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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationSat, 18 Dec 2010 16:04:44 +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/18/t12926881368j7x7eisntsazte.htm/, Retrieved Tue, 30 Apr 2024 07:02:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112073, Retrieved Tue, 30 Apr 2024 07:02:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2010-12-18 15:46:30] [ed939ef6f97e5f2afb6796311d9e7a5f]
- RMPD    [Percentiles] [] [2010-12-18 16:04:44] [f9aa24c2294a5d3925c7278aa2e9a372] [Current]
-           [Percentiles] [Paper] [2010-12-18 16:35:27] [5ddc7dfb25e070b079c4c8fcccc4d42e]
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Dataseries X:
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730
14538




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112073&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112073&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112073&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.0210272.0810298.7106981069811233.26106989766.310698
0.0411951.4412000.6127381273813080.081150912246.411509
0.0613836.2413880.1145381453814523.381380714464.913807
0.0815265.215346155481554815563.36155481474015548
0.116131.616271.5169711697117078.11557216271.516271.5
0.1217332.3217338.8173821738217379.841732817371.217328
0.1417499.817521.5175371753717640.541753717397.517537
0.1617741.417755177891778917839.68177041773817789
0.1817974.0817980.2180041800418001.961797017993.817970
0.21807218089180891808918129.8180891808918089
0.2218180.0418190.6182051820518276.241815718171.418205
0.2418512.4418562.6186881868818671.281847918604.418479
0.2618723.2818730187301873018730187301873018730
0.2818884.9618968.4190281902819061.841902818789.619028
0.31927219426.5196841968419632.51916919426.519426.5
0.3219772.8819790.8197851978519801.241978519808.219785
0.3419938.3220013.8200362003620073.182003619836.220036
0.3620243.6420301.6203662036620346.682020520269.420366
0.3820413.8420419.8204182041820421.242041820422.220418
0.420479.220516205162051620516.8205162051620516
0.4220588.3220690.8207642076420729.842052020593.220764
0.4420985.7621279209952099521364.2209952142120995
0.4622147.8822397.8223972239722398.442239722404.222397
0.4822430.622469224852248522472.2224052242122485
0.52251822598.52251822598.522598.52251822598.522598.5
0.5222733.422763.6227592275922762.682275922777.422759
0.5423109.2423600.1236912369123527.382278222872.923691
0.5623852.8823991.2240902409023961.562384323941.824090
0.5824254.8824456.1243192431924382.982431924638.924319
0.624905.625100251002510025035.2247762510025100
0.6225326.4825407.7254472544725376.262531625355.325447
0.6425556.4425665.8255912559125613.442559125703.225591
0.6625799.1225829.3258262582625815.442577825855.725826
0.6825888.5226055.8261052610525967.242585925908.226105
0.72617726338.5261952619526223.72619526338.526195
0.7226515.1226588265512655126534.44264822669926551
0.7426751.8426825.1268352683526777.582673626745.926835
0.7627010.5627060.2270442704427046.162704427054.827071
0.7827119.8827351.3271652716527140.562716527599.727165
0.827834.628029280292802927883.2277862802928029
0.8228967.9629296.9290962909629113.222909629182.129383
0.8429427.2429479.6294622946229439.882946229488.429462
0.8629562.8829770.6297432974329596.062950629991.429743
0.8829996.9230092.6300193001930022.683001930037.430111
0.93043530887.53065130651304893065130887.530887.5
0.9231233.231524.4315143151431264.43112431555.631514
0.9431563.9231897.2315663156631573.363156631602.831934
0.9631948.0832002.8319563195631948.963195631987.232034
0.9832825.0435085.6345063450632874.483203435858.434506

\begin{tabular}{lllllllll}
\hline
Percentiles - Ungrouped Data \tabularnewline
p & Weighted Average at Xnp & Weighted Average at X(n+1)p & Empirical Distribution Function & Empirical Distribution Function - Averaging & Empirical Distribution Function - Interpolation & Closest Observation & True Basic - Statistics Graphics Toolkit & MS Excel (old versions) \tabularnewline
0.02 & 10272.08 & 10298.7 & 10698 & 10698 & 11233.26 & 10698 & 9766.3 & 10698 \tabularnewline
0.04 & 11951.44 & 12000.6 & 12738 & 12738 & 13080.08 & 11509 & 12246.4 & 11509 \tabularnewline
0.06 & 13836.24 & 13880.1 & 14538 & 14538 & 14523.38 & 13807 & 14464.9 & 13807 \tabularnewline
0.08 & 15265.2 & 15346 & 15548 & 15548 & 15563.36 & 15548 & 14740 & 15548 \tabularnewline
0.1 & 16131.6 & 16271.5 & 16971 & 16971 & 17078.1 & 15572 & 16271.5 & 16271.5 \tabularnewline
0.12 & 17332.32 & 17338.8 & 17382 & 17382 & 17379.84 & 17328 & 17371.2 & 17328 \tabularnewline
0.14 & 17499.8 & 17521.5 & 17537 & 17537 & 17640.54 & 17537 & 17397.5 & 17537 \tabularnewline
0.16 & 17741.4 & 17755 & 17789 & 17789 & 17839.68 & 17704 & 17738 & 17789 \tabularnewline
0.18 & 17974.08 & 17980.2 & 18004 & 18004 & 18001.96 & 17970 & 17993.8 & 17970 \tabularnewline
0.2 & 18072 & 18089 & 18089 & 18089 & 18129.8 & 18089 & 18089 & 18089 \tabularnewline
0.22 & 18180.04 & 18190.6 & 18205 & 18205 & 18276.24 & 18157 & 18171.4 & 18205 \tabularnewline
0.24 & 18512.44 & 18562.6 & 18688 & 18688 & 18671.28 & 18479 & 18604.4 & 18479 \tabularnewline
0.26 & 18723.28 & 18730 & 18730 & 18730 & 18730 & 18730 & 18730 & 18730 \tabularnewline
0.28 & 18884.96 & 18968.4 & 19028 & 19028 & 19061.84 & 19028 & 18789.6 & 19028 \tabularnewline
0.3 & 19272 & 19426.5 & 19684 & 19684 & 19632.5 & 19169 & 19426.5 & 19426.5 \tabularnewline
0.32 & 19772.88 & 19790.8 & 19785 & 19785 & 19801.24 & 19785 & 19808.2 & 19785 \tabularnewline
0.34 & 19938.32 & 20013.8 & 20036 & 20036 & 20073.18 & 20036 & 19836.2 & 20036 \tabularnewline
0.36 & 20243.64 & 20301.6 & 20366 & 20366 & 20346.68 & 20205 & 20269.4 & 20366 \tabularnewline
0.38 & 20413.84 & 20419.8 & 20418 & 20418 & 20421.24 & 20418 & 20422.2 & 20418 \tabularnewline
0.4 & 20479.2 & 20516 & 20516 & 20516 & 20516.8 & 20516 & 20516 & 20516 \tabularnewline
0.42 & 20588.32 & 20690.8 & 20764 & 20764 & 20729.84 & 20520 & 20593.2 & 20764 \tabularnewline
0.44 & 20985.76 & 21279 & 20995 & 20995 & 21364.2 & 20995 & 21421 & 20995 \tabularnewline
0.46 & 22147.88 & 22397.8 & 22397 & 22397 & 22398.44 & 22397 & 22404.2 & 22397 \tabularnewline
0.48 & 22430.6 & 22469 & 22485 & 22485 & 22472.2 & 22405 & 22421 & 22485 \tabularnewline
0.5 & 22518 & 22598.5 & 22518 & 22598.5 & 22598.5 & 22518 & 22598.5 & 22598.5 \tabularnewline
0.52 & 22733.4 & 22763.6 & 22759 & 22759 & 22762.68 & 22759 & 22777.4 & 22759 \tabularnewline
0.54 & 23109.24 & 23600.1 & 23691 & 23691 & 23527.38 & 22782 & 22872.9 & 23691 \tabularnewline
0.56 & 23852.88 & 23991.2 & 24090 & 24090 & 23961.56 & 23843 & 23941.8 & 24090 \tabularnewline
0.58 & 24254.88 & 24456.1 & 24319 & 24319 & 24382.98 & 24319 & 24638.9 & 24319 \tabularnewline
0.6 & 24905.6 & 25100 & 25100 & 25100 & 25035.2 & 24776 & 25100 & 25100 \tabularnewline
0.62 & 25326.48 & 25407.7 & 25447 & 25447 & 25376.26 & 25316 & 25355.3 & 25447 \tabularnewline
0.64 & 25556.44 & 25665.8 & 25591 & 25591 & 25613.44 & 25591 & 25703.2 & 25591 \tabularnewline
0.66 & 25799.12 & 25829.3 & 25826 & 25826 & 25815.44 & 25778 & 25855.7 & 25826 \tabularnewline
0.68 & 25888.52 & 26055.8 & 26105 & 26105 & 25967.24 & 25859 & 25908.2 & 26105 \tabularnewline
0.7 & 26177 & 26338.5 & 26195 & 26195 & 26223.7 & 26195 & 26338.5 & 26195 \tabularnewline
0.72 & 26515.12 & 26588 & 26551 & 26551 & 26534.44 & 26482 & 26699 & 26551 \tabularnewline
0.74 & 26751.84 & 26825.1 & 26835 & 26835 & 26777.58 & 26736 & 26745.9 & 26835 \tabularnewline
0.76 & 27010.56 & 27060.2 & 27044 & 27044 & 27046.16 & 27044 & 27054.8 & 27071 \tabularnewline
0.78 & 27119.88 & 27351.3 & 27165 & 27165 & 27140.56 & 27165 & 27599.7 & 27165 \tabularnewline
0.8 & 27834.6 & 28029 & 28029 & 28029 & 27883.2 & 27786 & 28029 & 28029 \tabularnewline
0.82 & 28967.96 & 29296.9 & 29096 & 29096 & 29113.22 & 29096 & 29182.1 & 29383 \tabularnewline
0.84 & 29427.24 & 29479.6 & 29462 & 29462 & 29439.88 & 29462 & 29488.4 & 29462 \tabularnewline
0.86 & 29562.88 & 29770.6 & 29743 & 29743 & 29596.06 & 29506 & 29991.4 & 29743 \tabularnewline
0.88 & 29996.92 & 30092.6 & 30019 & 30019 & 30022.68 & 30019 & 30037.4 & 30111 \tabularnewline
0.9 & 30435 & 30887.5 & 30651 & 30651 & 30489 & 30651 & 30887.5 & 30887.5 \tabularnewline
0.92 & 31233.2 & 31524.4 & 31514 & 31514 & 31264.4 & 31124 & 31555.6 & 31514 \tabularnewline
0.94 & 31563.92 & 31897.2 & 31566 & 31566 & 31573.36 & 31566 & 31602.8 & 31934 \tabularnewline
0.96 & 31948.08 & 32002.8 & 31956 & 31956 & 31948.96 & 31956 & 31987.2 & 32034 \tabularnewline
0.98 & 32825.04 & 35085.6 & 34506 & 34506 & 32874.48 & 32034 & 35858.4 & 34506 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112073&T=1

[TABLE]
[ROW][C]Percentiles - Ungrouped Data[/C][/ROW]
[ROW][C]p[/C][C]Weighted Average at Xnp[/C][C]Weighted Average at X(n+1)p[/C][C]Empirical Distribution Function[/C][C]Empirical Distribution Function - Averaging[/C][C]Empirical Distribution Function - Interpolation[/C][C]Closest Observation[/C][C]True Basic - Statistics Graphics Toolkit[/C][C]MS Excel (old versions)[/C][/ROW]
[ROW][C]0.02[/C][C]10272.08[/C][C]10298.7[/C][C]10698[/C][C]10698[/C][C]11233.26[/C][C]10698[/C][C]9766.3[/C][C]10698[/C][/ROW]
[ROW][C]0.04[/C][C]11951.44[/C][C]12000.6[/C][C]12738[/C][C]12738[/C][C]13080.08[/C][C]11509[/C][C]12246.4[/C][C]11509[/C][/ROW]
[ROW][C]0.06[/C][C]13836.24[/C][C]13880.1[/C][C]14538[/C][C]14538[/C][C]14523.38[/C][C]13807[/C][C]14464.9[/C][C]13807[/C][/ROW]
[ROW][C]0.08[/C][C]15265.2[/C][C]15346[/C][C]15548[/C][C]15548[/C][C]15563.36[/C][C]15548[/C][C]14740[/C][C]15548[/C][/ROW]
[ROW][C]0.1[/C][C]16131.6[/C][C]16271.5[/C][C]16971[/C][C]16971[/C][C]17078.1[/C][C]15572[/C][C]16271.5[/C][C]16271.5[/C][/ROW]
[ROW][C]0.12[/C][C]17332.32[/C][C]17338.8[/C][C]17382[/C][C]17382[/C][C]17379.84[/C][C]17328[/C][C]17371.2[/C][C]17328[/C][/ROW]
[ROW][C]0.14[/C][C]17499.8[/C][C]17521.5[/C][C]17537[/C][C]17537[/C][C]17640.54[/C][C]17537[/C][C]17397.5[/C][C]17537[/C][/ROW]
[ROW][C]0.16[/C][C]17741.4[/C][C]17755[/C][C]17789[/C][C]17789[/C][C]17839.68[/C][C]17704[/C][C]17738[/C][C]17789[/C][/ROW]
[ROW][C]0.18[/C][C]17974.08[/C][C]17980.2[/C][C]18004[/C][C]18004[/C][C]18001.96[/C][C]17970[/C][C]17993.8[/C][C]17970[/C][/ROW]
[ROW][C]0.2[/C][C]18072[/C][C]18089[/C][C]18089[/C][C]18089[/C][C]18129.8[/C][C]18089[/C][C]18089[/C][C]18089[/C][/ROW]
[ROW][C]0.22[/C][C]18180.04[/C][C]18190.6[/C][C]18205[/C][C]18205[/C][C]18276.24[/C][C]18157[/C][C]18171.4[/C][C]18205[/C][/ROW]
[ROW][C]0.24[/C][C]18512.44[/C][C]18562.6[/C][C]18688[/C][C]18688[/C][C]18671.28[/C][C]18479[/C][C]18604.4[/C][C]18479[/C][/ROW]
[ROW][C]0.26[/C][C]18723.28[/C][C]18730[/C][C]18730[/C][C]18730[/C][C]18730[/C][C]18730[/C][C]18730[/C][C]18730[/C][/ROW]
[ROW][C]0.28[/C][C]18884.96[/C][C]18968.4[/C][C]19028[/C][C]19028[/C][C]19061.84[/C][C]19028[/C][C]18789.6[/C][C]19028[/C][/ROW]
[ROW][C]0.3[/C][C]19272[/C][C]19426.5[/C][C]19684[/C][C]19684[/C][C]19632.5[/C][C]19169[/C][C]19426.5[/C][C]19426.5[/C][/ROW]
[ROW][C]0.32[/C][C]19772.88[/C][C]19790.8[/C][C]19785[/C][C]19785[/C][C]19801.24[/C][C]19785[/C][C]19808.2[/C][C]19785[/C][/ROW]
[ROW][C]0.34[/C][C]19938.32[/C][C]20013.8[/C][C]20036[/C][C]20036[/C][C]20073.18[/C][C]20036[/C][C]19836.2[/C][C]20036[/C][/ROW]
[ROW][C]0.36[/C][C]20243.64[/C][C]20301.6[/C][C]20366[/C][C]20366[/C][C]20346.68[/C][C]20205[/C][C]20269.4[/C][C]20366[/C][/ROW]
[ROW][C]0.38[/C][C]20413.84[/C][C]20419.8[/C][C]20418[/C][C]20418[/C][C]20421.24[/C][C]20418[/C][C]20422.2[/C][C]20418[/C][/ROW]
[ROW][C]0.4[/C][C]20479.2[/C][C]20516[/C][C]20516[/C][C]20516[/C][C]20516.8[/C][C]20516[/C][C]20516[/C][C]20516[/C][/ROW]
[ROW][C]0.42[/C][C]20588.32[/C][C]20690.8[/C][C]20764[/C][C]20764[/C][C]20729.84[/C][C]20520[/C][C]20593.2[/C][C]20764[/C][/ROW]
[ROW][C]0.44[/C][C]20985.76[/C][C]21279[/C][C]20995[/C][C]20995[/C][C]21364.2[/C][C]20995[/C][C]21421[/C][C]20995[/C][/ROW]
[ROW][C]0.46[/C][C]22147.88[/C][C]22397.8[/C][C]22397[/C][C]22397[/C][C]22398.44[/C][C]22397[/C][C]22404.2[/C][C]22397[/C][/ROW]
[ROW][C]0.48[/C][C]22430.6[/C][C]22469[/C][C]22485[/C][C]22485[/C][C]22472.2[/C][C]22405[/C][C]22421[/C][C]22485[/C][/ROW]
[ROW][C]0.5[/C][C]22518[/C][C]22598.5[/C][C]22518[/C][C]22598.5[/C][C]22598.5[/C][C]22518[/C][C]22598.5[/C][C]22598.5[/C][/ROW]
[ROW][C]0.52[/C][C]22733.4[/C][C]22763.6[/C][C]22759[/C][C]22759[/C][C]22762.68[/C][C]22759[/C][C]22777.4[/C][C]22759[/C][/ROW]
[ROW][C]0.54[/C][C]23109.24[/C][C]23600.1[/C][C]23691[/C][C]23691[/C][C]23527.38[/C][C]22782[/C][C]22872.9[/C][C]23691[/C][/ROW]
[ROW][C]0.56[/C][C]23852.88[/C][C]23991.2[/C][C]24090[/C][C]24090[/C][C]23961.56[/C][C]23843[/C][C]23941.8[/C][C]24090[/C][/ROW]
[ROW][C]0.58[/C][C]24254.88[/C][C]24456.1[/C][C]24319[/C][C]24319[/C][C]24382.98[/C][C]24319[/C][C]24638.9[/C][C]24319[/C][/ROW]
[ROW][C]0.6[/C][C]24905.6[/C][C]25100[/C][C]25100[/C][C]25100[/C][C]25035.2[/C][C]24776[/C][C]25100[/C][C]25100[/C][/ROW]
[ROW][C]0.62[/C][C]25326.48[/C][C]25407.7[/C][C]25447[/C][C]25447[/C][C]25376.26[/C][C]25316[/C][C]25355.3[/C][C]25447[/C][/ROW]
[ROW][C]0.64[/C][C]25556.44[/C][C]25665.8[/C][C]25591[/C][C]25591[/C][C]25613.44[/C][C]25591[/C][C]25703.2[/C][C]25591[/C][/ROW]
[ROW][C]0.66[/C][C]25799.12[/C][C]25829.3[/C][C]25826[/C][C]25826[/C][C]25815.44[/C][C]25778[/C][C]25855.7[/C][C]25826[/C][/ROW]
[ROW][C]0.68[/C][C]25888.52[/C][C]26055.8[/C][C]26105[/C][C]26105[/C][C]25967.24[/C][C]25859[/C][C]25908.2[/C][C]26105[/C][/ROW]
[ROW][C]0.7[/C][C]26177[/C][C]26338.5[/C][C]26195[/C][C]26195[/C][C]26223.7[/C][C]26195[/C][C]26338.5[/C][C]26195[/C][/ROW]
[ROW][C]0.72[/C][C]26515.12[/C][C]26588[/C][C]26551[/C][C]26551[/C][C]26534.44[/C][C]26482[/C][C]26699[/C][C]26551[/C][/ROW]
[ROW][C]0.74[/C][C]26751.84[/C][C]26825.1[/C][C]26835[/C][C]26835[/C][C]26777.58[/C][C]26736[/C][C]26745.9[/C][C]26835[/C][/ROW]
[ROW][C]0.76[/C][C]27010.56[/C][C]27060.2[/C][C]27044[/C][C]27044[/C][C]27046.16[/C][C]27044[/C][C]27054.8[/C][C]27071[/C][/ROW]
[ROW][C]0.78[/C][C]27119.88[/C][C]27351.3[/C][C]27165[/C][C]27165[/C][C]27140.56[/C][C]27165[/C][C]27599.7[/C][C]27165[/C][/ROW]
[ROW][C]0.8[/C][C]27834.6[/C][C]28029[/C][C]28029[/C][C]28029[/C][C]27883.2[/C][C]27786[/C][C]28029[/C][C]28029[/C][/ROW]
[ROW][C]0.82[/C][C]28967.96[/C][C]29296.9[/C][C]29096[/C][C]29096[/C][C]29113.22[/C][C]29096[/C][C]29182.1[/C][C]29383[/C][/ROW]
[ROW][C]0.84[/C][C]29427.24[/C][C]29479.6[/C][C]29462[/C][C]29462[/C][C]29439.88[/C][C]29462[/C][C]29488.4[/C][C]29462[/C][/ROW]
[ROW][C]0.86[/C][C]29562.88[/C][C]29770.6[/C][C]29743[/C][C]29743[/C][C]29596.06[/C][C]29506[/C][C]29991.4[/C][C]29743[/C][/ROW]
[ROW][C]0.88[/C][C]29996.92[/C][C]30092.6[/C][C]30019[/C][C]30019[/C][C]30022.68[/C][C]30019[/C][C]30037.4[/C][C]30111[/C][/ROW]
[ROW][C]0.9[/C][C]30435[/C][C]30887.5[/C][C]30651[/C][C]30651[/C][C]30489[/C][C]30651[/C][C]30887.5[/C][C]30887.5[/C][/ROW]
[ROW][C]0.92[/C][C]31233.2[/C][C]31524.4[/C][C]31514[/C][C]31514[/C][C]31264.4[/C][C]31124[/C][C]31555.6[/C][C]31514[/C][/ROW]
[ROW][C]0.94[/C][C]31563.92[/C][C]31897.2[/C][C]31566[/C][C]31566[/C][C]31573.36[/C][C]31566[/C][C]31602.8[/C][C]31934[/C][/ROW]
[ROW][C]0.96[/C][C]31948.08[/C][C]32002.8[/C][C]31956[/C][C]31956[/C][C]31948.96[/C][C]31956[/C][C]31987.2[/C][C]32034[/C][/ROW]
[ROW][C]0.98[/C][C]32825.04[/C][C]35085.6[/C][C]34506[/C][C]34506[/C][C]32874.48[/C][C]32034[/C][C]35858.4[/C][C]34506[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112073&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112073&T=1

As an alternative you can also use a QR Code:  

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

Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.0210272.0810298.7106981069811233.26106989766.310698
0.0411951.4412000.6127381273813080.081150912246.411509
0.0613836.2413880.1145381453814523.381380714464.913807
0.0815265.215346155481554815563.36155481474015548
0.116131.616271.5169711697117078.11557216271.516271.5
0.1217332.3217338.8173821738217379.841732817371.217328
0.1417499.817521.5175371753717640.541753717397.517537
0.1617741.417755177891778917839.68177041773817789
0.1817974.0817980.2180041800418001.961797017993.817970
0.21807218089180891808918129.8180891808918089
0.2218180.0418190.6182051820518276.241815718171.418205
0.2418512.4418562.6186881868818671.281847918604.418479
0.2618723.2818730187301873018730187301873018730
0.2818884.9618968.4190281902819061.841902818789.619028
0.31927219426.5196841968419632.51916919426.519426.5
0.3219772.8819790.8197851978519801.241978519808.219785
0.3419938.3220013.8200362003620073.182003619836.220036
0.3620243.6420301.6203662036620346.682020520269.420366
0.3820413.8420419.8204182041820421.242041820422.220418
0.420479.220516205162051620516.8205162051620516
0.4220588.3220690.8207642076420729.842052020593.220764
0.4420985.7621279209952099521364.2209952142120995
0.4622147.8822397.8223972239722398.442239722404.222397
0.4822430.622469224852248522472.2224052242122485
0.52251822598.52251822598.522598.52251822598.522598.5
0.5222733.422763.6227592275922762.682275922777.422759
0.5423109.2423600.1236912369123527.382278222872.923691
0.5623852.8823991.2240902409023961.562384323941.824090
0.5824254.8824456.1243192431924382.982431924638.924319
0.624905.625100251002510025035.2247762510025100
0.6225326.4825407.7254472544725376.262531625355.325447
0.6425556.4425665.8255912559125613.442559125703.225591
0.6625799.1225829.3258262582625815.442577825855.725826
0.6825888.5226055.8261052610525967.242585925908.226105
0.72617726338.5261952619526223.72619526338.526195
0.7226515.1226588265512655126534.44264822669926551
0.7426751.8426825.1268352683526777.582673626745.926835
0.7627010.5627060.2270442704427046.162704427054.827071
0.7827119.8827351.3271652716527140.562716527599.727165
0.827834.628029280292802927883.2277862802928029
0.8228967.9629296.9290962909629113.222909629182.129383
0.8429427.2429479.6294622946229439.882946229488.429462
0.8629562.8829770.6297432974329596.062950629991.429743
0.8829996.9230092.6300193001930022.683001930037.430111
0.93043530887.53065130651304893065130887.530887.5
0.9231233.231524.4315143151431264.43112431555.631514
0.9431563.9231897.2315663156631573.363156631602.831934
0.9631948.0832002.8319563195631948.963195631987.232034
0.9832825.0435085.6345063450632874.483203435858.434506



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
x <-sort(x[!is.na(x)])
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
lx <- length(x)
qval <- array(NA,dim=c(99,8))
mystep <- 25
mystart <- 25
if (lx>10){
mystep=10
mystart=10
}
if (lx>20){
mystep=5
mystart=5
}
if (lx>50){
mystep=2
mystart=2
}
if (lx>=100){
mystep=1
mystart=1
}
for (perc in seq(mystart,99,mystep)) {
qval[perc,1] <- q1(x,lx,perc/100,i,f)
qval[perc,2] <- q2(x,lx,perc/100,i,f)
qval[perc,3] <- q3(x,lx,perc/100,i,f)
qval[perc,4] <- q4(x,lx,perc/100,i,f)
qval[perc,5] <- q5(x,lx,perc/100,i,f)
qval[perc,6] <- q6(x,lx,perc/100,i,f)
qval[perc,7] <- q7(x,lx,perc/100,i,f)
qval[perc,8] <- q8(x,lx,perc/100,i,f)
}
bitmap(file='test1.png')
myqqnorm <- qqnorm(x,col=2)
qqline(x)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Percentiles - Ungrouped Data',9,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p',1,TRUE)
a<-table.element(a,hyperlink('method_1.htm', 'Weighted Average at Xnp',''),1,TRUE)
a<-table.element(a,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE)
a<-table.element(a,hyperlink('method_3.htm','Empirical Distribution Function',''),1,TRUE)
a<-table.element(a,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE)
a<-table.element(a,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE)
a<-table.element(a,hyperlink('method_6.htm','Closest Observation',''),1,TRUE)
a<-table.element(a,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE)
a<-table.element(a,hyperlink('method_8.htm','MS Excel (old versions)',''),1,TRUE)
a<-table.row.end(a)
for (perc in seq(mystart,99,mystep)) {
a<-table.row.start(a)
a<-table.element(a,round(perc/100,2),1,TRUE)
for (j in 1:8) {
a<-table.element(a,round(qval[perc,j],6))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')