Run Heading (x1) Email Open(x2) Body(x3) x1 x2 x1x3 x2x3 x1x2x3 R Rate 1 R Rate 2 Ave RR SD RR 1 Generic(-) No(-) Text(-) + + + - 46 38 42 5.656854 2 Detailed(+) No(-) Text(-) - - + + 34 38 36 2.828427 3 Generic(-) Yes(+) Text(-) - + - + 56 59 57.5 2.12132 4 Detailed(+) Yes(+) Text(-) + - - - 68 80 74 8.485281 5 Generic (-) No(-) HTML(+) + - - + 25 27 26 1.414214 6 Detailed(+) No(-) HTML(+) - + - - 22 32 27 7.071068 7 Generic(-) Yes(+) HTML(+) - - + - 21 23 22 1.414214 8 Detailed(+) Yes(+) HTML(+) + + + + 19 33 26 9.899495 sum+ 163 179.5 101 168 152.5 126 145.5 sum- 147.5 131 209.5 143 158 185 165 ave + 40.75 44.875 25.25 42 38.13 31.5 36.375 ave- 36.875 32.75 52.375 35.6 39.5 46.1 41.25 effect 3.875 12.125 -27.125 6.38 -1.38 -15 -4.875 b0 = 77.625 b1= 1.9375 b2= 6.0625 b3= -13.5625 b4= 3.1875 b5 = -0.6875 b6= -7.3125 b7= -2.4375 Regression Model is y = b0 + b1x1 + b2x2 + b3x3 + b4x1x2 + b5x1x3 + b6x2x3 + b7 x1 x2 x3 y = 77.625 + 1.9375 x1 + 6.0625 X2 -13.5625 x3 + 3.1875 x1 x2 -0.6875x1x3 -7.3125 x2x3 - 2.4375 x1 x3 x3 Graphical Analysis Most highest response is detailed, open email, and text. Email Response + + + + + - - - - - + + - - + + + - + - + - + - response + + + + + - - - - - + + - - + + + - + - + - + - 46 34 56 68 25 22 21 19 response 2 + + + + + - - - - - + + - - + + + - + - + - + - 38 38 59 80 27 32 23 33 Regression old and new processWEEK 7 ASSIGNMENT Old Process New ProcessxySUMMARY OUTPUT (Old Process)WeekElapsed TimeWeekTest WeekElapsed Time131.713124Regression Statistics22714225.8Multiple R0.5745518821333.815331R Square0.330109865243016423.5Adjusted R Square0.2631208517532.517528.5Standard Error3.4883134897633.518625.6Observations12738.219728.7837.520827.4ANOVA92921928.5dfSSMSFSignificance F1031.3221025.2Regression159.963356643459.96335664344.92782096670.05070575211138.6231124.5Residual10121.683310023312.16833100231239.3241223.5Total11181.6466666667Average33.5326.35CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%standard Deviation4.062.43b029.32424242422.146908542213.65882237050.000000085724.540632089634.107852758924.540632089634.1078527589b10.64755244760.29170742842.21986958330.0507057521-0.00241220711.2975171022-0.00241220711.2975171022y = 29.32 + 0.648xRESIDUAL OUTPUTObservationPredicted YResiduals129.97179487181.7282051282230.6193473193-3.6193473193331.26689976692.5331002331431.9144522145-1.9144522145532.562004662-0.062004662633.20955710960.2904428904733.85710955714.3428904429834.50466200472.9953379953935.1522144522-6.15221445221035.7997668998-4.49976689981136.44731934732.15268065271237.09487179492.2051282051SUMMARY OUTPUT (New Process)Regression StatisticsMultiple R0.1713144422R Square0.0293486381Adjusted R Square-0.0677164981Standard Error2.5093057575Observations12ANOVAdfSSMSFSignificance FRegression11.903 ...

1. Run
Heading (x1)
Email Open(x2)
Body(x3)
x1 x2
x1x3
x2x3
x1x2x3
R Rate 1
R Rate 2

2. Ave RR
SD RR
1
Generic(-)
No(-)
Text(-)
+
+
+
-
46
38
42
5.656854
2
Detailed(+)
No(-)
Text(-)
-
-
+
+
34
38
36
2.828427
3
Generic(-)
Yes(+)
Text(-)
-
+
-
+
56
59

3. 57.5
2.12132
4
Detailed(+)
Yes(+)
Text(-)
+
-
-
-
68
80
74
8.485281
5
Generic (-)
No(-)
HTML(+)
+
-
-
+
25
27
26
1.414214
6
Detailed(+)
No(-)
HTML(+)
-
+
-
-
22
32

4. 27
7.071068
7
Generic(-)
Yes(+)
HTML(+)
-
-
+
-
21
23
22
1.414214
8
Detailed(+)
Yes(+)
HTML(+)
+
+
+
+
19
33
26
9.899495

5. sum+
163
179.5
101
168
152.5
126
145.5
sum-
147.5
131
209.5
143
158
185
165
ave +
40.75
44.875
25.25
42
38.13
31.5
36.375

6. ave-
36.875
32.75
52.375
35.6
39.5
46.1
41.25
effect
3.875
12.125
-27.125
6.38
-1.38
-15
-4.875

7. b0 =
77.625
b1=
1.9375
b2=
6.0625

8. b3=
-13.5625
b4=
3.1875
b5 =
-0.6875

9. b6=
-7.3125
b7=
-2.4375

10. Regression Model is
y = b0 + b1x1 + b2x2 + b3x3 + b4x1x2 + b5x1x3 + b6x2x3 + b7
x1 x2 x3

11. y = 77.625 + 1.9375 x1 + 6.0625 X2 -13.5625 x3 + 3.1875 x1
x2 -0.6875x1x3 -7.3125 x2x3 - 2.4375 x1 x3 x3
Graphical Analysis
Most highest response is detailed, open email, and text.
Email Response
+ + + + + - - - - - + + -
- + + + - + - + - + -
response + + + + + - - - - -
+ + - - + + + - + - + -
+ - 46 34 56 68 25 22 21 19
response 2 + + + + + - - - -
- + + - - + + + - + - +
- + - 38 38 59 80 27 32 23 33
Regression old and new processWEEK 7 ASSIGNMENT Old
Process New ProcessxySUMMARY OUTPUT (Old
Process)WeekElapsed TimeWeekTest WeekElapsed
Time131.713124Regression Statistics22714225.8Multiple
R0.5745518821333.815331R
Square0.330109865243016423.5Adjusted R
Square0.2631208517532.517528.5Standard
Error3.4883134897633.518625.6Observations12738.219728.783

12. 7.520827.4ANOVA92921928.5dfSSMSFSignificance
F1031.3221025.2Regression159.963356643459.96335664344.92
782096670.05070575211138.6231124.5Residual10121.6833100
23312.16833100231239.3241223.5Total11181.6466666667Aver
age33.5326.35CoefficientsStandard Errort StatP-valueLower
95%Upper 95%Lower 95.0%Upper 95.0%standard
Deviation4.062.43b029.32424242422.146908542213.658822370
50.000000085724.540632089634.107852758924.540632089634.
1078527589b10.64755244760.29170742842.21986958330.0507
057521-0.00241220711.2975171022-
0.00241220711.2975171022y = 29.32 + 0.648xRESIDUAL
OUTPUTObservationPredicted
YResiduals129.97179487181.7282051282230.6193473193-
3.6193473193331.26689976692.5331002331431.9144522145-
1.9144522145532.562004662-
0.062004662633.20955710960.2904428904733.85710955714.34
28904429834.50466200472.9953379953935.1522144522-
6.15221445221035.7997668998-
4.49976689981136.44731934732.15268065271237.0948717949
2.2051282051SUMMARY OUTPUT (New Process)Regression
StatisticsMultiple R0.1713144422R
Square0.0293486381Adjusted R Square-0.0677164981Standard
Error2.5093057575Observations12ANOVAdfSSMSFSignificanc
e
FRegression11.90384615381.90384615380.30236024240.59447
37741Residual1062.96615384626.2966153846Total1164.87Coef
ficientsStandard Errort StatP-valueLower 95%Upper 95%Lower
95.0%Upper
95.0%b027.11.544370935117.54759778540.000000007723.6589
27117730.541072882323.658927117730.5410728823b1-
0.11538461540.209838689-0.54987293290.5944737741-
0.58293435110.3521651203-0.58293435110.3521651203y =
27.1 -0.115xRESIDUAL OUTPUTObservationPredicted
YResiduals126.9846153846-2.98461538461-
2.9846153846226.8692307692-1.06923076922-
1.0692307692326.75384615384.246153846234.2461538462426.

13. 6384615385-3.13846153854-
3.1384615385526.52307692311.976923076951.9769230769626.
4076923077-0.80769230776-
0.8076923077726.29230769232.407692307772.4076923077826.
17692307691.223076923181.2230769231926.06153846152.438
461538592.43846153851025.9461538462-0.746153846210-
0.74615384621125.8307692308-1.330769230811-
1.33076923081225.7153846154-2.215384615412-2.2153846154
Old Process New ProcessElapsed TimeElapsed TimeWeekTest
Week131.70.647552447631.0524475524124-
0.115384615424.11538461542271.295104895125.70489510492
25.8-
0.230769230826.0307692308333.81.942657342731.8573426573
331-
0.346153846231.34615384624302.590209790227.40979020984
23.5-
0.461538461523.9615384615532.53.237762237829.2622377622
528.5-
0.576923076929.0769230769633.53.885314685329.6146853147
625.6-
0.692307692326.2923076923738.24.532867132933.6671328671
728.7-
0.807692307729.5076923077837.55.180419580432.3195804196
827.4-
0.923076923128.32307692319295.82797202823.172027972928.
5-
1.038461538529.53846153851031.36.475524475524.824475524
51025.2-
1.153846153826.35384615381138.67.123076923131.476923076
91124.5-
1.269230769225.76923076921239.37.770629370631.529370629
41223.5-
1.384615384624.884615384629.324242424227.1Process
differences during test period0.762.22
Old Process
Y 1 2 3 4 5 6 7 8 9 10 11 12

14. 31.7 27 33.799999999999997 30 32.5 33.5
38.200000000000003 37.5 29 31.3 38.6
39.299999999999997 Predicted Y 1 2 3 4
5 6 7 8 9 10 11 12
29.971794871794874 30.619 347319347323
31.266899766899769 31.914452214452218
32.562004662004668 33.20955710955711
33.85710955710956 34.504662004662009
35.152214452214459 35.799766899766901
36.44731934731935 37.0948717948718
Test week number
elapsed time (day)
X Variable 1 Line Fit Plot
Y 1 2 3 4 5 6 7 8 9 10 11 12
24 25.8 31 23.5 28.5 25.6 28.7 27.4 28.5 25.2 24.5
23.5 Predicted Y 1 2 3 4 5 6 7 8
9 10 11 12 26.984615384615381
26.869230769230768 26.753846153846151
26.638461538461534 26.523076923076921
26.407692307692304 26.292307692307688
26.176923076923075 26.061538461538458
25.946153846153845 25.830769230769228
25.715384615384611
X Variable 1
Y
New Process
Y 1 2 3 4 5 6 7 8 9 10 11 12
24 25.8 31 23.5 28.5 25.6 28.7 27.4 28.5 25.2 24.5
23.5 Predicted Y 1 2 3 4 5 6 7 8
9 10 11 12 26.984615384615381
26.869230769230768 26.753846153846151
26.638461538461534 26.523076923076921
26.407692307692304 26.292307692307688 26.1
76923076923075 26.061538461538458

15. 25.946153846153845 25.830769230769228
25.715384615384611
Test week number
elapsed time (day)
26.984615384615381 26.869230769230768
26.753846153846151 26.638461538461534
26.523076923076921 26.407692307692304
26.292307692307688 26.176923076923075
26.061538461538458 25.946153846153845
25.830769230769228 25.715384615384611 -
2.9846153846153811 -1.0692307692307672
4.2461538461538488 -3.1384615384615344
1.9769230769230788 -0.80769230769230305
2.4076923076923116 1.2230769230769241
2.4384615384615422 -0.74615384615384528 -
1.3307692307692278 -2.2153846153846111
29.971794871794874 30.619347319347323
31.266899766899769 31.914452214452218
32.562004662004668 33.20955710955711
33.85710955710956 34.504662004662009
35.152214452214459 35.799766899766901
36.44731934731935 37.0948717948718
1.7282051282051256 -3.6193473193473231
2.5331002331002281 -1.9144522144522185 -
6.2004662004667921E-2 0.29044289044288973
4.3428904428904431 2.9953379953379908 -
6.1522144522144586 -4.4997668997669003
2.152680652680651 2.2051282051281973

16. 1 2 3 4 5 6 7 8 9 10 11 12 -
2.9846153846153811 -1.0692307692307672
4.2461538461538488 -3.1384615384615344
1.9769230769230788 -0.80769230769230305
2.4076923076923116 1.2230769230769241
2.4384615384615422 -0.74615384615384528 -
1.3307692307692278 -2.2153846153846111
Old vs. new process Old Process New ProcessElapsed
TimeElapsed TimeSUMMARY OUTPUTWeekWeekTest
Week131.713124Regression Statistics22714225.8Multiple
R0.0077382654333.815331R
Square0.000059880843016423.5Adjusted R Square-
0.0999341312532.517528.5Standard
Error2.546882713633.518625.6Observations12738.219728.7837
.520827.4ANOVA92921928.5dfSSMSFSignificance
F1031.3221025.2Regression10.00388446430.00388446430.0005
9884340.98095813291138.6231124.5Residual1064.8661155357
6.48661155361239.3241223.5Total1164.87CoefficientsStandard
Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper
95.0%b026.5050702836.37933748334.15483117990.001964839
112.291020586440.719119979512.291020586440.7191199795b
1-0.00462436230.1889710296-0.02447127650.9809581329-
0.42567805520.4164293306-
0.42567805520.4164293306RESIDUAL
OUTPUTObservationPredicted YResiduals126.3584779976-
2.3584779976226.3802125005-
0.5802125005326.34876683674.6512331633426.3663394135-
2.8663394135526.35477850772.1452214923626.3501541454-
0.7501541454Correlation between old and new
processes726.32841964252.3715803575-

17. 0.0077382654826.33165669611.0683433038926.37096377582.1
2903622421026.3603277425-1.16032774251126.3265698976-
1.82656989761226.323332844-2.823332844
Process Effect (12 weeks test)
Y 31.7 27 33.799999999999997 30 32.5 33.5
38.200000000000003 37.5 29 31.3 38.6
39.299999999999997 24 25.8 31 23.5 28.5 25.6
28.7 27.4 28.5 25.2 24.5 23.5 Predicted Y 31.7 27
33.799999999999997 30 32.5 33.5
38.200000000000003 37.5 29 31.3 38.6
39.299999999999997 26.358477997577715
26.380212500458764 26.348766836715967
26.366339413513412 26.354778507725619
26.350154145410503 26.3 2841964252945
26.331656696150034 26.370963775828532
26.36032774250376 26.326569897603406
26.323332843982822
Old Process
New Process