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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 15 Dec 2010 16:56:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t1292432044bakr3918vd677f4.htm/, Retrieved Fri, 03 May 2024 04:11:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110573, Retrieved Fri, 03 May 2024 04:11:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact176

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- R PD    [Standard Deviation-Mean Plot] [tutorial] [2010-12-13 19:55:01] [2db53827eae1799a3d605fb62e1e92dc]
-    D        [Standard Deviation-Mean Plot] [tutorial9SMP] [2010-12-15 16:56:05] [6e19356a8195a048e2417405f21c29e8] [Current]
- R  D          [Standard Deviation-Mean Plot] [workshop9] [2010-12-17 20:13:38] [8b2514d8f13517d765015fc185a22b4b]
-    D          [Standard Deviation-Mean Plot] [SMP] [2010-12-19 10:46:58] [46df8573ee32a55e1a6edcfb6691f406]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,3866
1,3582
1,3332
1,3595
1,3617
1,3684
1,3394
1,3262
1,3173
1,3085
1,327
1,3182
1,293
1,291
1,2984
1,2795
1,299
1,3174
1,326
1,3111
1,2816
1,276
1,2849
1,2818
1,2829
1,2796
1,3008
1,2967
1,2938
1,2833
1,2823
1,2765
1,2634
1,2596
1,2705
1,2591
1,2798
1,2763
1,2795
1,2782
1,2644
1,2596
1,2615
1,2555
1,2555
1,2658
1,2565
1,2783
1,2786
1,2782
1,2905
1,3042
1,2942
1,313
1,3671
1,3549
1,3558
1,3507
1,3494
1,3607
1,3295
1,3193
1,3308
1,3246
1,3392
1,3425
1,3496
1,3255
1,3231
1,3273
1,3276
1,3173
1,3196
1,3058
1,2966
1,2932
1,2947
1,305
1,3232
1,3125
1,2992
1,3266
1,3275
1,3223
1,3403
1,3322
1,3363
1,3425
1,3574
1,3683
1,3623
1,3563
1,3518
1,3494
1,3612
1,369
1,3771
1,3972
1,401
1,3908
1,3901
1,3856
1,4098
1,422
1,4238
1,4207
1,4095
1,4177
1,3866
1,3959
1,4102
1,3969
1,4004
1,385
1,389
1,384
1,392
1,3932
1,3858
1,3978
1,4029
1,394
1,4096
1,4058
1,4134
1,4096
1,4049
1,4009
1,3897
1,4019
1,3901
1,399
1,3901
1,3975
1,3991
1,4089
1,413
1,409
1,4217
1,4223
1,4191
1,4229
1,4227
1,4269
1,4229
1,4104
1,4053
1,4138
1,4303
1,4384
1,441
1,437
1,4357
1,4202
1,4166
1,417
1,4293
1,4294
1,4072
1,4101
1,4112
1,4243
1,433
1,4323
1,4324
1,427
1,4268
1,4364
1,4272
1,4314
1,422
1,4335
1,4262
1,433
1,4473
1,4522
1,4545
1,4594
1,4561
1,4611
1,4671
1,4712
1,4705
1,4658
1,478
1,4783
1,4768
1,467
1,465
1,4549
1,4643
1,4539
1,4537
1,4616
1,4722
1,4694
1,4763
1,475
1,4765
1,4864
1,4881
1,4864
1,4869
1,4918
1,4971
1,4921
1,5
1,502
1,5019
1,4874
1,4785
1,4788
1,48
1,4772
1,4658
1,4761
1,4867
1,4862
1,4984
1,4966
1,5037
1,4922
1,4868
1,4965
1,4875
1,4957
1,4863
1,4815
1,4968
1,4969
1,5083
1,5071
1,4918
1,5023
1,5074
1,509
1,512
1,5068
1,4787
1,4774
1,4768
1,473
1,4757
1,4647
1,4541
1,456
1,4343
1,4337
1,4368
1,4279
1,4276
1,4398
1,4405
1,4433
1,4338
1,4406
1,4389
1,4442
1,435
1,4304
1,4273
1,4528
1,4481
1,4563
1,4486
1,4374
1,4369
1,4279
1,4132
1,4064
1,4135
1,4151
1,4085
1,4072
1,3999
1,3966
1,3913
1,3937
1,3984
1,3847
1,3691
1,3675
1,376
1,374
1,3718
1,3572
1,3607
1,3649
1,3726
1,3567
1,3519
1,3626
1,3577
1,3547
1,3489
1,357
1,3525
1,3548
1,3641
1,3668
1,3582
1,3662
1,3557
1,361
1,3657
1,3765
1,3705
1,3723
1,3756
1,366
1,3548
1,3471
1,3519
1,3338
1,3356
1,3353
1,3471
1,3482
1,3479
1,3468
1,3396
1,334
1,3296
1,3384
1,3585
1,3583
1,3615
1,3544
1,3535
1,3432
1,3486
1,3373
1,3339
1,3311
1,3321
1,329
1,3245
1,3256
1,3315
1,3238
1,3089
1,2924
1,2727
1,2746
1,2969
1,2698
1,2686
1,2587
1,2492
1,2349
1,2428
1,227
1,2334
1,2497
1,236
1,2223
1,2309
1,2255
1,2384
1,2307
1,2155
1,2218
1,2268
1,206
1,1959
1,1942
1,201
1,2045
1,2127
1,2249
1,2258
1,2277
1,2363
1,2372
1,2391
1,2258
1,2271
1,2262
1,2294
1,2339
1,2198
1,2271
1,2328
1,2548
1,2531
1,2579
1,2567
1,266
1,2637
1,2572
1,2569
1,2703
1,2828
1,3
1,2957
1,2844
1,2817
1,285
1,2897
1,2931
1,3033
1,2992
1,3069
1,3028
1,3073
1,3221
1,3206
1,3184
1,3176
1,3253
1,3133
1,3016
1,279
1,2799
1,282
1,286
1,288
1,2836
1,2711
1,2704
1,2611
1,2613
1,2693
1,2713
1,27
1,268
1,28
1,2818
1,2834
1,2874
1,2744
1,2697
1,2715
1,2725
1,2801
1,285
1,2989
1,3078
1,306
1,3074
1,312
1,3364
1,3323
1,3412
1,3477
1,346
1,3611
1,3648
1,3726
1,3705
1,378
1,3856
1,397
1,3874
1,3936
1,3833
1,3958
1,4101
1,4089
1,3896
1,3859
1,3861
1,4016
1,3934
1,4031
1,3912
1,3803
1,3857
1,3857
1,3926
1,4018
1,4014
1,4244
1,4084
1,3917
1,3945
1,377
1,37
1,3711
1,3626
1,3612
1,3481
1,3647
1,3674
1,3647
1,3496
1,3339
1,3321
1,3225
1,3146
1,2998

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110573&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110573&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.359840.01892123146098060.0534000000000001
21.331960.02335429296724700.0599000000000001
31.305520.01612798809523370.036
41.30660.01806529822615720.0465
51.281440.003311042132018220.0088999999999999
61.290840.009020698420854060.0211999999999999
71.270460.009279709047163030.0226999999999999
81.274580.008762819181062650.0206999999999999
91.25930.003867169507533870.0088999999999999
101.271480.00998784260989330.0221
111.31380.03106742667167650.0766
121.35430.004487204029236930.0113000000000001
131.328680.007424082434887160.0199000000000000
141.33360.01173413822996820.0265000000000000
151.313380.01219926227277700.0309999999999999
161.305720.01255217112694060.03
171.323180.01499389875916200.0411000000000001
181.347340.01512491322289160.0361
191.35620.005652875374532910.0129000000000001
201.387020.01356915620073700.032
211.406260.01771942436988290.0382
221.406080.01452212105720100.0341
231.39630.009891410415102560.0251999999999999
241.390560.00563808478120010.0138000000000000
251.405140.00737685569873780.0194000000000001
261.40140.007363423117002060.0199000000000000
271.395160.004662402814000580.00900000000000012
281.414980.006621706728631170.0133999999999999
291.42290.002760434748368460.00780000000000003
301.419640.01405962303904330.0330999999999999
311.43010.01093206293432310.0244
321.41860.01043910915739460.0222
331.426640.00934788746188140.0218000000000000
341.429760.004174685616905720.00959999999999983
351.43240.009620031184980680.0253000000000001
361.456660.0036087393920870.00890000000000013
371.470520.00475363019175870.0122
381.46840.009543846184845950.0233999999999999
391.461140.007750677389751160.0185000000000000
401.476720.006133269927208450.0169999999999999
411.490060.004466878104448370.0107000000000002
421.496680.006589157761049570.0145999999999999
431.476060.005821340051912430.0142
441.48880.009020254985309440.0223
451.493340.006990922685883480.0169000000000001
461.491440.007104787118556010.0153999999999999
471.503380.006882368778262340.0165000000000000
481.496780.01720354614607110.0346
491.468860.009514883078630050.0226999999999999
501.437740.01071554944928160.0281
511.4370.006292455800400980.0157000000000000
521.437820.005305845832664220.0138000000000000
531.446620.01130561807244520.0289999999999999
541.424360.01402615414146010.0309999999999999
551.408840.005992328428916460.0152000000000001
561.392940.005347242279904680.0137000000000000
571.371680.003470878851242150.00849999999999995
581.362420.006570920787834860.0159000000000000
591.355160.005287532505810240.0137000000000000
601.359040.006138648059630080.0143000000000000
611.361360.004593800169794090.0105000000000002
621.372180.004224570984135510.0105000000000000
631.344640.009502789064269510.0209999999999999
641.345060.005485708705354350.0129000000000001
651.340020.01105811918908460.0289000000000001
661.354180.006921488279264810.0183
671.33660.007111258679024410.0175000000000001
681.326880.003264506088216050.00769999999999982
691.28910.01535398970951850.0362
701.256240.01455723187972210.0348999999999999
711.237780.008744255257024430.0226999999999999
721.229560.006132536180080790.0161
731.21320.01240302382485820.0308999999999999
741.207460.01181029212170470.0307000000000002
751.233220.006029676608243620.0133000000000001
761.228480.003335715815233670.0081
771.237520.01570181518169160.0349999999999999
781.26030.004253821811030650.00930000000000009
791.281140.01785729542791970.0431000000000001
801.286780.004558179461144520.0113999999999999
811.30390.003324906013709260.0081
821.32080.003081395787626070.00769999999999982
831.291160.01547362271738590.0343
841.279820.008428641646196670.0176000000000001
851.26660.004981967482832450.0102000000000000
861.280120.007305614279442930.0194000000000001
871.273640.003990989852154460.0104000000000000
881.301020.00965152837637650.0228000000000002
891.333920.01352911674870160.0356999999999998
901.3630.01053873806487280.0266000000000000
911.388320.007381869681862490.0190000000000001
921.397540.01178613592319380.0267999999999999
931.394020.00819981707113030.0172000000000001
941.38710.004930010141977390.0123000000000000
951.405540.0121094178225050.0327000000000002
961.375040.01202301958744140.0319000000000000
971.361220.007657480003238630.0192999999999999
981.330540.01318836608530410.0349999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.35984 & 0.0189212314609806 & 0.0534000000000001 \tabularnewline
2 & 1.33196 & 0.0233542929672470 & 0.0599000000000001 \tabularnewline
3 & 1.30552 & 0.0161279880952337 & 0.036 \tabularnewline
4 & 1.3066 & 0.0180652982261572 & 0.0465 \tabularnewline
5 & 1.28144 & 0.00331104213201822 & 0.0088999999999999 \tabularnewline
6 & 1.29084 & 0.00902069842085406 & 0.0211999999999999 \tabularnewline
7 & 1.27046 & 0.00927970904716303 & 0.0226999999999999 \tabularnewline
8 & 1.27458 & 0.00876281918106265 & 0.0206999999999999 \tabularnewline
9 & 1.2593 & 0.00386716950753387 & 0.0088999999999999 \tabularnewline
10 & 1.27148 & 0.0099878426098933 & 0.0221 \tabularnewline
11 & 1.3138 & 0.0310674266716765 & 0.0766 \tabularnewline
12 & 1.3543 & 0.00448720402923693 & 0.0113000000000001 \tabularnewline
13 & 1.32868 & 0.00742408243488716 & 0.0199000000000000 \tabularnewline
14 & 1.3336 & 0.0117341382299682 & 0.0265000000000000 \tabularnewline
15 & 1.31338 & 0.0121992622727770 & 0.0309999999999999 \tabularnewline
16 & 1.30572 & 0.0125521711269406 & 0.03 \tabularnewline
17 & 1.32318 & 0.0149938987591620 & 0.0411000000000001 \tabularnewline
18 & 1.34734 & 0.0151249132228916 & 0.0361 \tabularnewline
19 & 1.3562 & 0.00565287537453291 & 0.0129000000000001 \tabularnewline
20 & 1.38702 & 0.0135691562007370 & 0.032 \tabularnewline
21 & 1.40626 & 0.0177194243698829 & 0.0382 \tabularnewline
22 & 1.40608 & 0.0145221210572010 & 0.0341 \tabularnewline
23 & 1.3963 & 0.00989141041510256 & 0.0251999999999999 \tabularnewline
24 & 1.39056 & 0.0056380847812001 & 0.0138000000000000 \tabularnewline
25 & 1.40514 & 0.0073768556987378 & 0.0194000000000001 \tabularnewline
26 & 1.4014 & 0.00736342311700206 & 0.0199000000000000 \tabularnewline
27 & 1.39516 & 0.00466240281400058 & 0.00900000000000012 \tabularnewline
28 & 1.41498 & 0.00662170672863117 & 0.0133999999999999 \tabularnewline
29 & 1.4229 & 0.00276043474836846 & 0.00780000000000003 \tabularnewline
30 & 1.41964 & 0.0140596230390433 & 0.0330999999999999 \tabularnewline
31 & 1.4301 & 0.0109320629343231 & 0.0244 \tabularnewline
32 & 1.4186 & 0.0104391091573946 & 0.0222 \tabularnewline
33 & 1.42664 & 0.0093478874618814 & 0.0218000000000000 \tabularnewline
34 & 1.42976 & 0.00417468561690572 & 0.00959999999999983 \tabularnewline
35 & 1.4324 & 0.00962003118498068 & 0.0253000000000001 \tabularnewline
36 & 1.45666 & 0.003608739392087 & 0.00890000000000013 \tabularnewline
37 & 1.47052 & 0.0047536301917587 & 0.0122 \tabularnewline
38 & 1.4684 & 0.00954384618484595 & 0.0233999999999999 \tabularnewline
39 & 1.46114 & 0.00775067738975116 & 0.0185000000000000 \tabularnewline
40 & 1.47672 & 0.00613326992720845 & 0.0169999999999999 \tabularnewline
41 & 1.49006 & 0.00446687810444837 & 0.0107000000000002 \tabularnewline
42 & 1.49668 & 0.00658915776104957 & 0.0145999999999999 \tabularnewline
43 & 1.47606 & 0.00582134005191243 & 0.0142 \tabularnewline
44 & 1.4888 & 0.00902025498530944 & 0.0223 \tabularnewline
45 & 1.49334 & 0.00699092268588348 & 0.0169000000000001 \tabularnewline
46 & 1.49144 & 0.00710478711855601 & 0.0153999999999999 \tabularnewline
47 & 1.50338 & 0.00688236877826234 & 0.0165000000000000 \tabularnewline
48 & 1.49678 & 0.0172035461460711 & 0.0346 \tabularnewline
49 & 1.46886 & 0.00951488307863005 & 0.0226999999999999 \tabularnewline
50 & 1.43774 & 0.0107155494492816 & 0.0281 \tabularnewline
51 & 1.437 & 0.00629245580040098 & 0.0157000000000000 \tabularnewline
52 & 1.43782 & 0.00530584583266422 & 0.0138000000000000 \tabularnewline
53 & 1.44662 & 0.0113056180724452 & 0.0289999999999999 \tabularnewline
54 & 1.42436 & 0.0140261541414601 & 0.0309999999999999 \tabularnewline
55 & 1.40884 & 0.00599232842891646 & 0.0152000000000001 \tabularnewline
56 & 1.39294 & 0.00534724227990468 & 0.0137000000000000 \tabularnewline
57 & 1.37168 & 0.00347087885124215 & 0.00849999999999995 \tabularnewline
58 & 1.36242 & 0.00657092078783486 & 0.0159000000000000 \tabularnewline
59 & 1.35516 & 0.00528753250581024 & 0.0137000000000000 \tabularnewline
60 & 1.35904 & 0.00613864805963008 & 0.0143000000000000 \tabularnewline
61 & 1.36136 & 0.00459380016979409 & 0.0105000000000002 \tabularnewline
62 & 1.37218 & 0.00422457098413551 & 0.0105000000000000 \tabularnewline
63 & 1.34464 & 0.00950278906426951 & 0.0209999999999999 \tabularnewline
64 & 1.34506 & 0.00548570870535435 & 0.0129000000000001 \tabularnewline
65 & 1.34002 & 0.0110581191890846 & 0.0289000000000001 \tabularnewline
66 & 1.35418 & 0.00692148827926481 & 0.0183 \tabularnewline
67 & 1.3366 & 0.00711125867902441 & 0.0175000000000001 \tabularnewline
68 & 1.32688 & 0.00326450608821605 & 0.00769999999999982 \tabularnewline
69 & 1.2891 & 0.0153539897095185 & 0.0362 \tabularnewline
70 & 1.25624 & 0.0145572318797221 & 0.0348999999999999 \tabularnewline
71 & 1.23778 & 0.00874425525702443 & 0.0226999999999999 \tabularnewline
72 & 1.22956 & 0.00613253618008079 & 0.0161 \tabularnewline
73 & 1.2132 & 0.0124030238248582 & 0.0308999999999999 \tabularnewline
74 & 1.20746 & 0.0118102921217047 & 0.0307000000000002 \tabularnewline
75 & 1.23322 & 0.00602967660824362 & 0.0133000000000001 \tabularnewline
76 & 1.22848 & 0.00333571581523367 & 0.0081 \tabularnewline
77 & 1.23752 & 0.0157018151816916 & 0.0349999999999999 \tabularnewline
78 & 1.2603 & 0.00425382181103065 & 0.00930000000000009 \tabularnewline
79 & 1.28114 & 0.0178572954279197 & 0.0431000000000001 \tabularnewline
80 & 1.28678 & 0.00455817946114452 & 0.0113999999999999 \tabularnewline
81 & 1.3039 & 0.00332490601370926 & 0.0081 \tabularnewline
82 & 1.3208 & 0.00308139578762607 & 0.00769999999999982 \tabularnewline
83 & 1.29116 & 0.0154736227173859 & 0.0343 \tabularnewline
84 & 1.27982 & 0.00842864164619667 & 0.0176000000000001 \tabularnewline
85 & 1.2666 & 0.00498196748283245 & 0.0102000000000000 \tabularnewline
86 & 1.28012 & 0.00730561427944293 & 0.0194000000000001 \tabularnewline
87 & 1.27364 & 0.00399098985215446 & 0.0104000000000000 \tabularnewline
88 & 1.30102 & 0.0096515283763765 & 0.0228000000000002 \tabularnewline
89 & 1.33392 & 0.0135291167487016 & 0.0356999999999998 \tabularnewline
90 & 1.363 & 0.0105387380648728 & 0.0266000000000000 \tabularnewline
91 & 1.38832 & 0.00738186968186249 & 0.0190000000000001 \tabularnewline
92 & 1.39754 & 0.0117861359231938 & 0.0267999999999999 \tabularnewline
93 & 1.39402 & 0.0081998170711303 & 0.0172000000000001 \tabularnewline
94 & 1.3871 & 0.00493001014197739 & 0.0123000000000000 \tabularnewline
95 & 1.40554 & 0.012109417822505 & 0.0327000000000002 \tabularnewline
96 & 1.37504 & 0.0120230195874414 & 0.0319000000000000 \tabularnewline
97 & 1.36122 & 0.00765748000323863 & 0.0192999999999999 \tabularnewline
98 & 1.33054 & 0.0131883660853041 & 0.0349999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110573&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]1.35984[/C][C]0.0189212314609806[/C][C]0.0534000000000001[/C][/ROW]
[ROW][C]2[/C][C]1.33196[/C][C]0.0233542929672470[/C][C]0.0599000000000001[/C][/ROW]
[ROW][C]3[/C][C]1.30552[/C][C]0.0161279880952337[/C][C]0.036[/C][/ROW]
[ROW][C]4[/C][C]1.3066[/C][C]0.0180652982261572[/C][C]0.0465[/C][/ROW]
[ROW][C]5[/C][C]1.28144[/C][C]0.00331104213201822[/C][C]0.0088999999999999[/C][/ROW]
[ROW][C]6[/C][C]1.29084[/C][C]0.00902069842085406[/C][C]0.0211999999999999[/C][/ROW]
[ROW][C]7[/C][C]1.27046[/C][C]0.00927970904716303[/C][C]0.0226999999999999[/C][/ROW]
[ROW][C]8[/C][C]1.27458[/C][C]0.00876281918106265[/C][C]0.0206999999999999[/C][/ROW]
[ROW][C]9[/C][C]1.2593[/C][C]0.00386716950753387[/C][C]0.0088999999999999[/C][/ROW]
[ROW][C]10[/C][C]1.27148[/C][C]0.0099878426098933[/C][C]0.0221[/C][/ROW]
[ROW][C]11[/C][C]1.3138[/C][C]0.0310674266716765[/C][C]0.0766[/C][/ROW]
[ROW][C]12[/C][C]1.3543[/C][C]0.00448720402923693[/C][C]0.0113000000000001[/C][/ROW]
[ROW][C]13[/C][C]1.32868[/C][C]0.00742408243488716[/C][C]0.0199000000000000[/C][/ROW]
[ROW][C]14[/C][C]1.3336[/C][C]0.0117341382299682[/C][C]0.0265000000000000[/C][/ROW]
[ROW][C]15[/C][C]1.31338[/C][C]0.0121992622727770[/C][C]0.0309999999999999[/C][/ROW]
[ROW][C]16[/C][C]1.30572[/C][C]0.0125521711269406[/C][C]0.03[/C][/ROW]
[ROW][C]17[/C][C]1.32318[/C][C]0.0149938987591620[/C][C]0.0411000000000001[/C][/ROW]
[ROW][C]18[/C][C]1.34734[/C][C]0.0151249132228916[/C][C]0.0361[/C][/ROW]
[ROW][C]19[/C][C]1.3562[/C][C]0.00565287537453291[/C][C]0.0129000000000001[/C][/ROW]
[ROW][C]20[/C][C]1.38702[/C][C]0.0135691562007370[/C][C]0.032[/C][/ROW]
[ROW][C]21[/C][C]1.40626[/C][C]0.0177194243698829[/C][C]0.0382[/C][/ROW]
[ROW][C]22[/C][C]1.40608[/C][C]0.0145221210572010[/C][C]0.0341[/C][/ROW]
[ROW][C]23[/C][C]1.3963[/C][C]0.00989141041510256[/C][C]0.0251999999999999[/C][/ROW]
[ROW][C]24[/C][C]1.39056[/C][C]0.0056380847812001[/C][C]0.0138000000000000[/C][/ROW]
[ROW][C]25[/C][C]1.40514[/C][C]0.0073768556987378[/C][C]0.0194000000000001[/C][/ROW]
[ROW][C]26[/C][C]1.4014[/C][C]0.00736342311700206[/C][C]0.0199000000000000[/C][/ROW]
[ROW][C]27[/C][C]1.39516[/C][C]0.00466240281400058[/C][C]0.00900000000000012[/C][/ROW]
[ROW][C]28[/C][C]1.41498[/C][C]0.00662170672863117[/C][C]0.0133999999999999[/C][/ROW]
[ROW][C]29[/C][C]1.4229[/C][C]0.00276043474836846[/C][C]0.00780000000000003[/C][/ROW]
[ROW][C]30[/C][C]1.41964[/C][C]0.0140596230390433[/C][C]0.0330999999999999[/C][/ROW]
[ROW][C]31[/C][C]1.4301[/C][C]0.0109320629343231[/C][C]0.0244[/C][/ROW]
[ROW][C]32[/C][C]1.4186[/C][C]0.0104391091573946[/C][C]0.0222[/C][/ROW]
[ROW][C]33[/C][C]1.42664[/C][C]0.0093478874618814[/C][C]0.0218000000000000[/C][/ROW]
[ROW][C]34[/C][C]1.42976[/C][C]0.00417468561690572[/C][C]0.00959999999999983[/C][/ROW]
[ROW][C]35[/C][C]1.4324[/C][C]0.00962003118498068[/C][C]0.0253000000000001[/C][/ROW]
[ROW][C]36[/C][C]1.45666[/C][C]0.003608739392087[/C][C]0.00890000000000013[/C][/ROW]
[ROW][C]37[/C][C]1.47052[/C][C]0.0047536301917587[/C][C]0.0122[/C][/ROW]
[ROW][C]38[/C][C]1.4684[/C][C]0.00954384618484595[/C][C]0.0233999999999999[/C][/ROW]
[ROW][C]39[/C][C]1.46114[/C][C]0.00775067738975116[/C][C]0.0185000000000000[/C][/ROW]
[ROW][C]40[/C][C]1.47672[/C][C]0.00613326992720845[/C][C]0.0169999999999999[/C][/ROW]
[ROW][C]41[/C][C]1.49006[/C][C]0.00446687810444837[/C][C]0.0107000000000002[/C][/ROW]
[ROW][C]42[/C][C]1.49668[/C][C]0.00658915776104957[/C][C]0.0145999999999999[/C][/ROW]
[ROW][C]43[/C][C]1.47606[/C][C]0.00582134005191243[/C][C]0.0142[/C][/ROW]
[ROW][C]44[/C][C]1.4888[/C][C]0.00902025498530944[/C][C]0.0223[/C][/ROW]
[ROW][C]45[/C][C]1.49334[/C][C]0.00699092268588348[/C][C]0.0169000000000001[/C][/ROW]
[ROW][C]46[/C][C]1.49144[/C][C]0.00710478711855601[/C][C]0.0153999999999999[/C][/ROW]
[ROW][C]47[/C][C]1.50338[/C][C]0.00688236877826234[/C][C]0.0165000000000000[/C][/ROW]
[ROW][C]48[/C][C]1.49678[/C][C]0.0172035461460711[/C][C]0.0346[/C][/ROW]
[ROW][C]49[/C][C]1.46886[/C][C]0.00951488307863005[/C][C]0.0226999999999999[/C][/ROW]
[ROW][C]50[/C][C]1.43774[/C][C]0.0107155494492816[/C][C]0.0281[/C][/ROW]
[ROW][C]51[/C][C]1.437[/C][C]0.00629245580040098[/C][C]0.0157000000000000[/C][/ROW]
[ROW][C]52[/C][C]1.43782[/C][C]0.00530584583266422[/C][C]0.0138000000000000[/C][/ROW]
[ROW][C]53[/C][C]1.44662[/C][C]0.0113056180724452[/C][C]0.0289999999999999[/C][/ROW]
[ROW][C]54[/C][C]1.42436[/C][C]0.0140261541414601[/C][C]0.0309999999999999[/C][/ROW]
[ROW][C]55[/C][C]1.40884[/C][C]0.00599232842891646[/C][C]0.0152000000000001[/C][/ROW]
[ROW][C]56[/C][C]1.39294[/C][C]0.00534724227990468[/C][C]0.0137000000000000[/C][/ROW]
[ROW][C]57[/C][C]1.37168[/C][C]0.00347087885124215[/C][C]0.00849999999999995[/C][/ROW]
[ROW][C]58[/C][C]1.36242[/C][C]0.00657092078783486[/C][C]0.0159000000000000[/C][/ROW]
[ROW][C]59[/C][C]1.35516[/C][C]0.00528753250581024[/C][C]0.0137000000000000[/C][/ROW]
[ROW][C]60[/C][C]1.35904[/C][C]0.00613864805963008[/C][C]0.0143000000000000[/C][/ROW]
[ROW][C]61[/C][C]1.36136[/C][C]0.00459380016979409[/C][C]0.0105000000000002[/C][/ROW]
[ROW][C]62[/C][C]1.37218[/C][C]0.00422457098413551[/C][C]0.0105000000000000[/C][/ROW]
[ROW][C]63[/C][C]1.34464[/C][C]0.00950278906426951[/C][C]0.0209999999999999[/C][/ROW]
[ROW][C]64[/C][C]1.34506[/C][C]0.00548570870535435[/C][C]0.0129000000000001[/C][/ROW]
[ROW][C]65[/C][C]1.34002[/C][C]0.0110581191890846[/C][C]0.0289000000000001[/C][/ROW]
[ROW][C]66[/C][C]1.35418[/C][C]0.00692148827926481[/C][C]0.0183[/C][/ROW]
[ROW][C]67[/C][C]1.3366[/C][C]0.00711125867902441[/C][C]0.0175000000000001[/C][/ROW]
[ROW][C]68[/C][C]1.32688[/C][C]0.00326450608821605[/C][C]0.00769999999999982[/C][/ROW]
[ROW][C]69[/C][C]1.2891[/C][C]0.0153539897095185[/C][C]0.0362[/C][/ROW]
[ROW][C]70[/C][C]1.25624[/C][C]0.0145572318797221[/C][C]0.0348999999999999[/C][/ROW]
[ROW][C]71[/C][C]1.23778[/C][C]0.00874425525702443[/C][C]0.0226999999999999[/C][/ROW]
[ROW][C]72[/C][C]1.22956[/C][C]0.00613253618008079[/C][C]0.0161[/C][/ROW]
[ROW][C]73[/C][C]1.2132[/C][C]0.0124030238248582[/C][C]0.0308999999999999[/C][/ROW]
[ROW][C]74[/C][C]1.20746[/C][C]0.0118102921217047[/C][C]0.0307000000000002[/C][/ROW]
[ROW][C]75[/C][C]1.23322[/C][C]0.00602967660824362[/C][C]0.0133000000000001[/C][/ROW]
[ROW][C]76[/C][C]1.22848[/C][C]0.00333571581523367[/C][C]0.0081[/C][/ROW]
[ROW][C]77[/C][C]1.23752[/C][C]0.0157018151816916[/C][C]0.0349999999999999[/C][/ROW]
[ROW][C]78[/C][C]1.2603[/C][C]0.00425382181103065[/C][C]0.00930000000000009[/C][/ROW]
[ROW][C]79[/C][C]1.28114[/C][C]0.0178572954279197[/C][C]0.0431000000000001[/C][/ROW]
[ROW][C]80[/C][C]1.28678[/C][C]0.00455817946114452[/C][C]0.0113999999999999[/C][/ROW]
[ROW][C]81[/C][C]1.3039[/C][C]0.00332490601370926[/C][C]0.0081[/C][/ROW]
[ROW][C]82[/C][C]1.3208[/C][C]0.00308139578762607[/C][C]0.00769999999999982[/C][/ROW]
[ROW][C]83[/C][C]1.29116[/C][C]0.0154736227173859[/C][C]0.0343[/C][/ROW]
[ROW][C]84[/C][C]1.27982[/C][C]0.00842864164619667[/C][C]0.0176000000000001[/C][/ROW]
[ROW][C]85[/C][C]1.2666[/C][C]0.00498196748283245[/C][C]0.0102000000000000[/C][/ROW]
[ROW][C]86[/C][C]1.28012[/C][C]0.00730561427944293[/C][C]0.0194000000000001[/C][/ROW]
[ROW][C]87[/C][C]1.27364[/C][C]0.00399098985215446[/C][C]0.0104000000000000[/C][/ROW]
[ROW][C]88[/C][C]1.30102[/C][C]0.0096515283763765[/C][C]0.0228000000000002[/C][/ROW]
[ROW][C]89[/C][C]1.33392[/C][C]0.0135291167487016[/C][C]0.0356999999999998[/C][/ROW]
[ROW][C]90[/C][C]1.363[/C][C]0.0105387380648728[/C][C]0.0266000000000000[/C][/ROW]
[ROW][C]91[/C][C]1.38832[/C][C]0.00738186968186249[/C][C]0.0190000000000001[/C][/ROW]
[ROW][C]92[/C][C]1.39754[/C][C]0.0117861359231938[/C][C]0.0267999999999999[/C][/ROW]
[ROW][C]93[/C][C]1.39402[/C][C]0.0081998170711303[/C][C]0.0172000000000001[/C][/ROW]
[ROW][C]94[/C][C]1.3871[/C][C]0.00493001014197739[/C][C]0.0123000000000000[/C][/ROW]
[ROW][C]95[/C][C]1.40554[/C][C]0.012109417822505[/C][C]0.0327000000000002[/C][/ROW]
[ROW][C]96[/C][C]1.37504[/C][C]0.0120230195874414[/C][C]0.0319000000000000[/C][/ROW]
[ROW][C]97[/C][C]1.36122[/C][C]0.00765748000323863[/C][C]0.0192999999999999[/C][/ROW]
[ROW][C]98[/C][C]1.33054[/C][C]0.0131883660853041[/C][C]0.0349999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110573&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.359840.01892123146098060.0534000000000001
21.331960.02335429296724700.0599000000000001
31.305520.01612798809523370.036
41.30660.01806529822615720.0465
51.281440.003311042132018220.0088999999999999
61.290840.009020698420854060.0211999999999999
71.270460.009279709047163030.0226999999999999
81.274580.008762819181062650.0206999999999999
91.25930.003867169507533870.0088999999999999
101.271480.00998784260989330.0221
111.31380.03106742667167650.0766
121.35430.004487204029236930.0113000000000001
131.328680.007424082434887160.0199000000000000
141.33360.01173413822996820.0265000000000000
151.313380.01219926227277700.0309999999999999
161.305720.01255217112694060.03
171.323180.01499389875916200.0411000000000001
181.347340.01512491322289160.0361
191.35620.005652875374532910.0129000000000001
201.387020.01356915620073700.032
211.406260.01771942436988290.0382
221.406080.01452212105720100.0341
231.39630.009891410415102560.0251999999999999
241.390560.00563808478120010.0138000000000000
251.405140.00737685569873780.0194000000000001
261.40140.007363423117002060.0199000000000000
271.395160.004662402814000580.00900000000000012
281.414980.006621706728631170.0133999999999999
291.42290.002760434748368460.00780000000000003
301.419640.01405962303904330.0330999999999999
311.43010.01093206293432310.0244
321.41860.01043910915739460.0222
331.426640.00934788746188140.0218000000000000
341.429760.004174685616905720.00959999999999983
351.43240.009620031184980680.0253000000000001
361.456660.0036087393920870.00890000000000013
371.470520.00475363019175870.0122
381.46840.009543846184845950.0233999999999999
391.461140.007750677389751160.0185000000000000
401.476720.006133269927208450.0169999999999999
411.490060.004466878104448370.0107000000000002
421.496680.006589157761049570.0145999999999999
431.476060.005821340051912430.0142
441.48880.009020254985309440.0223
451.493340.006990922685883480.0169000000000001
461.491440.007104787118556010.0153999999999999
471.503380.006882368778262340.0165000000000000
481.496780.01720354614607110.0346
491.468860.009514883078630050.0226999999999999
501.437740.01071554944928160.0281
511.4370.006292455800400980.0157000000000000
521.437820.005305845832664220.0138000000000000
531.446620.01130561807244520.0289999999999999
541.424360.01402615414146010.0309999999999999
551.408840.005992328428916460.0152000000000001
561.392940.005347242279904680.0137000000000000
571.371680.003470878851242150.00849999999999995
581.362420.006570920787834860.0159000000000000
591.355160.005287532505810240.0137000000000000
601.359040.006138648059630080.0143000000000000
611.361360.004593800169794090.0105000000000002
621.372180.004224570984135510.0105000000000000
631.344640.009502789064269510.0209999999999999
641.345060.005485708705354350.0129000000000001
651.340020.01105811918908460.0289000000000001
661.354180.006921488279264810.0183
671.33660.007111258679024410.0175000000000001
681.326880.003264506088216050.00769999999999982
691.28910.01535398970951850.0362
701.256240.01455723187972210.0348999999999999
711.237780.008744255257024430.0226999999999999
721.229560.006132536180080790.0161
731.21320.01240302382485820.0308999999999999
741.207460.01181029212170470.0307000000000002
751.233220.006029676608243620.0133000000000001
761.228480.003335715815233670.0081
771.237520.01570181518169160.0349999999999999
781.26030.004253821811030650.00930000000000009
791.281140.01785729542791970.0431000000000001
801.286780.004558179461144520.0113999999999999
811.30390.003324906013709260.0081
821.32080.003081395787626070.00769999999999982
831.291160.01547362271738590.0343
841.279820.008428641646196670.0176000000000001
851.26660.004981967482832450.0102000000000000
861.280120.007305614279442930.0194000000000001
871.273640.003990989852154460.0104000000000000
881.301020.00965152837637650.0228000000000002
891.333920.01352911674870160.0356999999999998
901.3630.01053873806487280.0266000000000000
911.388320.007381869681862490.0190000000000001
921.397540.01178613592319380.0267999999999999
931.394020.00819981707113030.0172000000000001
941.38710.004930010141977390.0123000000000000
951.405540.0121094178225050.0327000000000002
961.375040.01202301958744140.0319000000000000
971.361220.007657480003238630.0192999999999999
981.330540.01318836608530410.0349999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0199585030612476
beta-0.00790374240592255
S.D.0.00652274424505511
T-STAT-1.21172042149504
p-value0.228593503719

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0199585030612476 \tabularnewline
beta & -0.00790374240592255 \tabularnewline
S.D. & 0.00652274424505511 \tabularnewline
T-STAT & -1.21172042149504 \tabularnewline
p-value & 0.228593503719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110573&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0199585030612476[/C][/ROW]
[ROW][C]beta[/C][C]-0.00790374240592255[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00652274424505511[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.21172042149504[/C][/ROW]
[ROW][C]p-value[/C][C]0.228593503719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110573&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110573&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0199585030612476
beta-0.00790374240592255
S.D.0.00652274424505511
T-STAT-1.21172042149504
p-value0.228593503719






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.61550734181943
beta-0.667286454336136
S.D.0.938493281139817
T-STAT-0.71101889352442
p-value0.478796512237765
Lambda1.66728645433614

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.61550734181943 \tabularnewline
beta & -0.667286454336136 \tabularnewline
S.D. & 0.938493281139817 \tabularnewline
T-STAT & -0.71101889352442 \tabularnewline
p-value & 0.478796512237765 \tabularnewline
Lambda & 1.66728645433614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110573&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.61550734181943[/C][/ROW]
[ROW][C]beta[/C][C]-0.667286454336136[/C][/ROW]
[ROW][C]S.D.[/C][C]0.938493281139817[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.71101889352442[/C][/ROW]
[ROW][C]p-value[/C][C]0.478796512237765[/C][/ROW]
[ROW][C]Lambda[/C][C]1.66728645433614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110573&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110573&T=3

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.61550734181943
beta-0.667286454336136
S.D.0.938493281139817
T-STAT-0.71101889352442
p-value0.478796512237765
Lambda1.66728645433614


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
R code (references can be found in the software module):
par1 <- 5
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')