need it for tomorrow
d>t
d> >ChartDataSheet_
workshee contains values required for MegaStat charts.
.2 333
33333333
3 333333
8
86.6 2333333 633333333 88.11 333333 86.61 333333 87.3633333333 88.113 33333 8
86.6132333333 87.3633333333 88.1134333333 86.6132333333 87.3633333333 88.1134333333 86.6132333333 87.3633333333 88.1134333333 /2 :34. .000
0 2
0 1.3 2.7482 0 1.3 2.7482 0 1.3 2.7482 0 1.3 2.7482 ed
and Deseasonalization Moving t Cost Average 6
. 4
57
7
. . 7
54
8
2
8
5
2 2 1.882 2 3 0
1
1.057 0.574 0
0.679 2 9 0.333 0.649 1.324 1.725 1.820 0
1.882 1.416 1.057 0.574 0.287 0.679 30
0.252 0.333 0.649 1.324 56
1.725 01
1.820 1.882 1.416 1.057 0.574 0.287 0.679 0.252 0.333 0.649 1.324 1.725 1.461 1.580 0.478 0.281 0.271 0.454 0.463 0.772 1.079 1.987 1.820 1.882 1.416 1.057 0.574 0.287 0.679 0.252 0.333 0.649 1.324 1.725 Analysis
48 1 Deseasonalized 5,601.7827 p-value .0017 lower lower upper 2986
5 6 16:34.35.000
Deseasonalization 19.35 29.02 94.09 101.65 118.86 75.62 29.23 17.1 27.64 28.86 48.21 67.15000000000001 125.18 101.44 122.2 99.49 55.85 44.94 19.57 15.98 14.97 18.03 56.98 115.27 130.95 155.37 148.77 115.12 85.89 46.84 24.93 20.84 26.94 34.17 8
100.63 174.63 Deseasonalized
1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 31.0 32.0 33.0 34.0 35.0 36.0 37.0 38.0 39.0 40.0 41.0 42.0 43.0 44.0 45.0 46.0 47.0 48.0 43.39096623911426 44.85605375214149 46.27416789973552 59.2266703092875 50.89763461711603 63.05354128008874 134.8333225075606 25.74987388404096 58.10881216450544 44.69441097039092 71.0599262409136 58.91647922984285 65.30071216993062 59.12988326801124 53.39109820839182 73.29536979010387 50.8802277653318 59.56992021489047 24.42814044338136 109.83433860415 86.66771674768098 74.24939878988787 50.71393396830002 72.5544994588463 55.73030660035135 64.91484804016685 70.24438456430708 52.84040793568222 78.2263919183719 68.1744642459302 23.52993877548126 59.48697716729833 54.14480017188801 87.75629004455115 87.05577317238932 75.8987993620061 85.35900765473768 79.02931213531608 81.27986281076524 81.26164078058631 81.5336937573774 86.84667315539293 30. 68610288366893 107.0527164253185 102.6138558998011 136.4242220453903 75.9991537636639 101.2157871904324 Month Control Chart for the Mean 6 8 87.72 87.17999999999999 87.1 87.34 86.61323333333333 86.61323333333333 86.61323333333333 86.61323333333333 86.61323333333333 86.61323333333333 87.36333333333333 87.36333333333333 87.36333333333333 87.36333333333333 87.36333333333333 87.36333333333333 88.11343333333333 88.11343333333333 88.11343333333333 88.11343333333333 88.11343333333333 88.11343333333333
86.61323333333333
87.36333333333333
88.11343333333333 Sample Number Sample Mean Control Chart for the Range 0.900000000000006 1.599999999999994 1.5 2.0 0.0 1.799999999999997 0.0 0.0 0.0 0.0 0.0 0.0 1.3 1.3 1.3 1.3 1.3 1.3 2.748199999999999 2.748199999999999 2.748199999999999 2.748199999999999 2.748199999999999 2.748199999999999
0.0
1.3
2.748199999999999 Sample Number Sample Range ing (fantastic exercise) & QC
78.98 84.44 65.54 62.6 29.24 18.1 91.57 6.48 19.35 29.02 94.09 101.65 Jan 118.86 Jan 101.44 1.820 1.882 1.416 1.057 0.574 50.898 0.287 63.054 1.568 0.679 134.833 0.106 0.252 0.308 0.333 58.109 63.777 0.455 0.649 44.694 64.396 1.461 1.324 71.060 64.354 1.580 1.725 58.916 61.188 1.943 1.820 65.301 58.946 1.888 1.882 59.130 60.224 1.256 1.416 53.391 1.261 1.057 73.295 61.097 0.478 0.574 50.880 60.955 0.281 0.287 59.570 61.209 0.271 0.679 24.428 0.454 0.252 109.834 62.385 0.463 0.333 86.668 62.479 0.772 0.649 62.233 1.079 1.324 50.714 62.990 1.987 1.725 72.554 63.068 1.608 1.820 55.730 62.515 1.955 1.882 64.915 61.535 1.617 1.416 70.244 61.450 0.909 1.057 63.820 0.704 0.574 78.226 66.065 0.296 0.287 68.174 68.553 0.233 0.679 23.530 71.907 0.208 0.252 59.487 73.665 0.245 0.333 54.145 75.568 0.754 0.649 87.756 76.899 1.499 1.324 87.056 77.202 1.696 1.725 75.899 77.628 2.001 1.820 85.359 78.329 1.899 1.882 79.029 79.500 1.448 1.416 81.280 81.489 1.054 1.057 81.262 82.196 0.570 0.574 81.534 83.406 0.299 0.287 86.847 0.679 30.686 0.252 0.333 102.614 0.649 136.424 1.324 75.999 1.725 101.216 Year Month Cost 1 2 3 4 5 87.1 87.3 87.0 87.0 88.5 87.5 87.5 86.9 87.6 88.0 87.2 87.6 87.1 87.1 87.1 87.1 87.1 87.1 88.0 87.4 87.3 Quality Control Process Charts Sample size 5 Mean Range &P of &N
Forecast 2013
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 160.231479316853 167.18119183200 72 126.8892444654047 95.51637676417315 52.36391211917345 26.38888939310198 62.96170084048643 23.52654201405185 31.3909658139636 61.71456680247302 126.8851407085733 166.6795967518449 Control Chart for the Mean Control Chart for the Range
2
This
t
Xbar Plot data
8
7
6
86.6
1
3
23
33
87.
36
88.
11
4
87.
5
13
87.3
34
87.72
32
43
87.1
87.1 86.6132333333 87.3633333333 88.1134333333
87.34
Rbar Plot data 11/1
9
0
12
16
35
0.9
1.3
2.7
48
1.6
1.5
2 0 1.3 2.7482
0 0 1.3 2.7482
1.8
Output
Center
Moving
Average
Centered
Ratio to
Seasonal
Cost
Year
Month
CMA
Indexes
Deseasonalized
1 1 1
78.98
1.8
20
43.
39
1
2 1 2
84.
44
1.882
44.8
56
3 1 3
65.
54
1.
41
46
27
4 1 4
62.
60
1.0
59.
22
5 1 5
29
24
0.574
50.898
6 1 6
18
10
0.
28
63.0
7 1 7
91.
57
58.4
17
1.568
0.679
134.833
8 1 8
6.
48
61.
19
0.106
0.
25
25.7
50
9 1 9
19.35
62.7
38
0.
30
0.333
58.109
10 1 10
29.02
63.777
0.
45
0.649
44.694
11 1 11
94.09
64.396
1.461
1.324
71.060
12 1 12
101.65
64.354
1.580
1.725
58.916
13 2 1
118.86
61.188
1.943
1.820
65.301
14
111.
31
58.946
1.888
59.130
15
75.62
60.224
1.256
1.416
53.391
16 2 4
77.
47
61.
42
1.
26
73.295
17 2 5
29.23
61.097
0.478
50.880
18 2 6
17.1
60.955
0.281
0.287
59.570
19 2 7
16.
59
61.209
0.271
24.428
20 2 8
27.64
60.9
37
0.454
0.252
109.834
21
28.86
62.385
0.463
86.668
22 2 10
48.21
62.479
0.772
74.2
49
23 2 11
67.15
62.233
1.079
50.714
24 2 12
125.18
62.990
1.987
72.554
25 3 1
101.44
63.068
1.608
55.730
26 3 2
122.2
62.515
1.955
64.915
27 3 3
99.49
61.535
1.617
70.244
28 3 4
55.85
61.450
0.909
52.8
40
29 3 5
44.94
63.820
0.704
78.226
30 3 6
19.57
66.065
0.296
68.174
31 3 7
15.98
68.553
0.233
23.5
32 3 8
14.97
71.907
0.208
59.487
33 3 9
18.03
73.665
0.245
54.145
34 3 10
56.98
75.568
0.754
87.756
35 3 11
115.27
76.899
1.499
87.0
36 3 12
130.95
77.202
1.696
75.899
37 4 1
155.37
77.628
2.0
85.359
38 4 2
148.77
78.329
1.899
79.029
39 4 3
115.12
79.500
1.448
81.280
40 4 4
85.89
81.489
1.054
81.262
41 4 5
46.84
82.196
0.570
81.534
42 4 6
24.93
83.406
0.299
86.847
43 4 7
20.84
30.686
44 4 8
26.94
107.0
53
45 4 9
34.17
102.614
46 4 10
88.
58
136.424
47 4 11
100.63
75.999
48 4 12
174.63
101.216
Calculation of Seasonal Indexes
1 2 3 4 5 6 7 8 9 10 11 12
1 1.568 0.106
0.308
0.455
2 1.943 1.888 1.256
1.261
3 1.608 1.955 1.617 0.909 0.704 0.296 0.233 0.208 0.245 0.754 1.499 1.696
4 2.001 1.899 1.448 1.054 0.570 0.299
mean:
1.851
1.914
1.440
1.075
0.584
0.292
0.691
0.256
0.339
0.660
1.346
1.754
12.202
adjusted:
12.000
Regression
r²
0.194
n
r
0.441
k
Std. Error
22.473
Dep. Var.
ANOVA table
Source
SS
df
MS
F
p-value
Regression
5,601.7827
1
11.09
.0017
Residual
23,231.9286
46
505.0419
Total
28,833.7112
47
Regression output
confidence interval
variables
coefficients
std. error
t (df=46)
95%
lower
95% upper
Intercept
49.8194
6.590145953808421
7.559681821289353
1.3279221317601898E-9
36.554130988226404
63.08468214507181
t
0.7798
0.2341
3.330
0.3085
1.2511
Predicted values for: Deseasonalized
95% Confidence Intervals
95% Prediction Intervals
t
Predicted
upper
Leverage
49
88.0
74.76459
101.29514
40.88890
135.17083
0.086
50
88.80967
75.13216
102.48718
41.55105
136.06829
0.091
51
89.58948
75.49603
103.68292
42.20880
136.97015
0.097
52
90.36928
75.85651
104.88205
42.86219
137.87637
0.103
53
91.14909
76.21389
106.08428
43.51125
138.78692
0.109
54
91.92889
76.56843
107.28935
44.15602
139.70176
0.115
55
92.70870
76.92035
108.49704
44.79654
140.62085
0.122
56
93.48850
77.26986
109.70714
45.43283
141.54417
0.129
57
94.26831
77.61715
110.91946
46.06495
142.47167
0.135
58
95.04811
77.96239
112.13383
46.69292
143.40330
0.143
59
95.82792
78.30573
113.35010
47.31679
144.33905
0.150
60
96.60772
78.64731
114.56813
47.93659
145.27886
0.158
Quality Control Process Charts
Sample size
Number of samples
Mean
Range
Upper Control Limit, UCL
88.113
2.748
Center
87.363
1.300
Lower Control Limit, LCL
86.613
0.000
11/19/
2012
Cost 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 31.0 32.0 33.0 34.0 35.0 36.0 37.0 38.0 39.0 40.0 41.0 42.0 43.0 44.0 45.0 46.0 47.0 48.0 78.98
84.44
65.54
62.6
29.24
18.1
91.57
6.48
111.31
77.47
16.59
88.5
Cost87.2
87.5
Sheet1
Week 5 –
Forecast
You have a job, if you have one, because someone forecasted they could pay you. This week you will learn how to do rather sophisticated forecasting in a simple way. I hope you take this out of this class as you can use it personally.
Sample – forecast monthly cost and graph the forecasted cost using Deseasonization and regression
[Deseasonalize the data and forecast for 2004 by month]
Year Month Cost
2009
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2010
Feb 111.31
Mar 75.62
Apr 77.47
May 29.23
Jun 17.1
Jul 16.59
Aug 27.64
Sep 28.86
Oct 48.21
Nov 67.15
Dec 125.18
2011
Feb 122.2
Mar 99.49
Apr 55.85
May 44.94
Jun 19.57
Jul 15.98
Aug 14.97
Sep 18.03
Oct 56.98
Nov 115.27
Dec 130.95
2012 Jan 155.37
Feb 148.77
Mar 115.12
Apr 85.89
May 46.84
Jun 24.93
Jul 20.84
Aug 26.94
Sep 34.17
Oct 88.58
Nov 100.63
Dec 174.63
Centered Moving Average and Depersonalization
Centered
Moving Ratio to Seasonal Cost
t Year Month Cost Average CMA Indexes
Deseasonalized
1 1 1
78.98
43.391
2 1 2
84.44
44.856
3 1 3
65.54
46.274
4 1 4
62.60
59.227
5 1 5
29.24
6 1 6
18.10
7 1 7
91.57
58.417
8 1 8
6.48
61.198
25.750
9 1 9
19.35
62.738
10 1 10
29.02
11 1 11
94.09
12 1 12
101.65
13 2 1
118.86
14 2 2
111.31
15 2 3
75.62
16 2 4
77.47
61.420
17 2 5
29.23
18 2 6
17.10
19 2 7
16.59
20 2 8
27.64
60.937
21 2 9
28.86
22 2 10
48.21
74.249
23 2 11
67.15
24 2 12
125.18
25 3 1
101.44
26 3 2
122.20
27 3 3
99.49
28 3 4
55.85
52.840
29 3 5
44.94
30 3 6
19.57
31 3 7
15.98
32 3 8
14.97
33 3 9
18.03
34 3 10
56.98
35 3 11
115.27
36 3 12
130.95
37 4 1
155.37
38 4 2
148.77
39 4 3
115.12
40 4 4
85.89
41 4 5
46.84
42 4 6
24.93
43 4 7
20.84
44 4 8
26.94
107.053
45 4 9
34.17
46 4 10
88.58
47 4 11
100.63
48 4 12
174.63
Predicted values for: Deseasonalized
Seasonal
t Predicted Indexes Forecast
Jan 88.02986 1.820
160.2
Feb 88.80967 1.882
167.2
Mar 89.58948 1.416
126.9
Apr 90.36928 1.057
95.5
May 91.14909 0.574
52.4
Jun 91.92889 0.287
26.4
Jul 92.70870 0.679 63.0
Aug 93.48850 0.252 23.5
Sep 94.26831 0.333
31.4
Oct 95.04811 0.649
61.7
Nov 95.82792 1.324 126.9
Dec 96.60772 1.725
166.7
1.0
USING THE SAME DATA AS ABOVE —-Your turn to do the same this as above.
2009 Jan 78.98
Feb 84.44
Mar 65.54
Apr 62.6
May 29.24
Jun 18.1
Jul 91.57
Aug 6.48
Sep 19.35
Oct 29.02
Nov 94.09
Dec 101.65
2010 Jan 118.86
Feb 111.31
Mar 75.62
Apr 77.47
May 29.23
Jun 17.1
Jul 16.59
Aug 27.64
Sep 28.86
Oct 48.21
Nov 67.15
Dec 125.18
2011 Jan 101.44
Feb 122.2
Mar 99.49
Apr 55.85
May 44.94
Jun 19.57
Jul 15.98
Aug 14.97
Sep 18.03
Oct 56.98
Nov 115.27
Dec 130.95
2012 Jan 155.37
Feb 148.77
Mar 115.12
Apr 85.89
May 46.84
Jun 24.93
Jul 20.84
Aug 26.94
Sep 34.17
Oct 88.58
Nov 100.63
Dec 174.63
Now we end the class showing the QC is all based upon statistics
A new machine has jus been installed to cut and rough shape slugs. The slugs are then transferred to a
precision grinder. One of the measurements is the outside diameter. The quality control inspector
randomly selected five slugs each hour, measured the outside diameter, and recorded the results.
The measurements follow. Develop/make a Six Sigma Quality Control Chart.
Outside Diameter
Time
8:00
87.9
8:30
86.9
87.6
87.4
9:00
88.4
88.2
9:30
86.0
10:00
10:30
86.2
87.8
Number of samples 6
Upper Control Limit, UCL 88.113 2.748
Center 87.363 1.300
Lower Control Limit, LCL 86.613 0.000 11/19/2012 16:34.35.000
Note all points are in the control ranges
2.0
Your Turn – you do yourws in the final test
87.26 87.58 87.72 87.17999999999999 87.1 87.34 86.61323333333333 86.61323333333333 86.61323333333333 86.61323333333333 86.61323333333333 86.61323333333333 87.36333333333333 87.36333333333333 87.36333333333333 87.36333333333333 87.36333333333333 87.36333333333333 88.11343333333333 88.11343333333333 88.11343333333333 88.11343333333333 88.11343333333333 88.11343333333333
86.61323333333333
87.36333333333333
88.11343333333333 Sample Number
Sample Mean
0.900000000000006 1.599999999999994 1.5 2.0 0.0 1.799999999999997 0.0 0.0 0.0 0.0 0.0 0.0 1.3 1.3 1.3 1.3 1.3 1.3 2.748199999999999 2.748199999999999 2.748199999999999 2.748199999999999 2.748199999999999 2.748199999999999
0.0
1.3
2.748199999999999 Sample Number
Sample RangeSheet2
Sheet3