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Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationSun, 19 Oct 2008 05:53:20 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/19/t1224417251a87g4di20txkfri.htm/, Retrieved Sun, 19 May 2024 13:58:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16780, Retrieved Sun, 19 May 2024 13:58:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Werkloosheid WAAL...] [2008-10-19 10:43:11] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMP   [Histogram] [Histogram - Werkl...] [2008-10-19 11:32:59] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RM        [Percentiles] [Percentiles - Wal...] [2008-10-19 11:53:20] [b23db733701c4d62df5e228d507c1c6a] [Current]
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Dataseries X:
258778
252791
256389
258961
258647
256304
250498
247883
249552
262626
264416
273049
272441
267564
265952
263937
264765
263386
258985
257334
257477
271486
274488
281274
272674
269704
268227
276444
272247
268516
263406
263619
265905
281681
287413
289423
281242
273878
269022
272630
270287
260447
262248
252806
238663
258438
266719
263279
258064
248828
248284
253376
251846
239494
239709
228793
229521
249999
254016
251178




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=16780&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=16780&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16780&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)
0.02228938.6228953.16229521229521231166.56228793229360.84228793
0.04233177.8233543.48238663238663238962.16229521234640.52229521
0.06239161.6239211.46239494239494239610.1239494238945.54239494
0.08239666239683.2239709239709245594.28239709239519.8239709
0.1247883247923.1247883248083.5248243.9247883248243.9247883
0.12248392.8248458.08248828248828248885.92248284248653.92248284
0.14249117.6249218.96249552249552249668.22248828249161.04249552
0.16249820.2249891.72249999249999250218.56249999249659.28249999
0.18250398.2250488.02250498250498250919.6250498250008.98250498
0.2251178251311.6251178251512251712.4251178251712.4251178
0.22252035252242.9252791252791252772.1251846252394.1251846
0.24252797252800.6252806252806252897.2252791252796.4252806
0.26253148253296.2253376253376253593.6253376252885.8253376
0.28253888254199.04254016254016255205.76254016256120.96254016
0.3256304256329.5256304256346.5256363.5256304256363.5256304
0.32256578256880.4257334257334257220.6256389256842.6257334
0.34257391.2257439.82257477257477257512.22257334257371.18257477
0.36257829.2258040.52258064258064258153.76258064257500.48258064
0.38258363.2258475.62258438258438258525.78258438258609.38258438
0.4258647258699.4258647258712.5258725.6258647258725.6258647
0.42258814.6258891.46258961258961258920.74258778258847.54258961
0.44258970.6258981.16258985258985258984.04258961258964.84258985
0.46259862.2260555.06260447260447260699.14260447262139.94260447
0.48261887.8262353.84262248262248262368.96262248262520.16262248
0.5262626262952.5262626262952.5262952.5262626262952.5262952.5
0.52263300.4263356.04263386263386263351.76263279263308.96263386
0.54263394263404.8263406263406263403.2263386263387.2263406
0.56263533.8263669.88263619263619263631.72263619263886.12263619
0.58263873.4264119.02263937263937264042.38263937264233.98263937
0.6264416264625.4264416264590.5264555.6264416264555.6264765
0.62264993265699.8265905265905265426.2264765264970.2265905
0.64265923.8265982.68265952265952265940.72265905266688.32265952
0.66266412.2266938.7266719266719266672.98266719267344.3266719
0.68267395267882.24267564267564267643.56267564267908.76267564
0.7268227268429.3268227268371.5268313.7268227268313.7268516
0.72268617.2268981.52269022269022268758.88268516268556.48269022
0.74269294.8269785.62269704269704269472.12269022270205.38269704
0.76270053.8270718.64270287270287270193.72270287271054.36270287
0.78271246.2271927.38271486271486271501.22271486271805.62272247
0.8272247272402.2272247272344272285.8272247272285.8272441
0.82272478.8272630.88272630272630272512.82272441272673.12272630
0.84272647.6272764272674272674272654.64272630272959272674
0.86272899273430.34273049273049272951.5273049273496.66273049
0.88273712.2274292.8273878273878273811.68273878274073.2274488
0.9274488276248.4274488275466274683.6274488274683.6276444
0.92277403.6281245.84281242281242277787.44276444281270.16281242
0.94281254.8281412.38281274281274281256.72281242281542.62281274
0.96281518.2284890.92281681281681281534.48281681284203.08287413
0.98286266.6288980.8287413287413286381.24287413287855.2289423

\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 & 228938.6 & 228953.16 & 229521 & 229521 & 231166.56 & 228793 & 229360.84 & 228793 \tabularnewline
0.04 & 233177.8 & 233543.48 & 238663 & 238663 & 238962.16 & 229521 & 234640.52 & 229521 \tabularnewline
0.06 & 239161.6 & 239211.46 & 239494 & 239494 & 239610.1 & 239494 & 238945.54 & 239494 \tabularnewline
0.08 & 239666 & 239683.2 & 239709 & 239709 & 245594.28 & 239709 & 239519.8 & 239709 \tabularnewline
0.1 & 247883 & 247923.1 & 247883 & 248083.5 & 248243.9 & 247883 & 248243.9 & 247883 \tabularnewline
0.12 & 248392.8 & 248458.08 & 248828 & 248828 & 248885.92 & 248284 & 248653.92 & 248284 \tabularnewline
0.14 & 249117.6 & 249218.96 & 249552 & 249552 & 249668.22 & 248828 & 249161.04 & 249552 \tabularnewline
0.16 & 249820.2 & 249891.72 & 249999 & 249999 & 250218.56 & 249999 & 249659.28 & 249999 \tabularnewline
0.18 & 250398.2 & 250488.02 & 250498 & 250498 & 250919.6 & 250498 & 250008.98 & 250498 \tabularnewline
0.2 & 251178 & 251311.6 & 251178 & 251512 & 251712.4 & 251178 & 251712.4 & 251178 \tabularnewline
0.22 & 252035 & 252242.9 & 252791 & 252791 & 252772.1 & 251846 & 252394.1 & 251846 \tabularnewline
0.24 & 252797 & 252800.6 & 252806 & 252806 & 252897.2 & 252791 & 252796.4 & 252806 \tabularnewline
0.26 & 253148 & 253296.2 & 253376 & 253376 & 253593.6 & 253376 & 252885.8 & 253376 \tabularnewline
0.28 & 253888 & 254199.04 & 254016 & 254016 & 255205.76 & 254016 & 256120.96 & 254016 \tabularnewline
0.3 & 256304 & 256329.5 & 256304 & 256346.5 & 256363.5 & 256304 & 256363.5 & 256304 \tabularnewline
0.32 & 256578 & 256880.4 & 257334 & 257334 & 257220.6 & 256389 & 256842.6 & 257334 \tabularnewline
0.34 & 257391.2 & 257439.82 & 257477 & 257477 & 257512.22 & 257334 & 257371.18 & 257477 \tabularnewline
0.36 & 257829.2 & 258040.52 & 258064 & 258064 & 258153.76 & 258064 & 257500.48 & 258064 \tabularnewline
0.38 & 258363.2 & 258475.62 & 258438 & 258438 & 258525.78 & 258438 & 258609.38 & 258438 \tabularnewline
0.4 & 258647 & 258699.4 & 258647 & 258712.5 & 258725.6 & 258647 & 258725.6 & 258647 \tabularnewline
0.42 & 258814.6 & 258891.46 & 258961 & 258961 & 258920.74 & 258778 & 258847.54 & 258961 \tabularnewline
0.44 & 258970.6 & 258981.16 & 258985 & 258985 & 258984.04 & 258961 & 258964.84 & 258985 \tabularnewline
0.46 & 259862.2 & 260555.06 & 260447 & 260447 & 260699.14 & 260447 & 262139.94 & 260447 \tabularnewline
0.48 & 261887.8 & 262353.84 & 262248 & 262248 & 262368.96 & 262248 & 262520.16 & 262248 \tabularnewline
0.5 & 262626 & 262952.5 & 262626 & 262952.5 & 262952.5 & 262626 & 262952.5 & 262952.5 \tabularnewline
0.52 & 263300.4 & 263356.04 & 263386 & 263386 & 263351.76 & 263279 & 263308.96 & 263386 \tabularnewline
0.54 & 263394 & 263404.8 & 263406 & 263406 & 263403.2 & 263386 & 263387.2 & 263406 \tabularnewline
0.56 & 263533.8 & 263669.88 & 263619 & 263619 & 263631.72 & 263619 & 263886.12 & 263619 \tabularnewline
0.58 & 263873.4 & 264119.02 & 263937 & 263937 & 264042.38 & 263937 & 264233.98 & 263937 \tabularnewline
0.6 & 264416 & 264625.4 & 264416 & 264590.5 & 264555.6 & 264416 & 264555.6 & 264765 \tabularnewline
0.62 & 264993 & 265699.8 & 265905 & 265905 & 265426.2 & 264765 & 264970.2 & 265905 \tabularnewline
0.64 & 265923.8 & 265982.68 & 265952 & 265952 & 265940.72 & 265905 & 266688.32 & 265952 \tabularnewline
0.66 & 266412.2 & 266938.7 & 266719 & 266719 & 266672.98 & 266719 & 267344.3 & 266719 \tabularnewline
0.68 & 267395 & 267882.24 & 267564 & 267564 & 267643.56 & 267564 & 267908.76 & 267564 \tabularnewline
0.7 & 268227 & 268429.3 & 268227 & 268371.5 & 268313.7 & 268227 & 268313.7 & 268516 \tabularnewline
0.72 & 268617.2 & 268981.52 & 269022 & 269022 & 268758.88 & 268516 & 268556.48 & 269022 \tabularnewline
0.74 & 269294.8 & 269785.62 & 269704 & 269704 & 269472.12 & 269022 & 270205.38 & 269704 \tabularnewline
0.76 & 270053.8 & 270718.64 & 270287 & 270287 & 270193.72 & 270287 & 271054.36 & 270287 \tabularnewline
0.78 & 271246.2 & 271927.38 & 271486 & 271486 & 271501.22 & 271486 & 271805.62 & 272247 \tabularnewline
0.8 & 272247 & 272402.2 & 272247 & 272344 & 272285.8 & 272247 & 272285.8 & 272441 \tabularnewline
0.82 & 272478.8 & 272630.88 & 272630 & 272630 & 272512.82 & 272441 & 272673.12 & 272630 \tabularnewline
0.84 & 272647.6 & 272764 & 272674 & 272674 & 272654.64 & 272630 & 272959 & 272674 \tabularnewline
0.86 & 272899 & 273430.34 & 273049 & 273049 & 272951.5 & 273049 & 273496.66 & 273049 \tabularnewline
0.88 & 273712.2 & 274292.8 & 273878 & 273878 & 273811.68 & 273878 & 274073.2 & 274488 \tabularnewline
0.9 & 274488 & 276248.4 & 274488 & 275466 & 274683.6 & 274488 & 274683.6 & 276444 \tabularnewline
0.92 & 277403.6 & 281245.84 & 281242 & 281242 & 277787.44 & 276444 & 281270.16 & 281242 \tabularnewline
0.94 & 281254.8 & 281412.38 & 281274 & 281274 & 281256.72 & 281242 & 281542.62 & 281274 \tabularnewline
0.96 & 281518.2 & 284890.92 & 281681 & 281681 & 281534.48 & 281681 & 284203.08 & 287413 \tabularnewline
0.98 & 286266.6 & 288980.8 & 287413 & 287413 & 286381.24 & 287413 & 287855.2 & 289423 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16780&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]228938.6[/C][C]228953.16[/C][C]229521[/C][C]229521[/C][C]231166.56[/C][C]228793[/C][C]229360.84[/C][C]228793[/C][/ROW]
[ROW][C]0.04[/C][C]233177.8[/C][C]233543.48[/C][C]238663[/C][C]238663[/C][C]238962.16[/C][C]229521[/C][C]234640.52[/C][C]229521[/C][/ROW]
[ROW][C]0.06[/C][C]239161.6[/C][C]239211.46[/C][C]239494[/C][C]239494[/C][C]239610.1[/C][C]239494[/C][C]238945.54[/C][C]239494[/C][/ROW]
[ROW][C]0.08[/C][C]239666[/C][C]239683.2[/C][C]239709[/C][C]239709[/C][C]245594.28[/C][C]239709[/C][C]239519.8[/C][C]239709[/C][/ROW]
[ROW][C]0.1[/C][C]247883[/C][C]247923.1[/C][C]247883[/C][C]248083.5[/C][C]248243.9[/C][C]247883[/C][C]248243.9[/C][C]247883[/C][/ROW]
[ROW][C]0.12[/C][C]248392.8[/C][C]248458.08[/C][C]248828[/C][C]248828[/C][C]248885.92[/C][C]248284[/C][C]248653.92[/C][C]248284[/C][/ROW]
[ROW][C]0.14[/C][C]249117.6[/C][C]249218.96[/C][C]249552[/C][C]249552[/C][C]249668.22[/C][C]248828[/C][C]249161.04[/C][C]249552[/C][/ROW]
[ROW][C]0.16[/C][C]249820.2[/C][C]249891.72[/C][C]249999[/C][C]249999[/C][C]250218.56[/C][C]249999[/C][C]249659.28[/C][C]249999[/C][/ROW]
[ROW][C]0.18[/C][C]250398.2[/C][C]250488.02[/C][C]250498[/C][C]250498[/C][C]250919.6[/C][C]250498[/C][C]250008.98[/C][C]250498[/C][/ROW]
[ROW][C]0.2[/C][C]251178[/C][C]251311.6[/C][C]251178[/C][C]251512[/C][C]251712.4[/C][C]251178[/C][C]251712.4[/C][C]251178[/C][/ROW]
[ROW][C]0.22[/C][C]252035[/C][C]252242.9[/C][C]252791[/C][C]252791[/C][C]252772.1[/C][C]251846[/C][C]252394.1[/C][C]251846[/C][/ROW]
[ROW][C]0.24[/C][C]252797[/C][C]252800.6[/C][C]252806[/C][C]252806[/C][C]252897.2[/C][C]252791[/C][C]252796.4[/C][C]252806[/C][/ROW]
[ROW][C]0.26[/C][C]253148[/C][C]253296.2[/C][C]253376[/C][C]253376[/C][C]253593.6[/C][C]253376[/C][C]252885.8[/C][C]253376[/C][/ROW]
[ROW][C]0.28[/C][C]253888[/C][C]254199.04[/C][C]254016[/C][C]254016[/C][C]255205.76[/C][C]254016[/C][C]256120.96[/C][C]254016[/C][/ROW]
[ROW][C]0.3[/C][C]256304[/C][C]256329.5[/C][C]256304[/C][C]256346.5[/C][C]256363.5[/C][C]256304[/C][C]256363.5[/C][C]256304[/C][/ROW]
[ROW][C]0.32[/C][C]256578[/C][C]256880.4[/C][C]257334[/C][C]257334[/C][C]257220.6[/C][C]256389[/C][C]256842.6[/C][C]257334[/C][/ROW]
[ROW][C]0.34[/C][C]257391.2[/C][C]257439.82[/C][C]257477[/C][C]257477[/C][C]257512.22[/C][C]257334[/C][C]257371.18[/C][C]257477[/C][/ROW]
[ROW][C]0.36[/C][C]257829.2[/C][C]258040.52[/C][C]258064[/C][C]258064[/C][C]258153.76[/C][C]258064[/C][C]257500.48[/C][C]258064[/C][/ROW]
[ROW][C]0.38[/C][C]258363.2[/C][C]258475.62[/C][C]258438[/C][C]258438[/C][C]258525.78[/C][C]258438[/C][C]258609.38[/C][C]258438[/C][/ROW]
[ROW][C]0.4[/C][C]258647[/C][C]258699.4[/C][C]258647[/C][C]258712.5[/C][C]258725.6[/C][C]258647[/C][C]258725.6[/C][C]258647[/C][/ROW]
[ROW][C]0.42[/C][C]258814.6[/C][C]258891.46[/C][C]258961[/C][C]258961[/C][C]258920.74[/C][C]258778[/C][C]258847.54[/C][C]258961[/C][/ROW]
[ROW][C]0.44[/C][C]258970.6[/C][C]258981.16[/C][C]258985[/C][C]258985[/C][C]258984.04[/C][C]258961[/C][C]258964.84[/C][C]258985[/C][/ROW]
[ROW][C]0.46[/C][C]259862.2[/C][C]260555.06[/C][C]260447[/C][C]260447[/C][C]260699.14[/C][C]260447[/C][C]262139.94[/C][C]260447[/C][/ROW]
[ROW][C]0.48[/C][C]261887.8[/C][C]262353.84[/C][C]262248[/C][C]262248[/C][C]262368.96[/C][C]262248[/C][C]262520.16[/C][C]262248[/C][/ROW]
[ROW][C]0.5[/C][C]262626[/C][C]262952.5[/C][C]262626[/C][C]262952.5[/C][C]262952.5[/C][C]262626[/C][C]262952.5[/C][C]262952.5[/C][/ROW]
[ROW][C]0.52[/C][C]263300.4[/C][C]263356.04[/C][C]263386[/C][C]263386[/C][C]263351.76[/C][C]263279[/C][C]263308.96[/C][C]263386[/C][/ROW]
[ROW][C]0.54[/C][C]263394[/C][C]263404.8[/C][C]263406[/C][C]263406[/C][C]263403.2[/C][C]263386[/C][C]263387.2[/C][C]263406[/C][/ROW]
[ROW][C]0.56[/C][C]263533.8[/C][C]263669.88[/C][C]263619[/C][C]263619[/C][C]263631.72[/C][C]263619[/C][C]263886.12[/C][C]263619[/C][/ROW]
[ROW][C]0.58[/C][C]263873.4[/C][C]264119.02[/C][C]263937[/C][C]263937[/C][C]264042.38[/C][C]263937[/C][C]264233.98[/C][C]263937[/C][/ROW]
[ROW][C]0.6[/C][C]264416[/C][C]264625.4[/C][C]264416[/C][C]264590.5[/C][C]264555.6[/C][C]264416[/C][C]264555.6[/C][C]264765[/C][/ROW]
[ROW][C]0.62[/C][C]264993[/C][C]265699.8[/C][C]265905[/C][C]265905[/C][C]265426.2[/C][C]264765[/C][C]264970.2[/C][C]265905[/C][/ROW]
[ROW][C]0.64[/C][C]265923.8[/C][C]265982.68[/C][C]265952[/C][C]265952[/C][C]265940.72[/C][C]265905[/C][C]266688.32[/C][C]265952[/C][/ROW]
[ROW][C]0.66[/C][C]266412.2[/C][C]266938.7[/C][C]266719[/C][C]266719[/C][C]266672.98[/C][C]266719[/C][C]267344.3[/C][C]266719[/C][/ROW]
[ROW][C]0.68[/C][C]267395[/C][C]267882.24[/C][C]267564[/C][C]267564[/C][C]267643.56[/C][C]267564[/C][C]267908.76[/C][C]267564[/C][/ROW]
[ROW][C]0.7[/C][C]268227[/C][C]268429.3[/C][C]268227[/C][C]268371.5[/C][C]268313.7[/C][C]268227[/C][C]268313.7[/C][C]268516[/C][/ROW]
[ROW][C]0.72[/C][C]268617.2[/C][C]268981.52[/C][C]269022[/C][C]269022[/C][C]268758.88[/C][C]268516[/C][C]268556.48[/C][C]269022[/C][/ROW]
[ROW][C]0.74[/C][C]269294.8[/C][C]269785.62[/C][C]269704[/C][C]269704[/C][C]269472.12[/C][C]269022[/C][C]270205.38[/C][C]269704[/C][/ROW]
[ROW][C]0.76[/C][C]270053.8[/C][C]270718.64[/C][C]270287[/C][C]270287[/C][C]270193.72[/C][C]270287[/C][C]271054.36[/C][C]270287[/C][/ROW]
[ROW][C]0.78[/C][C]271246.2[/C][C]271927.38[/C][C]271486[/C][C]271486[/C][C]271501.22[/C][C]271486[/C][C]271805.62[/C][C]272247[/C][/ROW]
[ROW][C]0.8[/C][C]272247[/C][C]272402.2[/C][C]272247[/C][C]272344[/C][C]272285.8[/C][C]272247[/C][C]272285.8[/C][C]272441[/C][/ROW]
[ROW][C]0.82[/C][C]272478.8[/C][C]272630.88[/C][C]272630[/C][C]272630[/C][C]272512.82[/C][C]272441[/C][C]272673.12[/C][C]272630[/C][/ROW]
[ROW][C]0.84[/C][C]272647.6[/C][C]272764[/C][C]272674[/C][C]272674[/C][C]272654.64[/C][C]272630[/C][C]272959[/C][C]272674[/C][/ROW]
[ROW][C]0.86[/C][C]272899[/C][C]273430.34[/C][C]273049[/C][C]273049[/C][C]272951.5[/C][C]273049[/C][C]273496.66[/C][C]273049[/C][/ROW]
[ROW][C]0.88[/C][C]273712.2[/C][C]274292.8[/C][C]273878[/C][C]273878[/C][C]273811.68[/C][C]273878[/C][C]274073.2[/C][C]274488[/C][/ROW]
[ROW][C]0.9[/C][C]274488[/C][C]276248.4[/C][C]274488[/C][C]275466[/C][C]274683.6[/C][C]274488[/C][C]274683.6[/C][C]276444[/C][/ROW]
[ROW][C]0.92[/C][C]277403.6[/C][C]281245.84[/C][C]281242[/C][C]281242[/C][C]277787.44[/C][C]276444[/C][C]281270.16[/C][C]281242[/C][/ROW]
[ROW][C]0.94[/C][C]281254.8[/C][C]281412.38[/C][C]281274[/C][C]281274[/C][C]281256.72[/C][C]281242[/C][C]281542.62[/C][C]281274[/C][/ROW]
[ROW][C]0.96[/C][C]281518.2[/C][C]284890.92[/C][C]281681[/C][C]281681[/C][C]281534.48[/C][C]281681[/C][C]284203.08[/C][C]287413[/C][/ROW]
[ROW][C]0.98[/C][C]286266.6[/C][C]288980.8[/C][C]287413[/C][C]287413[/C][C]286381.24[/C][C]287413[/C][C]287855.2[/C][C]289423[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16780&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16780&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)
0.02228938.6228953.16229521229521231166.56228793229360.84228793
0.04233177.8233543.48238663238663238962.16229521234640.52229521
0.06239161.6239211.46239494239494239610.1239494238945.54239494
0.08239666239683.2239709239709245594.28239709239519.8239709
0.1247883247923.1247883248083.5248243.9247883248243.9247883
0.12248392.8248458.08248828248828248885.92248284248653.92248284
0.14249117.6249218.96249552249552249668.22248828249161.04249552
0.16249820.2249891.72249999249999250218.56249999249659.28249999
0.18250398.2250488.02250498250498250919.6250498250008.98250498
0.2251178251311.6251178251512251712.4251178251712.4251178
0.22252035252242.9252791252791252772.1251846252394.1251846
0.24252797252800.6252806252806252897.2252791252796.4252806
0.26253148253296.2253376253376253593.6253376252885.8253376
0.28253888254199.04254016254016255205.76254016256120.96254016
0.3256304256329.5256304256346.5256363.5256304256363.5256304
0.32256578256880.4257334257334257220.6256389256842.6257334
0.34257391.2257439.82257477257477257512.22257334257371.18257477
0.36257829.2258040.52258064258064258153.76258064257500.48258064
0.38258363.2258475.62258438258438258525.78258438258609.38258438
0.4258647258699.4258647258712.5258725.6258647258725.6258647
0.42258814.6258891.46258961258961258920.74258778258847.54258961
0.44258970.6258981.16258985258985258984.04258961258964.84258985
0.46259862.2260555.06260447260447260699.14260447262139.94260447
0.48261887.8262353.84262248262248262368.96262248262520.16262248
0.5262626262952.5262626262952.5262952.5262626262952.5262952.5
0.52263300.4263356.04263386263386263351.76263279263308.96263386
0.54263394263404.8263406263406263403.2263386263387.2263406
0.56263533.8263669.88263619263619263631.72263619263886.12263619
0.58263873.4264119.02263937263937264042.38263937264233.98263937
0.6264416264625.4264416264590.5264555.6264416264555.6264765
0.62264993265699.8265905265905265426.2264765264970.2265905
0.64265923.8265982.68265952265952265940.72265905266688.32265952
0.66266412.2266938.7266719266719266672.98266719267344.3266719
0.68267395267882.24267564267564267643.56267564267908.76267564
0.7268227268429.3268227268371.5268313.7268227268313.7268516
0.72268617.2268981.52269022269022268758.88268516268556.48269022
0.74269294.8269785.62269704269704269472.12269022270205.38269704
0.76270053.8270718.64270287270287270193.72270287271054.36270287
0.78271246.2271927.38271486271486271501.22271486271805.62272247
0.8272247272402.2272247272344272285.8272247272285.8272441
0.82272478.8272630.88272630272630272512.82272441272673.12272630
0.84272647.6272764272674272674272654.64272630272959272674
0.86272899273430.34273049273049272951.5273049273496.66273049
0.88273712.2274292.8273878273878273811.68273878274073.2274488
0.9274488276248.4274488275466274683.6274488274683.6276444
0.92277403.6281245.84281242281242277787.44276444281270.16281242
0.94281254.8281412.38281274281274281256.72281242281542.62281274
0.96281518.2284890.92281681281681281534.48281681284203.08287413
0.98286266.6288980.8287413287413286381.24287413287855.2289423



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
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')