0 1
117.6 4 0 0 0 0 0 0 0 0 0 0 0
46.8 5 1 0 0 0 0 0 0 0 0 0 0
48 6 0 1 0 0 0 0 0 0 0 0 0
60 7 0 0 1 0 0 0 0 0 0 0 0
57.6 8 0 0 0 1 0 0 0 0 0 0 0
61.8 9 0 0 0 0 1 0 0 0 0 0 0
58.2 10 0 0 0 0 0 1 0 0 0 0 0
56.4 11 0 0 0 0 0 0 1 0 0 0 0
63 12 0 0 0 0 0 0 0 1 0 0 0
57.6 13 0 0 0 0 0 0 0 0 1 0 0
53.4 14 0 0 0 0 0 0 0 0 0 1 0
71.4 15 0 0 0 0 0 0 0 0 0 0 1
114 16 0 0 0 0 0 0 0 0 0 0 0
46.8 17 1 0 0 0 0 0 0 0 0 0 0
48.6 18 0 1 0 0 0 0 0 0 0 0 0
59.4 19 0 0 1 0 0 0 0 0 0 0 0
58.2 20 0 0 0 1 0 0 0 0 0 0 0
60.6 21 0 0 0 0 1 0 0 0 0 0 0
55.2 22 0 0 0 0 0 1 0 0 0 0 0
51 23 0 0 0 0 0 0 1 0 0 0 0
58.8 24 0 0 0 0 0 0 0 1 0 0 0
49.8 25 0 0 0 0 0 0 0 0 1 0 0
54.6 26 0 0 0 0 0 0 0 0 0 1 0
65.4 27 0 0 0 0 0 0 0 0 0 0 1
102 28 0 0 0 0 0 0 0 0 0 0 0
43.8 29 1 0 0 0 0 0 0 0 0 0 0
45.6 30 0 1 0 0 0 0 0 0 0 0 0
57.6 31 0 0 1 0 0 0 0 0 0 0 0
53.4 32 0 0 0 1 0 0 0 0 0 0 0
56.4 33 0 0 0 0 1 0 0 0 0 0 0
52.8 34 0 0 0 0 0 1 0 0 0 0 0
54 35 0 0 0 0 0 0 1 0 0 0 0
60.6 36 0 0 0 0 0 0 0 1 0 0 0
47.4 37 0 0 0 0 0 0 0 0 1 0 0
54.6 38 0 0 0 0 0 0 0 0 0 1 0
67.8 39 0 0 0 0 0 0 0 0 0 0 1
100.2 40 0 0 0 0 0 0 0 0 0 0 0
48 41 1 0 0 0 0 0 0 0 0 0 0
51.6 42 0 1 0 0 0 0 0 0 0 0 0
57.6 43 0 0 1 0 0 0 0 0 0 0 0
58.2 44 0 0 0 1 0 0 0 0 0 0 0
60 45 0 0 0 0 1 0 0 0 0 0 0
57 46 0 0 0 0 0 1 0 0 0 0 0
57.6 47 0 0 0 0 0 0 1 0 0 0 0
61.8 48 0 0 0 0 0 0 0 1 0 0 0
69
75
85.2
121.8
60.5375
10.7041090233
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.9845193661 county regression
R Square 0.9692783821
Adjusted R Square 0.958745256 0.7291666667
Standard Error 3.2426113815 7.66684375
Observations 48
ANOVA
df SS MS F Significance F
Regression 12 11610.804 967.567 92.02190982 8.72253186566655E-23
Residual 35 368.0085 10.5145285714
Total 47 11978.8125
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 110.4758333333 1.7937782629 61.5883443456 2.8030194183941E-37 106.834265411 114.1174012556 106.834265411 114.1174012556
tp -0.0920833333 0.0348849441 -2.6396296651 0.0123108953 -0.1629036215 -0.0212630452 -0.1629036215 -0.0212630452
m1 -62.0079166667 2.29313786 -27.0406405772 4.80438389251601E-25 -66.6632397048 -57.3525936285 -66.6632397048 -57.3525936285
m2 -59.8158333333 2.293933766 -26.0756584251 1.61649687311951E-24 -64.4727721486 -55.1588945181 -64.4727721486 -55.1588945181
m3 -49.52375 2.2952596628 -21.5765348047 8.36709392382501E-22 -54.183380532 -44.864119468 -54.183380532 -44.864119468
m4 -51.2316666667 2.2971146325 -22.3026164831 2.83581121492046E-22 -55.895062992 -46.5682703413 -55.895062992 -46.5682703413
m5 -48.2895833333 2.2994973948 -21.0000600313 2.02064667876997E-21 -52.9578169293 -43.6213497374 -52.9578169293 -43.6213497374
m6 -52.0975 2.3024063111 -22.6274136536 1.76513847414242E-22 -56.7716390172 -47.4233609828 -56.7716390172 -47.4233609828
m7 -53.0554166667 2.30583939 -23.0091553192 1.01874369300846E-22 -57.7365252131 -48.3743081202 -57.7365252131 -48.3743081202
m8 -46.6633333333 2.3097942944 -20.2023762229 7.08699089938482E-21 -51.3524707723 -41.9741958943 -51.3524707723 -41.9741958943
m9 -56.07625 2.2952596628 -24.4313316306 1.40752939713777E-23 -60.735880532 -51.416619468 -60.735880532 -51.416619468
m10 -53.8841666667 2.293933766 -23.4898528738 5.15678267106364E-23 -58.5411054819 -49.2272278514 -58.5411054819 -49.2272278514
m11 -39.5420833333 2.29313786 -17.243657271 1.10409711324045E-18 -44.1974063715 -34.8867602952 -44.1974063715 -34.8867602952
RESIDUAL OUTPUT
Observation Predicted sales Residuals Intercept 110.4758333333
1 54.3075 1.4925 tp -0.0920833333
2 56.4075 -0.0075 49 m9 -56.07625 49.8875
3 70.6575 0.7425 50 m10 -53.8841666667 51.9875
4 110.1075 7.4925 51 m11 -39.5420833333 66.2375
5 48.0075 -1.2075 52 m12 0 105.6875
6 50.1075 -2.1075
7 60.3075 -0.3075
8 58.5075 -0.9075
9 61.3575 0.4425
10 57.4575 0.7425
11 56.4075 -0.0075
12 62.7075 0.2925
13 53.2025 4.3975
14 55.3025 -1.9025
15 69.5525 1.8475
16 109.0025 4.9975
17 46.9025 -0.1025
18 49.0025 -0.4025
19 59.2025 0.1975
20 57.4025 0.7975
21 60.2525 0.3475
22 56.3525 -1.1525
23 55.3025 -4.3025
24 61.6025 -2.8025
25 52.0975 -2.2975
26 54.1975 0.4025
27 68.4475 -3.0475
28 107.8975 -5.8975
29 45.7975 -1.9975
30 47.8975 -2.2975
31 58.0975 -0.4975
32 56.2975 -2.8975
33 59.1475 -2.7475
34 55.2475 -2.4475
35 54.1975 -0.1975
36 60.4975 0.1025
37 50.9925 -3.5925
38 53.0925 1.5075
39 67.3425 0.4575
40 106.7925 -6.5925
41 44.6925 3.3075
42 46.7925 4.8075
43 56.9925 0.6075
44 55.1925 3.0075
45 58.0425 1.9575
46 54.1425 2.8575
47 53.0925 4.5075
48 59.3925 2.4075
Carlson Regression County Regression carlson carlson county county
regression ms regression ms
Intercept 3.9430555556 R Square 0.9472225338 Intercept 110.4758333333 R Square 0.9692783821 sept 2.2308333333 2.16 49.8875 50.55
tp 0.0111111111 MSE 0.026552381 tp -0.0920833333 MSE 10.5145285714 oct 2.5483333333 2.54 51.9875 53.2
m1 -2.0411111111 Standard Error 0.1629490134 m1 -62.0079166667 Standard Error 3.2426113815 nov 3.1083333333 3.06 66.2375 66.78
m2 -2.2197222222 PFE 13.3949666153 m2 -59.8158333333 PFE 10.7041090233 dec 4.5208333333 4.6 105.6875 103.11
m3 -1.9308333333 Mse (corrected) 0.0193611111 m3 -49.52375 Mse (corrected) 7.66684375 Pfe 13.3949666153 14.2167437083 10.7041090233 8.9134833781
m4 -1.9444444444 m4 -51.2316666667 **** ***
m5 -1.7405555556 m5 -48.2895833333 average of forecasts carlson county
m6 -1.9716666667 m6 -52.0975 sept 2.1954166667 50.21875
m7 -1.9877777778 m7 -53.0554166667 oct 2.5441666667 52.59375
m8 -1.9338888889 m8 -46.6633333333 nov 3.0841666667 66.50875
m9 -2.2566666667 m9 -56.07625 dec 4.5604166667 104.39875
m10 -1.9502777778 m10 -53.8841666667
m11 -1.4013888889 m11 -39.5420833333 county actual lift factor
50.21875 69 1.373988799
forecast forecast 52.59375 75 1.4260249554
3.9430555556 yintercept Intercept 110.4758333333 66.50875 85.2 1.2810344504
0.0111111111 tp tp -0.0920833333 104.39875 121.8 1.1666806355
49 -2.2566666667 m9 2.2308333333 49 m9 -56.07625 49.8875 m9
50 -1.9502777778 m10 2.5483333333 50 m10 -53.8841666667 51.9875 m10 carlson lift factor lost sales
51 -1.4013888889 m11 3.1083333333 51 m11 -39.5420833333 66.2375 m11 sept 2.1954166667 1.373988799 3.0164779091
52 0 m12 4.5208333333 52 m12 0 105.6875 m12 oct 2.5441666667 1.4260249554 3.6280451575
nov 3.0841666667 1.2810344504 3.9509237506
dec 4.5604166667 1.1666806355 5.320549815
Management Scientist Management Scientist 15.9159966323
jan 0.957 jan 0.773 ms only regression
feb 0.819 feb 0.813 carlson county carlson county
mar 0.907 MSE 0.03 mar 0.976 MSE 7.28 sept 2.16 50.55 sept 2.2308333333 49.8875
apr 0.929 standard error 0.173 apr 0.935 standard error 2.698 oct 2.54 53.2 oct 2.5483333333 51.9875
may 1.011 PFE 14.2167437083 may 0.989 PFE 8.9134833781 nov 3.06 66.78 nov 3.1083333333 66.2375
jun 0.937 jun 0.924 dec 4.6 103.11 dec 4.5208333333 105.6875
july 0.936 july 0.901
aug 0.974 aug 1.017 county actual lift factor county actual lift factor
sept 0.797 sept 0.861 50.55 69 1.3649851632 49.8875 69 1.383112002
oct 0.936 oct 0.907 53.2 75 1.4097744361 51.9875 75 1.4426544843
nov 1.119 nov 1.141 66.78 85.2 1.2758310872 66.2375 85.2 1.2862804303
dec 1.677 dec 1.763 103.11 121.8 1.1812627291 105.6875 121.8 1.1524541691
forecast forecast carlson lift factor lost sales carlson lift factor lost sales
sept 2.16 sept 50.55 sept 2.16 1.3649851632 2.9483679525 sept 2.2308333333 1.383112002 3.0854923578
oct 2.54 oct 53.2 oct 2.54 1.4097744361 3.5808270677 oct 2.5483333333 1.4426544843 3.6763645107
nov 3.06 nov 66.78 nov 3.06 1.2758310872 3.9040431267 nov 3.1083333333 1.2862804303 3.9981883374
dec 4.6 dec 103.11 dec 4.6 1.1812627291 5.433808554 dec 4.5208333333 1.1524541691 5.2100532229
12.36 15.8670467008 12.4083333333 15.9700984289