Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationWed, 03 Mar 2010 11:39:15 -0700
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/Mar/03/t12676418939zz3x6qd1q0amuo.htm/, Retrieved Sun, 23 Jan 2022 03:23:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=73936, Retrieved Sun, 23 Jan 2022 03:23:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Percentiles Sales...] [2010-03-03 18:39:15] [7305f5ba5e018172148a6d5988ec7f42] [Current]
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Dataseries X:
164
96
73
49
39
59
169
169
210
278
298
245
200
188
90
79
78
91
167
169
289
247
275
203
223
104
107
85
75
99
135
211
335
488
326
346
261
224
141
148
145
223
272
445
560
612
467
404
518
404
300
210
196
186
247
343
464
680
711
610
513
292
273
322
189
257
324
404
677
858
895
664
628
308
324
248
272




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=73936&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=73936&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=73936&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)
0.0244.444.6494954.24943.449
0.0460.1260.68737373.085971.3259
0.0674.2474.36757576.687573.6475
0.0878.1678.24797979.487878.7678
0.183.283.88585888580.285
0.1290.2490.36919191.69090.6490
0.1494.995.6969697.929691.496
0.16100.6101.4104104104.4899101.699
0.18106.58108.12107107126.04107133.88107
0.2137.4138.6141141141.8135137.4141
0.22144.76145.48145145147.16145147.52145
0.24155.68159.52164164164.72148152.48164
0.26167.04167.56169169168.52167168.44167
0.28169169169169169169169169
0.3170.7175.8186186182.6169179.2169
0.32187.28187.92188188188.32188186.08188
0.34190.26192.64196196194.88189192.36196
0.36198.88200.24200200201.08200202.76200
0.38204.82207.48210210209.16203205.52210
0.4210210.2210210210.4210210.8210
0.42215.08220.12223223222.04211213.88223
0.44223223.32223223223.44223223.68223
0.46232.82242.48245245244.16224226.52245
0.48246.92247247247247247247247
0.5247.5248248248248248248248
0.52257.16259.24261261259.08257258.76261
0.54267.38272272272272272272272
0.56272.12272.68273273272.56272272.32273
0.58274.32275.72275275275.24275277.28275
0.6280.2286.8289289284.6278280.2289
0.62291.22294.16292292292.72292295.84292
0.64298.56299.84300300299.28298298.16300
0.66306.56314.72308308310.24308315.28308
0.68322.72324324324323.36322324324
0.7324325.2324324324.4324324.8326
0.72329.96336.28335335332.48326341.72335
0.74342.84345.16343343343.72343343.84346
0.76376.16404404404390.08404404404
0.78404404404404404404404404
0.8428.6452.6445445436.8445456.4445
0.82464.42466.88467467464.96464464.12467
0.84481.28501488488484.64488500513
0.86514.1521.36518518514.8513556.64518
0.88549.92592560560554.96560578610
0.9610.6615.2612612610.8610624.8612
0.92625.44655.36628628626.72628636.64664
0.94668.94677.96677677669.72664679.04677
0.96679.76707.28680680679.88680683.72711
0.98778.62874.28858858781.56711878.72858

\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 & 44.4 & 44.6 & 49 & 49 & 54.2 & 49 & 43.4 & 49 \tabularnewline
0.04 & 60.12 & 60.68 & 73 & 73 & 73.08 & 59 & 71.32 & 59 \tabularnewline
0.06 & 74.24 & 74.36 & 75 & 75 & 76.68 & 75 & 73.64 & 75 \tabularnewline
0.08 & 78.16 & 78.24 & 79 & 79 & 79.48 & 78 & 78.76 & 78 \tabularnewline
0.1 & 83.2 & 83.8 & 85 & 85 & 88 & 85 & 80.2 & 85 \tabularnewline
0.12 & 90.24 & 90.36 & 91 & 91 & 91.6 & 90 & 90.64 & 90 \tabularnewline
0.14 & 94.9 & 95.6 & 96 & 96 & 97.92 & 96 & 91.4 & 96 \tabularnewline
0.16 & 100.6 & 101.4 & 104 & 104 & 104.48 & 99 & 101.6 & 99 \tabularnewline
0.18 & 106.58 & 108.12 & 107 & 107 & 126.04 & 107 & 133.88 & 107 \tabularnewline
0.2 & 137.4 & 138.6 & 141 & 141 & 141.8 & 135 & 137.4 & 141 \tabularnewline
0.22 & 144.76 & 145.48 & 145 & 145 & 147.16 & 145 & 147.52 & 145 \tabularnewline
0.24 & 155.68 & 159.52 & 164 & 164 & 164.72 & 148 & 152.48 & 164 \tabularnewline
0.26 & 167.04 & 167.56 & 169 & 169 & 168.52 & 167 & 168.44 & 167 \tabularnewline
0.28 & 169 & 169 & 169 & 169 & 169 & 169 & 169 & 169 \tabularnewline
0.3 & 170.7 & 175.8 & 186 & 186 & 182.6 & 169 & 179.2 & 169 \tabularnewline
0.32 & 187.28 & 187.92 & 188 & 188 & 188.32 & 188 & 186.08 & 188 \tabularnewline
0.34 & 190.26 & 192.64 & 196 & 196 & 194.88 & 189 & 192.36 & 196 \tabularnewline
0.36 & 198.88 & 200.24 & 200 & 200 & 201.08 & 200 & 202.76 & 200 \tabularnewline
0.38 & 204.82 & 207.48 & 210 & 210 & 209.16 & 203 & 205.52 & 210 \tabularnewline
0.4 & 210 & 210.2 & 210 & 210 & 210.4 & 210 & 210.8 & 210 \tabularnewline
0.42 & 215.08 & 220.12 & 223 & 223 & 222.04 & 211 & 213.88 & 223 \tabularnewline
0.44 & 223 & 223.32 & 223 & 223 & 223.44 & 223 & 223.68 & 223 \tabularnewline
0.46 & 232.82 & 242.48 & 245 & 245 & 244.16 & 224 & 226.52 & 245 \tabularnewline
0.48 & 246.92 & 247 & 247 & 247 & 247 & 247 & 247 & 247 \tabularnewline
0.5 & 247.5 & 248 & 248 & 248 & 248 & 248 & 248 & 248 \tabularnewline
0.52 & 257.16 & 259.24 & 261 & 261 & 259.08 & 257 & 258.76 & 261 \tabularnewline
0.54 & 267.38 & 272 & 272 & 272 & 272 & 272 & 272 & 272 \tabularnewline
0.56 & 272.12 & 272.68 & 273 & 273 & 272.56 & 272 & 272.32 & 273 \tabularnewline
0.58 & 274.32 & 275.72 & 275 & 275 & 275.24 & 275 & 277.28 & 275 \tabularnewline
0.6 & 280.2 & 286.8 & 289 & 289 & 284.6 & 278 & 280.2 & 289 \tabularnewline
0.62 & 291.22 & 294.16 & 292 & 292 & 292.72 & 292 & 295.84 & 292 \tabularnewline
0.64 & 298.56 & 299.84 & 300 & 300 & 299.28 & 298 & 298.16 & 300 \tabularnewline
0.66 & 306.56 & 314.72 & 308 & 308 & 310.24 & 308 & 315.28 & 308 \tabularnewline
0.68 & 322.72 & 324 & 324 & 324 & 323.36 & 322 & 324 & 324 \tabularnewline
0.7 & 324 & 325.2 & 324 & 324 & 324.4 & 324 & 324.8 & 326 \tabularnewline
0.72 & 329.96 & 336.28 & 335 & 335 & 332.48 & 326 & 341.72 & 335 \tabularnewline
0.74 & 342.84 & 345.16 & 343 & 343 & 343.72 & 343 & 343.84 & 346 \tabularnewline
0.76 & 376.16 & 404 & 404 & 404 & 390.08 & 404 & 404 & 404 \tabularnewline
0.78 & 404 & 404 & 404 & 404 & 404 & 404 & 404 & 404 \tabularnewline
0.8 & 428.6 & 452.6 & 445 & 445 & 436.8 & 445 & 456.4 & 445 \tabularnewline
0.82 & 464.42 & 466.88 & 467 & 467 & 464.96 & 464 & 464.12 & 467 \tabularnewline
0.84 & 481.28 & 501 & 488 & 488 & 484.64 & 488 & 500 & 513 \tabularnewline
0.86 & 514.1 & 521.36 & 518 & 518 & 514.8 & 513 & 556.64 & 518 \tabularnewline
0.88 & 549.92 & 592 & 560 & 560 & 554.96 & 560 & 578 & 610 \tabularnewline
0.9 & 610.6 & 615.2 & 612 & 612 & 610.8 & 610 & 624.8 & 612 \tabularnewline
0.92 & 625.44 & 655.36 & 628 & 628 & 626.72 & 628 & 636.64 & 664 \tabularnewline
0.94 & 668.94 & 677.96 & 677 & 677 & 669.72 & 664 & 679.04 & 677 \tabularnewline
0.96 & 679.76 & 707.28 & 680 & 680 & 679.88 & 680 & 683.72 & 711 \tabularnewline
0.98 & 778.62 & 874.28 & 858 & 858 & 781.56 & 711 & 878.72 & 858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=73936&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]44.4[/C][C]44.6[/C][C]49[/C][C]49[/C][C]54.2[/C][C]49[/C][C]43.4[/C][C]49[/C][/ROW]
[ROW][C]0.04[/C][C]60.12[/C][C]60.68[/C][C]73[/C][C]73[/C][C]73.08[/C][C]59[/C][C]71.32[/C][C]59[/C][/ROW]
[ROW][C]0.06[/C][C]74.24[/C][C]74.36[/C][C]75[/C][C]75[/C][C]76.68[/C][C]75[/C][C]73.64[/C][C]75[/C][/ROW]
[ROW][C]0.08[/C][C]78.16[/C][C]78.24[/C][C]79[/C][C]79[/C][C]79.48[/C][C]78[/C][C]78.76[/C][C]78[/C][/ROW]
[ROW][C]0.1[/C][C]83.2[/C][C]83.8[/C][C]85[/C][C]85[/C][C]88[/C][C]85[/C][C]80.2[/C][C]85[/C][/ROW]
[ROW][C]0.12[/C][C]90.24[/C][C]90.36[/C][C]91[/C][C]91[/C][C]91.6[/C][C]90[/C][C]90.64[/C][C]90[/C][/ROW]
[ROW][C]0.14[/C][C]94.9[/C][C]95.6[/C][C]96[/C][C]96[/C][C]97.92[/C][C]96[/C][C]91.4[/C][C]96[/C][/ROW]
[ROW][C]0.16[/C][C]100.6[/C][C]101.4[/C][C]104[/C][C]104[/C][C]104.48[/C][C]99[/C][C]101.6[/C][C]99[/C][/ROW]
[ROW][C]0.18[/C][C]106.58[/C][C]108.12[/C][C]107[/C][C]107[/C][C]126.04[/C][C]107[/C][C]133.88[/C][C]107[/C][/ROW]
[ROW][C]0.2[/C][C]137.4[/C][C]138.6[/C][C]141[/C][C]141[/C][C]141.8[/C][C]135[/C][C]137.4[/C][C]141[/C][/ROW]
[ROW][C]0.22[/C][C]144.76[/C][C]145.48[/C][C]145[/C][C]145[/C][C]147.16[/C][C]145[/C][C]147.52[/C][C]145[/C][/ROW]
[ROW][C]0.24[/C][C]155.68[/C][C]159.52[/C][C]164[/C][C]164[/C][C]164.72[/C][C]148[/C][C]152.48[/C][C]164[/C][/ROW]
[ROW][C]0.26[/C][C]167.04[/C][C]167.56[/C][C]169[/C][C]169[/C][C]168.52[/C][C]167[/C][C]168.44[/C][C]167[/C][/ROW]
[ROW][C]0.28[/C][C]169[/C][C]169[/C][C]169[/C][C]169[/C][C]169[/C][C]169[/C][C]169[/C][C]169[/C][/ROW]
[ROW][C]0.3[/C][C]170.7[/C][C]175.8[/C][C]186[/C][C]186[/C][C]182.6[/C][C]169[/C][C]179.2[/C][C]169[/C][/ROW]
[ROW][C]0.32[/C][C]187.28[/C][C]187.92[/C][C]188[/C][C]188[/C][C]188.32[/C][C]188[/C][C]186.08[/C][C]188[/C][/ROW]
[ROW][C]0.34[/C][C]190.26[/C][C]192.64[/C][C]196[/C][C]196[/C][C]194.88[/C][C]189[/C][C]192.36[/C][C]196[/C][/ROW]
[ROW][C]0.36[/C][C]198.88[/C][C]200.24[/C][C]200[/C][C]200[/C][C]201.08[/C][C]200[/C][C]202.76[/C][C]200[/C][/ROW]
[ROW][C]0.38[/C][C]204.82[/C][C]207.48[/C][C]210[/C][C]210[/C][C]209.16[/C][C]203[/C][C]205.52[/C][C]210[/C][/ROW]
[ROW][C]0.4[/C][C]210[/C][C]210.2[/C][C]210[/C][C]210[/C][C]210.4[/C][C]210[/C][C]210.8[/C][C]210[/C][/ROW]
[ROW][C]0.42[/C][C]215.08[/C][C]220.12[/C][C]223[/C][C]223[/C][C]222.04[/C][C]211[/C][C]213.88[/C][C]223[/C][/ROW]
[ROW][C]0.44[/C][C]223[/C][C]223.32[/C][C]223[/C][C]223[/C][C]223.44[/C][C]223[/C][C]223.68[/C][C]223[/C][/ROW]
[ROW][C]0.46[/C][C]232.82[/C][C]242.48[/C][C]245[/C][C]245[/C][C]244.16[/C][C]224[/C][C]226.52[/C][C]245[/C][/ROW]
[ROW][C]0.48[/C][C]246.92[/C][C]247[/C][C]247[/C][C]247[/C][C]247[/C][C]247[/C][C]247[/C][C]247[/C][/ROW]
[ROW][C]0.5[/C][C]247.5[/C][C]248[/C][C]248[/C][C]248[/C][C]248[/C][C]248[/C][C]248[/C][C]248[/C][/ROW]
[ROW][C]0.52[/C][C]257.16[/C][C]259.24[/C][C]261[/C][C]261[/C][C]259.08[/C][C]257[/C][C]258.76[/C][C]261[/C][/ROW]
[ROW][C]0.54[/C][C]267.38[/C][C]272[/C][C]272[/C][C]272[/C][C]272[/C][C]272[/C][C]272[/C][C]272[/C][/ROW]
[ROW][C]0.56[/C][C]272.12[/C][C]272.68[/C][C]273[/C][C]273[/C][C]272.56[/C][C]272[/C][C]272.32[/C][C]273[/C][/ROW]
[ROW][C]0.58[/C][C]274.32[/C][C]275.72[/C][C]275[/C][C]275[/C][C]275.24[/C][C]275[/C][C]277.28[/C][C]275[/C][/ROW]
[ROW][C]0.6[/C][C]280.2[/C][C]286.8[/C][C]289[/C][C]289[/C][C]284.6[/C][C]278[/C][C]280.2[/C][C]289[/C][/ROW]
[ROW][C]0.62[/C][C]291.22[/C][C]294.16[/C][C]292[/C][C]292[/C][C]292.72[/C][C]292[/C][C]295.84[/C][C]292[/C][/ROW]
[ROW][C]0.64[/C][C]298.56[/C][C]299.84[/C][C]300[/C][C]300[/C][C]299.28[/C][C]298[/C][C]298.16[/C][C]300[/C][/ROW]
[ROW][C]0.66[/C][C]306.56[/C][C]314.72[/C][C]308[/C][C]308[/C][C]310.24[/C][C]308[/C][C]315.28[/C][C]308[/C][/ROW]
[ROW][C]0.68[/C][C]322.72[/C][C]324[/C][C]324[/C][C]324[/C][C]323.36[/C][C]322[/C][C]324[/C][C]324[/C][/ROW]
[ROW][C]0.7[/C][C]324[/C][C]325.2[/C][C]324[/C][C]324[/C][C]324.4[/C][C]324[/C][C]324.8[/C][C]326[/C][/ROW]
[ROW][C]0.72[/C][C]329.96[/C][C]336.28[/C][C]335[/C][C]335[/C][C]332.48[/C][C]326[/C][C]341.72[/C][C]335[/C][/ROW]
[ROW][C]0.74[/C][C]342.84[/C][C]345.16[/C][C]343[/C][C]343[/C][C]343.72[/C][C]343[/C][C]343.84[/C][C]346[/C][/ROW]
[ROW][C]0.76[/C][C]376.16[/C][C]404[/C][C]404[/C][C]404[/C][C]390.08[/C][C]404[/C][C]404[/C][C]404[/C][/ROW]
[ROW][C]0.78[/C][C]404[/C][C]404[/C][C]404[/C][C]404[/C][C]404[/C][C]404[/C][C]404[/C][C]404[/C][/ROW]
[ROW][C]0.8[/C][C]428.6[/C][C]452.6[/C][C]445[/C][C]445[/C][C]436.8[/C][C]445[/C][C]456.4[/C][C]445[/C][/ROW]
[ROW][C]0.82[/C][C]464.42[/C][C]466.88[/C][C]467[/C][C]467[/C][C]464.96[/C][C]464[/C][C]464.12[/C][C]467[/C][/ROW]
[ROW][C]0.84[/C][C]481.28[/C][C]501[/C][C]488[/C][C]488[/C][C]484.64[/C][C]488[/C][C]500[/C][C]513[/C][/ROW]
[ROW][C]0.86[/C][C]514.1[/C][C]521.36[/C][C]518[/C][C]518[/C][C]514.8[/C][C]513[/C][C]556.64[/C][C]518[/C][/ROW]
[ROW][C]0.88[/C][C]549.92[/C][C]592[/C][C]560[/C][C]560[/C][C]554.96[/C][C]560[/C][C]578[/C][C]610[/C][/ROW]
[ROW][C]0.9[/C][C]610.6[/C][C]615.2[/C][C]612[/C][C]612[/C][C]610.8[/C][C]610[/C][C]624.8[/C][C]612[/C][/ROW]
[ROW][C]0.92[/C][C]625.44[/C][C]655.36[/C][C]628[/C][C]628[/C][C]626.72[/C][C]628[/C][C]636.64[/C][C]664[/C][/ROW]
[ROW][C]0.94[/C][C]668.94[/C][C]677.96[/C][C]677[/C][C]677[/C][C]669.72[/C][C]664[/C][C]679.04[/C][C]677[/C][/ROW]
[ROW][C]0.96[/C][C]679.76[/C][C]707.28[/C][C]680[/C][C]680[/C][C]679.88[/C][C]680[/C][C]683.72[/C][C]711[/C][/ROW]
[ROW][C]0.98[/C][C]778.62[/C][C]874.28[/C][C]858[/C][C]858[/C][C]781.56[/C][C]711[/C][C]878.72[/C][C]858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=73936&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=73936&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)
0.0244.444.6494954.24943.449
0.0460.1260.68737373.085971.3259
0.0674.2474.36757576.687573.6475
0.0878.1678.24797979.487878.7678
0.183.283.88585888580.285
0.1290.2490.36919191.69090.6490
0.1494.995.6969697.929691.496
0.16100.6101.4104104104.4899101.699
0.18106.58108.12107107126.04107133.88107
0.2137.4138.6141141141.8135137.4141
0.22144.76145.48145145147.16145147.52145
0.24155.68159.52164164164.72148152.48164
0.26167.04167.56169169168.52167168.44167
0.28169169169169169169169169
0.3170.7175.8186186182.6169179.2169
0.32187.28187.92188188188.32188186.08188
0.34190.26192.64196196194.88189192.36196
0.36198.88200.24200200201.08200202.76200
0.38204.82207.48210210209.16203205.52210
0.4210210.2210210210.4210210.8210
0.42215.08220.12223223222.04211213.88223
0.44223223.32223223223.44223223.68223
0.46232.82242.48245245244.16224226.52245
0.48246.92247247247247247247247
0.5247.5248248248248248248248
0.52257.16259.24261261259.08257258.76261
0.54267.38272272272272272272272
0.56272.12272.68273273272.56272272.32273
0.58274.32275.72275275275.24275277.28275
0.6280.2286.8289289284.6278280.2289
0.62291.22294.16292292292.72292295.84292
0.64298.56299.84300300299.28298298.16300
0.66306.56314.72308308310.24308315.28308
0.68322.72324324324323.36322324324
0.7324325.2324324324.4324324.8326
0.72329.96336.28335335332.48326341.72335
0.74342.84345.16343343343.72343343.84346
0.76376.16404404404390.08404404404
0.78404404404404404404404404
0.8428.6452.6445445436.8445456.4445
0.82464.42466.88467467464.96464464.12467
0.84481.28501488488484.64488500513
0.86514.1521.36518518514.8513556.64518
0.88549.92592560560554.96560578610
0.9610.6615.2612612610.8610624.8612
0.92625.44655.36628628626.72628636.64664
0.94668.94677.96677677669.72664679.04677
0.96679.76707.28680680679.88680683.72711
0.98778.62874.28858858781.56711878.72858



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')