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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 20 Dec 2011 10:29:15 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/20/t1324394972oe6ton2rq7sricj.htm/, Retrieved Mon, 06 May 2024 05:40:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157996, Retrieved Mon, 06 May 2024 05:40:23 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

119

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [(Partial) Autocorrelation Function] [] [2011-12-05 11:42:22] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RMPD  [Variance Reduction Matrix] [Variance Reductio...] [2011-12-20 13:59:28] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RMP     [Standard Deviation-Mean Plot] [] [2011-12-20 14:38:17] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RM        [ARIMA Backward Selection] [] [2011-12-20 14:48:06] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RM D        [(Partial) Autocorrelation Function] [] [2011-12-20 15:23:33] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RM            [Spectral Analysis] [] [2011-12-20 15:26:09] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RM              [Variance Reduction Matrix] [] [2011-12-20 15:27:08] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RM                  [Standard Deviation-Mean Plot] [] [2011-12-20 15:29:15] [3627de22d386f4cb93d383ef7c1ade7f] [Current]
- R                     [Standard Deviation-Mean Plot] [Standard Deviatio...] [2011-12-20 15:29:48] [aba4febe8a2e49e81bdc61a6c01f5c21] 

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157996&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157996&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157996&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	554.75	295.299142114117	670
2	521	697.450117690625	1453
3	548.25	136.394953474582	285
4	593	196.203975494892	420
5	824.5	452.360107289167	1051
6	641.75	236.791575019045	565
7	767.25	247.541747320864	556
8	577	102.228502222554	214
9	604	300.746848140869	728
10	515.75	426.084792030882	867
11	549.25	277.058808438449	667
12	812	352.362502734518	737
13	807	616.137971561565	1305
14	731.75	320.41886648573	726
15	422.75	249.993833257276	546
16	773.75	390.082363097846	897
17	838.75	169.068772988982	406
18	748.25	185.672426601259	418
19	563.25	165.737493243583	335
20	520.25	120.563607002003	272
21	666.75	149.858544412167	338
22	484.25	51.7646919563261	107
23	634.75	259.057747744912	563
24	605	425.272461683879	914
25	695	163.366663266	393
26	663	216.371593945847	433
27	593	246.549521732788	574
28	744.5	287.975114665602	686
29	570.5	279.588387932451	683
30	580	242.317972919881	546
31	515.75	128.704765516537	292
32	349	92.7397793110738	220
33	390.75	232.345109696761	449
34	548.75	332.962835763993	783
35	308.75	265.135657101542	559
36	530.5	303.633002158856	690
37	440.25	70.6700077826513	168
38	500.25	235.497169126651	546
39	859.75	349.147891301093	789
40	466.5	169.883293273157	369
41	873	542.648443592473	1046
42	527.75	82.5444324793219	164
43	703	478.41753033656	1137
44	650.25	126.088262736862	280
45	556.25	236.261684014428	542
46	396.5	214.349403233754	479
47	306.5	356.148377318593	755
48	417.75	126.241501364118	296
49	416.5	90.6476695784288	210
50	352	150.459296821433	330
51	302	161.276160668587	351
52	406.25	213.824499687633	436
53	398.25	46.1401849440015	106
54	255.5	89.563757551069	203
55	263.75	90.8675776427801	196
56	384.5	187.709882531528	451
57	306.5	203.60173542155	488
58	308.25	100.260909630823	237
59	309.75	149.742835109619	339
60	306	118.476439289281	239
61	270.75	92.4098659956465	186
62	348.5	113.350488897637	252
63	349	128.90565025113	298
64	277.25	186.548251130907	400
65	183.5	82.2374610503024	193
66	179.75	30.2365672654817	66
67	243.5	32.705758922041	73
68	307.5	92.8601098427091	198
69	288.5	72.3579067322063	164
70	213	124.654188323805	286
71	308	109.444049632678	267
72	203.25	38.1171439993432	73

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 554.75 & 295.299142114117 & 670 \tabularnewline
2 & 521 & 697.450117690625 & 1453 \tabularnewline
3 & 548.25 & 136.394953474582 & 285 \tabularnewline
4 & 593 & 196.203975494892 & 420 \tabularnewline
5 & 824.5 & 452.360107289167 & 1051 \tabularnewline
6 & 641.75 & 236.791575019045 & 565 \tabularnewline
7 & 767.25 & 247.541747320864 & 556 \tabularnewline
8 & 577 & 102.228502222554 & 214 \tabularnewline
9 & 604 & 300.746848140869 & 728 \tabularnewline
10 & 515.75 & 426.084792030882 & 867 \tabularnewline
11 & 549.25 & 277.058808438449 & 667 \tabularnewline
12 & 812 & 352.362502734518 & 737 \tabularnewline
13 & 807 & 616.137971561565 & 1305 \tabularnewline
14 & 731.75 & 320.41886648573 & 726 \tabularnewline
15 & 422.75 & 249.993833257276 & 546 \tabularnewline
16 & 773.75 & 390.082363097846 & 897 \tabularnewline
17 & 838.75 & 169.068772988982 & 406 \tabularnewline
18 & 748.25 & 185.672426601259 & 418 \tabularnewline
19 & 563.25 & 165.737493243583 & 335 \tabularnewline
20 & 520.25 & 120.563607002003 & 272 \tabularnewline
21 & 666.75 & 149.858544412167 & 338 \tabularnewline
22 & 484.25 & 51.7646919563261 & 107 \tabularnewline
23 & 634.75 & 259.057747744912 & 563 \tabularnewline
24 & 605 & 425.272461683879 & 914 \tabularnewline
25 & 695 & 163.366663266 & 393 \tabularnewline
26 & 663 & 216.371593945847 & 433 \tabularnewline
27 & 593 & 246.549521732788 & 574 \tabularnewline
28 & 744.5 & 287.975114665602 & 686 \tabularnewline
29 & 570.5 & 279.588387932451 & 683 \tabularnewline
30 & 580 & 242.317972919881 & 546 \tabularnewline
31 & 515.75 & 128.704765516537 & 292 \tabularnewline
32 & 349 & 92.7397793110738 & 220 \tabularnewline
33 & 390.75 & 232.345109696761 & 449 \tabularnewline
34 & 548.75 & 332.962835763993 & 783 \tabularnewline
35 & 308.75 & 265.135657101542 & 559 \tabularnewline
36 & 530.5 & 303.633002158856 & 690 \tabularnewline
37 & 440.25 & 70.6700077826513 & 168 \tabularnewline
38 & 500.25 & 235.497169126651 & 546 \tabularnewline
39 & 859.75 & 349.147891301093 & 789 \tabularnewline
40 & 466.5 & 169.883293273157 & 369 \tabularnewline
41 & 873 & 542.648443592473 & 1046 \tabularnewline
42 & 527.75 & 82.5444324793219 & 164 \tabularnewline
43 & 703 & 478.41753033656 & 1137 \tabularnewline
44 & 650.25 & 126.088262736862 & 280 \tabularnewline
45 & 556.25 & 236.261684014428 & 542 \tabularnewline
46 & 396.5 & 214.349403233754 & 479 \tabularnewline
47 & 306.5 & 356.148377318593 & 755 \tabularnewline
48 & 417.75 & 126.241501364118 & 296 \tabularnewline
49 & 416.5 & 90.6476695784288 & 210 \tabularnewline
50 & 352 & 150.459296821433 & 330 \tabularnewline
51 & 302 & 161.276160668587 & 351 \tabularnewline
52 & 406.25 & 213.824499687633 & 436 \tabularnewline
53 & 398.25 & 46.1401849440015 & 106 \tabularnewline
54 & 255.5 & 89.563757551069 & 203 \tabularnewline
55 & 263.75 & 90.8675776427801 & 196 \tabularnewline
56 & 384.5 & 187.709882531528 & 451 \tabularnewline
57 & 306.5 & 203.60173542155 & 488 \tabularnewline
58 & 308.25 & 100.260909630823 & 237 \tabularnewline
59 & 309.75 & 149.742835109619 & 339 \tabularnewline
60 & 306 & 118.476439289281 & 239 \tabularnewline
61 & 270.75 & 92.4098659956465 & 186 \tabularnewline
62 & 348.5 & 113.350488897637 & 252 \tabularnewline
63 & 349 & 128.90565025113 & 298 \tabularnewline
64 & 277.25 & 186.548251130907 & 400 \tabularnewline
65 & 183.5 & 82.2374610503024 & 193 \tabularnewline
66 & 179.75 & 30.2365672654817 & 66 \tabularnewline
67 & 243.5 & 32.705758922041 & 73 \tabularnewline
68 & 307.5 & 92.8601098427091 & 198 \tabularnewline
69 & 288.5 & 72.3579067322063 & 164 \tabularnewline
70 & 213 & 124.654188323805 & 286 \tabularnewline
71 & 308 & 109.444049632678 & 267 \tabularnewline
72 & 203.25 & 38.1171439993432 & 73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157996&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]554.75[/C][C]295.299142114117[/C][C]670[/C][/ROW]
[ROW][C]2[/C][C]521[/C][C]697.450117690625[/C][C]1453[/C][/ROW]
[ROW][C]3[/C][C]548.25[/C][C]136.394953474582[/C][C]285[/C][/ROW]
[ROW][C]4[/C][C]593[/C][C]196.203975494892[/C][C]420[/C][/ROW]
[ROW][C]5[/C][C]824.5[/C][C]452.360107289167[/C][C]1051[/C][/ROW]
[ROW][C]6[/C][C]641.75[/C][C]236.791575019045[/C][C]565[/C][/ROW]
[ROW][C]7[/C][C]767.25[/C][C]247.541747320864[/C][C]556[/C][/ROW]
[ROW][C]8[/C][C]577[/C][C]102.228502222554[/C][C]214[/C][/ROW]
[ROW][C]9[/C][C]604[/C][C]300.746848140869[/C][C]728[/C][/ROW]
[ROW][C]10[/C][C]515.75[/C][C]426.084792030882[/C][C]867[/C][/ROW]
[ROW][C]11[/C][C]549.25[/C][C]277.058808438449[/C][C]667[/C][/ROW]
[ROW][C]12[/C][C]812[/C][C]352.362502734518[/C][C]737[/C][/ROW]
[ROW][C]13[/C][C]807[/C][C]616.137971561565[/C][C]1305[/C][/ROW]
[ROW][C]14[/C][C]731.75[/C][C]320.41886648573[/C][C]726[/C][/ROW]
[ROW][C]15[/C][C]422.75[/C][C]249.993833257276[/C][C]546[/C][/ROW]
[ROW][C]16[/C][C]773.75[/C][C]390.082363097846[/C][C]897[/C][/ROW]
[ROW][C]17[/C][C]838.75[/C][C]169.068772988982[/C][C]406[/C][/ROW]
[ROW][C]18[/C][C]748.25[/C][C]185.672426601259[/C][C]418[/C][/ROW]
[ROW][C]19[/C][C]563.25[/C][C]165.737493243583[/C][C]335[/C][/ROW]
[ROW][C]20[/C][C]520.25[/C][C]120.563607002003[/C][C]272[/C][/ROW]
[ROW][C]21[/C][C]666.75[/C][C]149.858544412167[/C][C]338[/C][/ROW]
[ROW][C]22[/C][C]484.25[/C][C]51.7646919563261[/C][C]107[/C][/ROW]
[ROW][C]23[/C][C]634.75[/C][C]259.057747744912[/C][C]563[/C][/ROW]
[ROW][C]24[/C][C]605[/C][C]425.272461683879[/C][C]914[/C][/ROW]
[ROW][C]25[/C][C]695[/C][C]163.366663266[/C][C]393[/C][/ROW]
[ROW][C]26[/C][C]663[/C][C]216.371593945847[/C][C]433[/C][/ROW]
[ROW][C]27[/C][C]593[/C][C]246.549521732788[/C][C]574[/C][/ROW]
[ROW][C]28[/C][C]744.5[/C][C]287.975114665602[/C][C]686[/C][/ROW]
[ROW][C]29[/C][C]570.5[/C][C]279.588387932451[/C][C]683[/C][/ROW]
[ROW][C]30[/C][C]580[/C][C]242.317972919881[/C][C]546[/C][/ROW]
[ROW][C]31[/C][C]515.75[/C][C]128.704765516537[/C][C]292[/C][/ROW]
[ROW][C]32[/C][C]349[/C][C]92.7397793110738[/C][C]220[/C][/ROW]
[ROW][C]33[/C][C]390.75[/C][C]232.345109696761[/C][C]449[/C][/ROW]
[ROW][C]34[/C][C]548.75[/C][C]332.962835763993[/C][C]783[/C][/ROW]
[ROW][C]35[/C][C]308.75[/C][C]265.135657101542[/C][C]559[/C][/ROW]
[ROW][C]36[/C][C]530.5[/C][C]303.633002158856[/C][C]690[/C][/ROW]
[ROW][C]37[/C][C]440.25[/C][C]70.6700077826513[/C][C]168[/C][/ROW]
[ROW][C]38[/C][C]500.25[/C][C]235.497169126651[/C][C]546[/C][/ROW]
[ROW][C]39[/C][C]859.75[/C][C]349.147891301093[/C][C]789[/C][/ROW]
[ROW][C]40[/C][C]466.5[/C][C]169.883293273157[/C][C]369[/C][/ROW]
[ROW][C]41[/C][C]873[/C][C]542.648443592473[/C][C]1046[/C][/ROW]
[ROW][C]42[/C][C]527.75[/C][C]82.5444324793219[/C][C]164[/C][/ROW]
[ROW][C]43[/C][C]703[/C][C]478.41753033656[/C][C]1137[/C][/ROW]
[ROW][C]44[/C][C]650.25[/C][C]126.088262736862[/C][C]280[/C][/ROW]
[ROW][C]45[/C][C]556.25[/C][C]236.261684014428[/C][C]542[/C][/ROW]
[ROW][C]46[/C][C]396.5[/C][C]214.349403233754[/C][C]479[/C][/ROW]
[ROW][C]47[/C][C]306.5[/C][C]356.148377318593[/C][C]755[/C][/ROW]
[ROW][C]48[/C][C]417.75[/C][C]126.241501364118[/C][C]296[/C][/ROW]
[ROW][C]49[/C][C]416.5[/C][C]90.6476695784288[/C][C]210[/C][/ROW]
[ROW][C]50[/C][C]352[/C][C]150.459296821433[/C][C]330[/C][/ROW]
[ROW][C]51[/C][C]302[/C][C]161.276160668587[/C][C]351[/C][/ROW]
[ROW][C]52[/C][C]406.25[/C][C]213.824499687633[/C][C]436[/C][/ROW]
[ROW][C]53[/C][C]398.25[/C][C]46.1401849440015[/C][C]106[/C][/ROW]
[ROW][C]54[/C][C]255.5[/C][C]89.563757551069[/C][C]203[/C][/ROW]
[ROW][C]55[/C][C]263.75[/C][C]90.8675776427801[/C][C]196[/C][/ROW]
[ROW][C]56[/C][C]384.5[/C][C]187.709882531528[/C][C]451[/C][/ROW]
[ROW][C]57[/C][C]306.5[/C][C]203.60173542155[/C][C]488[/C][/ROW]
[ROW][C]58[/C][C]308.25[/C][C]100.260909630823[/C][C]237[/C][/ROW]
[ROW][C]59[/C][C]309.75[/C][C]149.742835109619[/C][C]339[/C][/ROW]
[ROW][C]60[/C][C]306[/C][C]118.476439289281[/C][C]239[/C][/ROW]
[ROW][C]61[/C][C]270.75[/C][C]92.4098659956465[/C][C]186[/C][/ROW]
[ROW][C]62[/C][C]348.5[/C][C]113.350488897637[/C][C]252[/C][/ROW]
[ROW][C]63[/C][C]349[/C][C]128.90565025113[/C][C]298[/C][/ROW]
[ROW][C]64[/C][C]277.25[/C][C]186.548251130907[/C][C]400[/C][/ROW]
[ROW][C]65[/C][C]183.5[/C][C]82.2374610503024[/C][C]193[/C][/ROW]
[ROW][C]66[/C][C]179.75[/C][C]30.2365672654817[/C][C]66[/C][/ROW]
[ROW][C]67[/C][C]243.5[/C][C]32.705758922041[/C][C]73[/C][/ROW]
[ROW][C]68[/C][C]307.5[/C][C]92.8601098427091[/C][C]198[/C][/ROW]
[ROW][C]69[/C][C]288.5[/C][C]72.3579067322063[/C][C]164[/C][/ROW]
[ROW][C]70[/C][C]213[/C][C]124.654188323805[/C][C]286[/C][/ROW]
[ROW][C]71[/C][C]308[/C][C]109.444049632678[/C][C]267[/C][/ROW]
[ROW][C]72[/C][C]203.25[/C][C]38.1171439993432[/C][C]73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157996&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157996&T=1

As an alternative you can also use a QR Code:

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

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	554.75	295.299142114117	670
2	521	697.450117690625	1453
3	548.25	136.394953474582	285
4	593	196.203975494892	420
5	824.5	452.360107289167	1051
6	641.75	236.791575019045	565
7	767.25	247.541747320864	556
8	577	102.228502222554	214
9	604	300.746848140869	728
10	515.75	426.084792030882	867
11	549.25	277.058808438449	667
12	812	352.362502734518	737
13	807	616.137971561565	1305
14	731.75	320.41886648573	726
15	422.75	249.993833257276	546
16	773.75	390.082363097846	897
17	838.75	169.068772988982	406
18	748.25	185.672426601259	418
19	563.25	165.737493243583	335
20	520.25	120.563607002003	272
21	666.75	149.858544412167	338
22	484.25	51.7646919563261	107
23	634.75	259.057747744912	563
24	605	425.272461683879	914
25	695	163.366663266	393
26	663	216.371593945847	433
27	593	246.549521732788	574
28	744.5	287.975114665602	686
29	570.5	279.588387932451	683
30	580	242.317972919881	546
31	515.75	128.704765516537	292
32	349	92.7397793110738	220
33	390.75	232.345109696761	449
34	548.75	332.962835763993	783
35	308.75	265.135657101542	559
36	530.5	303.633002158856	690
37	440.25	70.6700077826513	168
38	500.25	235.497169126651	546
39	859.75	349.147891301093	789
40	466.5	169.883293273157	369
41	873	542.648443592473	1046
42	527.75	82.5444324793219	164
43	703	478.41753033656	1137
44	650.25	126.088262736862	280
45	556.25	236.261684014428	542
46	396.5	214.349403233754	479
47	306.5	356.148377318593	755
48	417.75	126.241501364118	296
49	416.5	90.6476695784288	210
50	352	150.459296821433	330
51	302	161.276160668587	351
52	406.25	213.824499687633	436
53	398.25	46.1401849440015	106
54	255.5	89.563757551069	203
55	263.75	90.8675776427801	196
56	384.5	187.709882531528	451
57	306.5	203.60173542155	488
58	308.25	100.260909630823	237
59	309.75	149.742835109619	339
60	306	118.476439289281	239
61	270.75	92.4098659956465	186
62	348.5	113.350488897637	252
63	349	128.90565025113	298
64	277.25	186.548251130907	400
65	183.5	82.2374610503024	193
66	179.75	30.2365672654817	66
67	243.5	32.705758922041	73
68	307.5	92.8601098427091	198
69	288.5	72.3579067322063	164
70	213	124.654188323805	286
71	308	109.444049632678	267
72	203.25	38.1171439993432	73

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-5.42306605553759
beta	0.440113230910367
S.D.	0.0701055395852634
T-STAT	6.27786667806892
p-value	2.51555780672337e-08

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5.42306605553759 \tabularnewline
beta & 0.440113230910367 \tabularnewline
S.D. & 0.0701055395852634 \tabularnewline
T-STAT & 6.27786667806892 \tabularnewline
p-value & 2.51555780672337e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157996&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.42306605553759[/C][/ROW]
[ROW][C]beta[/C][C]0.440113230910367[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0701055395852634[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.27786667806892[/C][/ROW]
[ROW][C]p-value[/C][C]2.51555780672337e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157996&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157996&T=2

As an alternative you can also use a QR Code:

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-5.42306605553759
beta	0.440113230910367
S.D.	0.0701055395852634
T-STAT	6.27786667806892
p-value	2.51555780672337e-08

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.54136596188352
beta	1.09217562752926
S.D.	0.150561537159701
T-STAT	7.2540148575316
p-value	4.29087035222405e-10
Lambda	-0.092175627529264

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.54136596188352 \tabularnewline
beta & 1.09217562752926 \tabularnewline
S.D. & 0.150561537159701 \tabularnewline
T-STAT & 7.2540148575316 \tabularnewline
p-value & 4.29087035222405e-10 \tabularnewline
Lambda & -0.092175627529264 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157996&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.54136596188352[/C][/ROW]
[ROW][C]beta[/C][C]1.09217562752926[/C][/ROW]
[ROW][C]S.D.[/C][C]0.150561537159701[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.2540148575316[/C][/ROW]
[ROW][C]p-value[/C][C]4.29087035222405e-10[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.092175627529264[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157996&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157996&T=3

As an alternative you can also use a QR Code:

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.54136596188352
beta	1.09217562752926
S.D.	0.150561537159701
T-STAT	7.2540148575316
p-value	4.29087035222405e-10
Lambda	-0.092175627529264

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
(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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code