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Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationWed, 21 Nov 2012 12:16:43 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/21/t13535186965de2e48a5qztblu.htm/, Retrieved Sun, 28 Apr 2024 13:36:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=191491, Retrieved Sun, 28 Apr 2024 13:36:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-19 12:03:37] [74be16979710d4c4e7c6647856088456]
- RM D  [Percentiles] [] [2010-11-16 19:22:04] [b98453cac15ba1066b407e146608df68]
- R  D      [Percentiles] [normal QQ plot] [2012-11-21 17:16:43] [18a55f974a2e8651a7d8da0218fcbdb6] [Current]
- RM          [Mean versus Median] [gem mediaan] [2012-12-09 18:03:23] [93b3e8d0ee7e4ccb504c2c04707a9358]
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Dataseries X:
12584
9441
18960
21480
10766
13059
8589
4965
4803
7240
10906
8561
6389
14372
18149
6309
13051
12754
10860
9574
19110
29585
21122
14522
17330
18119
10902
29158
16065
10376
10999
17950
15418
12618
16561
8022
9567
9045
8172
13708
11259
10518
9301
5197
11259
10518
9301
5197
6758
7304
7628
14265
13054
15336
14682
27804
16022
24009
32613
19111




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191491&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191491&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191491&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







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)
0.024835.44838.64496549655006.7648034929.364803
0.045057.85067.0851975197519749655094.924965
0.0651975197519751975797.48519751975197
0.086086.66175.56630963096366.663095330.446309
0.163896425.963896573.56721.163896721.16389
0.126854.46912.24724072407245.1267587085.766758
0.147265.67274.56730473047388.2472407269.447304
0.167498.47550.24762876287801.3676287381.767628
0.187943.28014.1280228022811580227635.888022
0.281728249.881728366.58483.281728483.28172
0.228566.68572.76858985898588.4485618577.248561
0.248771.48880.84904590459085.9685898753.169045
0.269198.69265.1693019301930193019080.849301
0.2893019312.2930193019373.893019429.89301
0.394419478.8944195049529.294419529.29441
0.329568.49570.64957495749573.1695679570.369574
0.349894.810167.48103761037610384.5295749782.5210376
0.3610461.210512.321051810518105181051810381.6810518
0.381051810562.64105181051810622.161051810721.3610518
0.41076610803.6107661081310822.41076610822.410766
0.4210868.410886.04109021090210892.761086010875.9610902
0.4410903.610905.36109061090610905.841090210902.6410906
0.4610961.811014.6109991099911035.41099911243.410999
0.481120711259112591125911259112591125911259
0.51125911921.51125911921.511921.51125911921.511921.5
0.5212590.812608.48126181261812607.121258412593.5212618
0.5412672.412745.84127541275412734.961261812626.1612754
0.5612932.213051.48130511305113051.121305113053.5213051
0.5813053.413055.9130541305413055.11305413057.113054
0.61305913448.41305913383.513318.61305913318.613708
0.6213819.414164.74142651426514031.061370813808.2614265
0.6414307.814378143721437214346.32142651451614372
0.661446214563.61452214522145131452214640.414522
0.681465014995.92146821468214760.481468215022.0814682
0.71533615393.4153361537715360.61533615360.615418
0.7215538.815973.68160221602215707.921541815466.3216022
0.7416039.216134.44160651606516050.381602216491.5616065
0.7616362.616837.84165611656116481.641656117053.1616561
0.7817176.217689.6173301733017342.41733017590.417950
0.81795018085.21795018034.517983.81795017983.818119
0.821812518165.22181491814918130.41811918943.7818149
0.8418473.418996189601896018603.16181491907418960
0.861905019110.461911019110190711911019110.5419110
0.8819110.820478.48191111911119110.921911119754.5221122
0.92112221444.2211222130121157.82112221157.821480
0.9221985.824464.4240092400922188.122148027348.624009
0.942552728264.36278042780425754.72400928697.6427804
0.9628616.429397.12291582915828670.562915829345.8829585
0.9829499.631946.84295852958529508.142958530251.1632613

\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 & 4835.4 & 4838.64 & 4965 & 4965 & 5006.76 & 4803 & 4929.36 & 4803 \tabularnewline
0.04 & 5057.8 & 5067.08 & 5197 & 5197 & 5197 & 4965 & 5094.92 & 4965 \tabularnewline
0.06 & 5197 & 5197 & 5197 & 5197 & 5797.48 & 5197 & 5197 & 5197 \tabularnewline
0.08 & 6086.6 & 6175.56 & 6309 & 6309 & 6366.6 & 6309 & 5330.44 & 6309 \tabularnewline
0.1 & 6389 & 6425.9 & 6389 & 6573.5 & 6721.1 & 6389 & 6721.1 & 6389 \tabularnewline
0.12 & 6854.4 & 6912.24 & 7240 & 7240 & 7245.12 & 6758 & 7085.76 & 6758 \tabularnewline
0.14 & 7265.6 & 7274.56 & 7304 & 7304 & 7388.24 & 7240 & 7269.44 & 7304 \tabularnewline
0.16 & 7498.4 & 7550.24 & 7628 & 7628 & 7801.36 & 7628 & 7381.76 & 7628 \tabularnewline
0.18 & 7943.2 & 8014.12 & 8022 & 8022 & 8115 & 8022 & 7635.88 & 8022 \tabularnewline
0.2 & 8172 & 8249.8 & 8172 & 8366.5 & 8483.2 & 8172 & 8483.2 & 8172 \tabularnewline
0.22 & 8566.6 & 8572.76 & 8589 & 8589 & 8588.44 & 8561 & 8577.24 & 8561 \tabularnewline
0.24 & 8771.4 & 8880.84 & 9045 & 9045 & 9085.96 & 8589 & 8753.16 & 9045 \tabularnewline
0.26 & 9198.6 & 9265.16 & 9301 & 9301 & 9301 & 9301 & 9080.84 & 9301 \tabularnewline
0.28 & 9301 & 9312.2 & 9301 & 9301 & 9373.8 & 9301 & 9429.8 & 9301 \tabularnewline
0.3 & 9441 & 9478.8 & 9441 & 9504 & 9529.2 & 9441 & 9529.2 & 9441 \tabularnewline
0.32 & 9568.4 & 9570.64 & 9574 & 9574 & 9573.16 & 9567 & 9570.36 & 9574 \tabularnewline
0.34 & 9894.8 & 10167.48 & 10376 & 10376 & 10384.52 & 9574 & 9782.52 & 10376 \tabularnewline
0.36 & 10461.2 & 10512.32 & 10518 & 10518 & 10518 & 10518 & 10381.68 & 10518 \tabularnewline
0.38 & 10518 & 10562.64 & 10518 & 10518 & 10622.16 & 10518 & 10721.36 & 10518 \tabularnewline
0.4 & 10766 & 10803.6 & 10766 & 10813 & 10822.4 & 10766 & 10822.4 & 10766 \tabularnewline
0.42 & 10868.4 & 10886.04 & 10902 & 10902 & 10892.76 & 10860 & 10875.96 & 10902 \tabularnewline
0.44 & 10903.6 & 10905.36 & 10906 & 10906 & 10905.84 & 10902 & 10902.64 & 10906 \tabularnewline
0.46 & 10961.8 & 11014.6 & 10999 & 10999 & 11035.4 & 10999 & 11243.4 & 10999 \tabularnewline
0.48 & 11207 & 11259 & 11259 & 11259 & 11259 & 11259 & 11259 & 11259 \tabularnewline
0.5 & 11259 & 11921.5 & 11259 & 11921.5 & 11921.5 & 11259 & 11921.5 & 11921.5 \tabularnewline
0.52 & 12590.8 & 12608.48 & 12618 & 12618 & 12607.12 & 12584 & 12593.52 & 12618 \tabularnewline
0.54 & 12672.4 & 12745.84 & 12754 & 12754 & 12734.96 & 12618 & 12626.16 & 12754 \tabularnewline
0.56 & 12932.2 & 13051.48 & 13051 & 13051 & 13051.12 & 13051 & 13053.52 & 13051 \tabularnewline
0.58 & 13053.4 & 13055.9 & 13054 & 13054 & 13055.1 & 13054 & 13057.1 & 13054 \tabularnewline
0.6 & 13059 & 13448.4 & 13059 & 13383.5 & 13318.6 & 13059 & 13318.6 & 13708 \tabularnewline
0.62 & 13819.4 & 14164.74 & 14265 & 14265 & 14031.06 & 13708 & 13808.26 & 14265 \tabularnewline
0.64 & 14307.8 & 14378 & 14372 & 14372 & 14346.32 & 14265 & 14516 & 14372 \tabularnewline
0.66 & 14462 & 14563.6 & 14522 & 14522 & 14513 & 14522 & 14640.4 & 14522 \tabularnewline
0.68 & 14650 & 14995.92 & 14682 & 14682 & 14760.48 & 14682 & 15022.08 & 14682 \tabularnewline
0.7 & 15336 & 15393.4 & 15336 & 15377 & 15360.6 & 15336 & 15360.6 & 15418 \tabularnewline
0.72 & 15538.8 & 15973.68 & 16022 & 16022 & 15707.92 & 15418 & 15466.32 & 16022 \tabularnewline
0.74 & 16039.2 & 16134.44 & 16065 & 16065 & 16050.38 & 16022 & 16491.56 & 16065 \tabularnewline
0.76 & 16362.6 & 16837.84 & 16561 & 16561 & 16481.64 & 16561 & 17053.16 & 16561 \tabularnewline
0.78 & 17176.2 & 17689.6 & 17330 & 17330 & 17342.4 & 17330 & 17590.4 & 17950 \tabularnewline
0.8 & 17950 & 18085.2 & 17950 & 18034.5 & 17983.8 & 17950 & 17983.8 & 18119 \tabularnewline
0.82 & 18125 & 18165.22 & 18149 & 18149 & 18130.4 & 18119 & 18943.78 & 18149 \tabularnewline
0.84 & 18473.4 & 18996 & 18960 & 18960 & 18603.16 & 18149 & 19074 & 18960 \tabularnewline
0.86 & 19050 & 19110.46 & 19110 & 19110 & 19071 & 19110 & 19110.54 & 19110 \tabularnewline
0.88 & 19110.8 & 20478.48 & 19111 & 19111 & 19110.92 & 19111 & 19754.52 & 21122 \tabularnewline
0.9 & 21122 & 21444.2 & 21122 & 21301 & 21157.8 & 21122 & 21157.8 & 21480 \tabularnewline
0.92 & 21985.8 & 24464.4 & 24009 & 24009 & 22188.12 & 21480 & 27348.6 & 24009 \tabularnewline
0.94 & 25527 & 28264.36 & 27804 & 27804 & 25754.7 & 24009 & 28697.64 & 27804 \tabularnewline
0.96 & 28616.4 & 29397.12 & 29158 & 29158 & 28670.56 & 29158 & 29345.88 & 29585 \tabularnewline
0.98 & 29499.6 & 31946.84 & 29585 & 29585 & 29508.14 & 29585 & 30251.16 & 32613 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191491&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]4835.4[/C][C]4838.64[/C][C]4965[/C][C]4965[/C][C]5006.76[/C][C]4803[/C][C]4929.36[/C][C]4803[/C][/ROW]
[ROW][C]0.04[/C][C]5057.8[/C][C]5067.08[/C][C]5197[/C][C]5197[/C][C]5197[/C][C]4965[/C][C]5094.92[/C][C]4965[/C][/ROW]
[ROW][C]0.06[/C][C]5197[/C][C]5197[/C][C]5197[/C][C]5197[/C][C]5797.48[/C][C]5197[/C][C]5197[/C][C]5197[/C][/ROW]
[ROW][C]0.08[/C][C]6086.6[/C][C]6175.56[/C][C]6309[/C][C]6309[/C][C]6366.6[/C][C]6309[/C][C]5330.44[/C][C]6309[/C][/ROW]
[ROW][C]0.1[/C][C]6389[/C][C]6425.9[/C][C]6389[/C][C]6573.5[/C][C]6721.1[/C][C]6389[/C][C]6721.1[/C][C]6389[/C][/ROW]
[ROW][C]0.12[/C][C]6854.4[/C][C]6912.24[/C][C]7240[/C][C]7240[/C][C]7245.12[/C][C]6758[/C][C]7085.76[/C][C]6758[/C][/ROW]
[ROW][C]0.14[/C][C]7265.6[/C][C]7274.56[/C][C]7304[/C][C]7304[/C][C]7388.24[/C][C]7240[/C][C]7269.44[/C][C]7304[/C][/ROW]
[ROW][C]0.16[/C][C]7498.4[/C][C]7550.24[/C][C]7628[/C][C]7628[/C][C]7801.36[/C][C]7628[/C][C]7381.76[/C][C]7628[/C][/ROW]
[ROW][C]0.18[/C][C]7943.2[/C][C]8014.12[/C][C]8022[/C][C]8022[/C][C]8115[/C][C]8022[/C][C]7635.88[/C][C]8022[/C][/ROW]
[ROW][C]0.2[/C][C]8172[/C][C]8249.8[/C][C]8172[/C][C]8366.5[/C][C]8483.2[/C][C]8172[/C][C]8483.2[/C][C]8172[/C][/ROW]
[ROW][C]0.22[/C][C]8566.6[/C][C]8572.76[/C][C]8589[/C][C]8589[/C][C]8588.44[/C][C]8561[/C][C]8577.24[/C][C]8561[/C][/ROW]
[ROW][C]0.24[/C][C]8771.4[/C][C]8880.84[/C][C]9045[/C][C]9045[/C][C]9085.96[/C][C]8589[/C][C]8753.16[/C][C]9045[/C][/ROW]
[ROW][C]0.26[/C][C]9198.6[/C][C]9265.16[/C][C]9301[/C][C]9301[/C][C]9301[/C][C]9301[/C][C]9080.84[/C][C]9301[/C][/ROW]
[ROW][C]0.28[/C][C]9301[/C][C]9312.2[/C][C]9301[/C][C]9301[/C][C]9373.8[/C][C]9301[/C][C]9429.8[/C][C]9301[/C][/ROW]
[ROW][C]0.3[/C][C]9441[/C][C]9478.8[/C][C]9441[/C][C]9504[/C][C]9529.2[/C][C]9441[/C][C]9529.2[/C][C]9441[/C][/ROW]
[ROW][C]0.32[/C][C]9568.4[/C][C]9570.64[/C][C]9574[/C][C]9574[/C][C]9573.16[/C][C]9567[/C][C]9570.36[/C][C]9574[/C][/ROW]
[ROW][C]0.34[/C][C]9894.8[/C][C]10167.48[/C][C]10376[/C][C]10376[/C][C]10384.52[/C][C]9574[/C][C]9782.52[/C][C]10376[/C][/ROW]
[ROW][C]0.36[/C][C]10461.2[/C][C]10512.32[/C][C]10518[/C][C]10518[/C][C]10518[/C][C]10518[/C][C]10381.68[/C][C]10518[/C][/ROW]
[ROW][C]0.38[/C][C]10518[/C][C]10562.64[/C][C]10518[/C][C]10518[/C][C]10622.16[/C][C]10518[/C][C]10721.36[/C][C]10518[/C][/ROW]
[ROW][C]0.4[/C][C]10766[/C][C]10803.6[/C][C]10766[/C][C]10813[/C][C]10822.4[/C][C]10766[/C][C]10822.4[/C][C]10766[/C][/ROW]
[ROW][C]0.42[/C][C]10868.4[/C][C]10886.04[/C][C]10902[/C][C]10902[/C][C]10892.76[/C][C]10860[/C][C]10875.96[/C][C]10902[/C][/ROW]
[ROW][C]0.44[/C][C]10903.6[/C][C]10905.36[/C][C]10906[/C][C]10906[/C][C]10905.84[/C][C]10902[/C][C]10902.64[/C][C]10906[/C][/ROW]
[ROW][C]0.46[/C][C]10961.8[/C][C]11014.6[/C][C]10999[/C][C]10999[/C][C]11035.4[/C][C]10999[/C][C]11243.4[/C][C]10999[/C][/ROW]
[ROW][C]0.48[/C][C]11207[/C][C]11259[/C][C]11259[/C][C]11259[/C][C]11259[/C][C]11259[/C][C]11259[/C][C]11259[/C][/ROW]
[ROW][C]0.5[/C][C]11259[/C][C]11921.5[/C][C]11259[/C][C]11921.5[/C][C]11921.5[/C][C]11259[/C][C]11921.5[/C][C]11921.5[/C][/ROW]
[ROW][C]0.52[/C][C]12590.8[/C][C]12608.48[/C][C]12618[/C][C]12618[/C][C]12607.12[/C][C]12584[/C][C]12593.52[/C][C]12618[/C][/ROW]
[ROW][C]0.54[/C][C]12672.4[/C][C]12745.84[/C][C]12754[/C][C]12754[/C][C]12734.96[/C][C]12618[/C][C]12626.16[/C][C]12754[/C][/ROW]
[ROW][C]0.56[/C][C]12932.2[/C][C]13051.48[/C][C]13051[/C][C]13051[/C][C]13051.12[/C][C]13051[/C][C]13053.52[/C][C]13051[/C][/ROW]
[ROW][C]0.58[/C][C]13053.4[/C][C]13055.9[/C][C]13054[/C][C]13054[/C][C]13055.1[/C][C]13054[/C][C]13057.1[/C][C]13054[/C][/ROW]
[ROW][C]0.6[/C][C]13059[/C][C]13448.4[/C][C]13059[/C][C]13383.5[/C][C]13318.6[/C][C]13059[/C][C]13318.6[/C][C]13708[/C][/ROW]
[ROW][C]0.62[/C][C]13819.4[/C][C]14164.74[/C][C]14265[/C][C]14265[/C][C]14031.06[/C][C]13708[/C][C]13808.26[/C][C]14265[/C][/ROW]
[ROW][C]0.64[/C][C]14307.8[/C][C]14378[/C][C]14372[/C][C]14372[/C][C]14346.32[/C][C]14265[/C][C]14516[/C][C]14372[/C][/ROW]
[ROW][C]0.66[/C][C]14462[/C][C]14563.6[/C][C]14522[/C][C]14522[/C][C]14513[/C][C]14522[/C][C]14640.4[/C][C]14522[/C][/ROW]
[ROW][C]0.68[/C][C]14650[/C][C]14995.92[/C][C]14682[/C][C]14682[/C][C]14760.48[/C][C]14682[/C][C]15022.08[/C][C]14682[/C][/ROW]
[ROW][C]0.7[/C][C]15336[/C][C]15393.4[/C][C]15336[/C][C]15377[/C][C]15360.6[/C][C]15336[/C][C]15360.6[/C][C]15418[/C][/ROW]
[ROW][C]0.72[/C][C]15538.8[/C][C]15973.68[/C][C]16022[/C][C]16022[/C][C]15707.92[/C][C]15418[/C][C]15466.32[/C][C]16022[/C][/ROW]
[ROW][C]0.74[/C][C]16039.2[/C][C]16134.44[/C][C]16065[/C][C]16065[/C][C]16050.38[/C][C]16022[/C][C]16491.56[/C][C]16065[/C][/ROW]
[ROW][C]0.76[/C][C]16362.6[/C][C]16837.84[/C][C]16561[/C][C]16561[/C][C]16481.64[/C][C]16561[/C][C]17053.16[/C][C]16561[/C][/ROW]
[ROW][C]0.78[/C][C]17176.2[/C][C]17689.6[/C][C]17330[/C][C]17330[/C][C]17342.4[/C][C]17330[/C][C]17590.4[/C][C]17950[/C][/ROW]
[ROW][C]0.8[/C][C]17950[/C][C]18085.2[/C][C]17950[/C][C]18034.5[/C][C]17983.8[/C][C]17950[/C][C]17983.8[/C][C]18119[/C][/ROW]
[ROW][C]0.82[/C][C]18125[/C][C]18165.22[/C][C]18149[/C][C]18149[/C][C]18130.4[/C][C]18119[/C][C]18943.78[/C][C]18149[/C][/ROW]
[ROW][C]0.84[/C][C]18473.4[/C][C]18996[/C][C]18960[/C][C]18960[/C][C]18603.16[/C][C]18149[/C][C]19074[/C][C]18960[/C][/ROW]
[ROW][C]0.86[/C][C]19050[/C][C]19110.46[/C][C]19110[/C][C]19110[/C][C]19071[/C][C]19110[/C][C]19110.54[/C][C]19110[/C][/ROW]
[ROW][C]0.88[/C][C]19110.8[/C][C]20478.48[/C][C]19111[/C][C]19111[/C][C]19110.92[/C][C]19111[/C][C]19754.52[/C][C]21122[/C][/ROW]
[ROW][C]0.9[/C][C]21122[/C][C]21444.2[/C][C]21122[/C][C]21301[/C][C]21157.8[/C][C]21122[/C][C]21157.8[/C][C]21480[/C][/ROW]
[ROW][C]0.92[/C][C]21985.8[/C][C]24464.4[/C][C]24009[/C][C]24009[/C][C]22188.12[/C][C]21480[/C][C]27348.6[/C][C]24009[/C][/ROW]
[ROW][C]0.94[/C][C]25527[/C][C]28264.36[/C][C]27804[/C][C]27804[/C][C]25754.7[/C][C]24009[/C][C]28697.64[/C][C]27804[/C][/ROW]
[ROW][C]0.96[/C][C]28616.4[/C][C]29397.12[/C][C]29158[/C][C]29158[/C][C]28670.56[/C][C]29158[/C][C]29345.88[/C][C]29585[/C][/ROW]
[ROW][C]0.98[/C][C]29499.6[/C][C]31946.84[/C][C]29585[/C][C]29585[/C][C]29508.14[/C][C]29585[/C][C]30251.16[/C][C]32613[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191491&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191491&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)
0.024835.44838.64496549655006.7648034929.364803
0.045057.85067.0851975197519749655094.924965
0.0651975197519751975797.48519751975197
0.086086.66175.56630963096366.663095330.446309
0.163896425.963896573.56721.163896721.16389
0.126854.46912.24724072407245.1267587085.766758
0.147265.67274.56730473047388.2472407269.447304
0.167498.47550.24762876287801.3676287381.767628
0.187943.28014.1280228022811580227635.888022
0.281728249.881728366.58483.281728483.28172
0.228566.68572.76858985898588.4485618577.248561
0.248771.48880.84904590459085.9685898753.169045
0.269198.69265.1693019301930193019080.849301
0.2893019312.2930193019373.893019429.89301
0.394419478.8944195049529.294419529.29441
0.329568.49570.64957495749573.1695679570.369574
0.349894.810167.48103761037610384.5295749782.5210376
0.3610461.210512.321051810518105181051810381.6810518
0.381051810562.64105181051810622.161051810721.3610518
0.41076610803.6107661081310822.41076610822.410766
0.4210868.410886.04109021090210892.761086010875.9610902
0.4410903.610905.36109061090610905.841090210902.6410906
0.4610961.811014.6109991099911035.41099911243.410999
0.481120711259112591125911259112591125911259
0.51125911921.51125911921.511921.51125911921.511921.5
0.5212590.812608.48126181261812607.121258412593.5212618
0.5412672.412745.84127541275412734.961261812626.1612754
0.5612932.213051.48130511305113051.121305113053.5213051
0.5813053.413055.9130541305413055.11305413057.113054
0.61305913448.41305913383.513318.61305913318.613708
0.6213819.414164.74142651426514031.061370813808.2614265
0.6414307.814378143721437214346.32142651451614372
0.661446214563.61452214522145131452214640.414522
0.681465014995.92146821468214760.481468215022.0814682
0.71533615393.4153361537715360.61533615360.615418
0.7215538.815973.68160221602215707.921541815466.3216022
0.7416039.216134.44160651606516050.381602216491.5616065
0.7616362.616837.84165611656116481.641656117053.1616561
0.7817176.217689.6173301733017342.41733017590.417950
0.81795018085.21795018034.517983.81795017983.818119
0.821812518165.22181491814918130.41811918943.7818149
0.8418473.418996189601896018603.16181491907418960
0.861905019110.461911019110190711911019110.5419110
0.8819110.820478.48191111911119110.921911119754.5221122
0.92112221444.2211222130121157.82112221157.821480
0.9221985.824464.4240092400922188.122148027348.624009
0.942552728264.36278042780425754.72400928697.6427804
0.9628616.429397.12291582915828670.562915829345.8829585
0.9829499.631946.84295852958529508.142958530251.1632613



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')