Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationMon, 20 Oct 2008 16:52:58 -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/21/t1224543211avidq7fwz4pekzs.htm/, Retrieved Sun, 19 May 2024 21:35:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18284, Retrieved Sun, 19 May 2024 21:35:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Percentiles] [Percentiles: bouw...] [2008-10-20 22:52:58] [7957bb37a64ed417bbed8444b0b0ea8a] [Current]
Feedback Forum
2008-10-27 18:16:37 [Evelyn Ongena] [reply
Je hebt enkel de link in het document vervat, zonder enige uitleg of conclusie wat het moeilijk maakt je hierop te beoordelen.

Post a new message
Dataseries X:
572
582
574
461
576
460
455
444
488
513
468
488
536
486
460
376
503
369
353
359
400
374
430
433
418
438
389
368
386
261
294
263
293
303
326
314
332
347
290
340
371
340
376
322
364
379
343
358
433
344
357
385
392
308
294
300
302
400
392
373
379
303
324
353
392
327
376
329
359
413
338
421
390
370
366
405
418
346
349
326
318
379
336
372
420
425
422
396
457
313
334
384
342
385
435
405
454




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18284&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18284&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18284&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'George Udny Yule' @ 72.249.76.132







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)
0.02262.88262.92263263287.84263261.08263
0.04292.64292.76293293293.84293290.24293
0.06294294294294298.56294294294
0.08301.52301.68302302302.68302300.32302
0.1303303303303306303303303
0.12311.2311.8313313313.52313309.2313
0.14316.32316.88318318319.76318315.12318
0.16323.04323.36324324324.72324322.64324
0.18326326326326326.28326326326
0.2327.8328.2329329329.6327327.8329
0.22332.68333.12334334334.24332332.88334
0.24336.56337.04338338338.08336336.96338
0.26340340340340340340340340
0.28342.16342.44343343342.88342342.56342
0.3344.2344.8346346345.6344345.2344
0.32347.08347.72349349348.44347348.28347
0.34352.92353353353353353353353
0.36356.68357.28357357357.56357357.72357
0.38358.86359359359359359359359
0.4363364.4364364364.8364365.6364
0.42367.48368.16368368368.32368368.84368
0.44369.68370.12370370370.24370370.88370
0.46371.62372.08372372372.16372372.92372
0.48373.56374.08374374374.16374375.92374
0.5376376376376376376376376
0.52377.32378.88379379378.76376376.12379
0.54379379379379379379379379
0.56384.32384.88385385384.76384384.12385
0.58385.26385.84386386385.68385385.16386
0.6389.2389.8390390389.6389389.2390
0.62392392392392392392392392
0.64392.32394.88396396393.76392393.12396
0.66400400400400400400400400
0.68404.8405405405405405405405
0.7412.2416413413414413415418
0.72418419.12418418418.24418418.88420
0.74420.78421.52421421421.04421421.48422
0.76424.16427.4425425424.88425427.6425
0.78431.98433433433432.64433433433
0.8434.2436.2435435434.6435436.8435
0.82441.24447.6444444442.32444450.4444
0.84454.48455.64455455454.64454456.36455
0.86458.26460460460458.68457460460
0.88460.36462.68461461460.48460466.32461
0.9473.4486.4486486475.2468487.6486
0.92488490.4488488488488500.6488
0.94504.8515.76513513505.4503533.24513
0.96540.32572.16572572541.76536573.84572
0.98574.12576.24576576574.16574581.76576

\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 & 262.88 & 262.92 & 263 & 263 & 287.84 & 263 & 261.08 & 263 \tabularnewline
0.04 & 292.64 & 292.76 & 293 & 293 & 293.84 & 293 & 290.24 & 293 \tabularnewline
0.06 & 294 & 294 & 294 & 294 & 298.56 & 294 & 294 & 294 \tabularnewline
0.08 & 301.52 & 301.68 & 302 & 302 & 302.68 & 302 & 300.32 & 302 \tabularnewline
0.1 & 303 & 303 & 303 & 303 & 306 & 303 & 303 & 303 \tabularnewline
0.12 & 311.2 & 311.8 & 313 & 313 & 313.52 & 313 & 309.2 & 313 \tabularnewline
0.14 & 316.32 & 316.88 & 318 & 318 & 319.76 & 318 & 315.12 & 318 \tabularnewline
0.16 & 323.04 & 323.36 & 324 & 324 & 324.72 & 324 & 322.64 & 324 \tabularnewline
0.18 & 326 & 326 & 326 & 326 & 326.28 & 326 & 326 & 326 \tabularnewline
0.2 & 327.8 & 328.2 & 329 & 329 & 329.6 & 327 & 327.8 & 329 \tabularnewline
0.22 & 332.68 & 333.12 & 334 & 334 & 334.24 & 332 & 332.88 & 334 \tabularnewline
0.24 & 336.56 & 337.04 & 338 & 338 & 338.08 & 336 & 336.96 & 338 \tabularnewline
0.26 & 340 & 340 & 340 & 340 & 340 & 340 & 340 & 340 \tabularnewline
0.28 & 342.16 & 342.44 & 343 & 343 & 342.88 & 342 & 342.56 & 342 \tabularnewline
0.3 & 344.2 & 344.8 & 346 & 346 & 345.6 & 344 & 345.2 & 344 \tabularnewline
0.32 & 347.08 & 347.72 & 349 & 349 & 348.44 & 347 & 348.28 & 347 \tabularnewline
0.34 & 352.92 & 353 & 353 & 353 & 353 & 353 & 353 & 353 \tabularnewline
0.36 & 356.68 & 357.28 & 357 & 357 & 357.56 & 357 & 357.72 & 357 \tabularnewline
0.38 & 358.86 & 359 & 359 & 359 & 359 & 359 & 359 & 359 \tabularnewline
0.4 & 363 & 364.4 & 364 & 364 & 364.8 & 364 & 365.6 & 364 \tabularnewline
0.42 & 367.48 & 368.16 & 368 & 368 & 368.32 & 368 & 368.84 & 368 \tabularnewline
0.44 & 369.68 & 370.12 & 370 & 370 & 370.24 & 370 & 370.88 & 370 \tabularnewline
0.46 & 371.62 & 372.08 & 372 & 372 & 372.16 & 372 & 372.92 & 372 \tabularnewline
0.48 & 373.56 & 374.08 & 374 & 374 & 374.16 & 374 & 375.92 & 374 \tabularnewline
0.5 & 376 & 376 & 376 & 376 & 376 & 376 & 376 & 376 \tabularnewline
0.52 & 377.32 & 378.88 & 379 & 379 & 378.76 & 376 & 376.12 & 379 \tabularnewline
0.54 & 379 & 379 & 379 & 379 & 379 & 379 & 379 & 379 \tabularnewline
0.56 & 384.32 & 384.88 & 385 & 385 & 384.76 & 384 & 384.12 & 385 \tabularnewline
0.58 & 385.26 & 385.84 & 386 & 386 & 385.68 & 385 & 385.16 & 386 \tabularnewline
0.6 & 389.2 & 389.8 & 390 & 390 & 389.6 & 389 & 389.2 & 390 \tabularnewline
0.62 & 392 & 392 & 392 & 392 & 392 & 392 & 392 & 392 \tabularnewline
0.64 & 392.32 & 394.88 & 396 & 396 & 393.76 & 392 & 393.12 & 396 \tabularnewline
0.66 & 400 & 400 & 400 & 400 & 400 & 400 & 400 & 400 \tabularnewline
0.68 & 404.8 & 405 & 405 & 405 & 405 & 405 & 405 & 405 \tabularnewline
0.7 & 412.2 & 416 & 413 & 413 & 414 & 413 & 415 & 418 \tabularnewline
0.72 & 418 & 419.12 & 418 & 418 & 418.24 & 418 & 418.88 & 420 \tabularnewline
0.74 & 420.78 & 421.52 & 421 & 421 & 421.04 & 421 & 421.48 & 422 \tabularnewline
0.76 & 424.16 & 427.4 & 425 & 425 & 424.88 & 425 & 427.6 & 425 \tabularnewline
0.78 & 431.98 & 433 & 433 & 433 & 432.64 & 433 & 433 & 433 \tabularnewline
0.8 & 434.2 & 436.2 & 435 & 435 & 434.6 & 435 & 436.8 & 435 \tabularnewline
0.82 & 441.24 & 447.6 & 444 & 444 & 442.32 & 444 & 450.4 & 444 \tabularnewline
0.84 & 454.48 & 455.64 & 455 & 455 & 454.64 & 454 & 456.36 & 455 \tabularnewline
0.86 & 458.26 & 460 & 460 & 460 & 458.68 & 457 & 460 & 460 \tabularnewline
0.88 & 460.36 & 462.68 & 461 & 461 & 460.48 & 460 & 466.32 & 461 \tabularnewline
0.9 & 473.4 & 486.4 & 486 & 486 & 475.2 & 468 & 487.6 & 486 \tabularnewline
0.92 & 488 & 490.4 & 488 & 488 & 488 & 488 & 500.6 & 488 \tabularnewline
0.94 & 504.8 & 515.76 & 513 & 513 & 505.4 & 503 & 533.24 & 513 \tabularnewline
0.96 & 540.32 & 572.16 & 572 & 572 & 541.76 & 536 & 573.84 & 572 \tabularnewline
0.98 & 574.12 & 576.24 & 576 & 576 & 574.16 & 574 & 581.76 & 576 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18284&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]262.88[/C][C]262.92[/C][C]263[/C][C]263[/C][C]287.84[/C][C]263[/C][C]261.08[/C][C]263[/C][/ROW]
[ROW][C]0.04[/C][C]292.64[/C][C]292.76[/C][C]293[/C][C]293[/C][C]293.84[/C][C]293[/C][C]290.24[/C][C]293[/C][/ROW]
[ROW][C]0.06[/C][C]294[/C][C]294[/C][C]294[/C][C]294[/C][C]298.56[/C][C]294[/C][C]294[/C][C]294[/C][/ROW]
[ROW][C]0.08[/C][C]301.52[/C][C]301.68[/C][C]302[/C][C]302[/C][C]302.68[/C][C]302[/C][C]300.32[/C][C]302[/C][/ROW]
[ROW][C]0.1[/C][C]303[/C][C]303[/C][C]303[/C][C]303[/C][C]306[/C][C]303[/C][C]303[/C][C]303[/C][/ROW]
[ROW][C]0.12[/C][C]311.2[/C][C]311.8[/C][C]313[/C][C]313[/C][C]313.52[/C][C]313[/C][C]309.2[/C][C]313[/C][/ROW]
[ROW][C]0.14[/C][C]316.32[/C][C]316.88[/C][C]318[/C][C]318[/C][C]319.76[/C][C]318[/C][C]315.12[/C][C]318[/C][/ROW]
[ROW][C]0.16[/C][C]323.04[/C][C]323.36[/C][C]324[/C][C]324[/C][C]324.72[/C][C]324[/C][C]322.64[/C][C]324[/C][/ROW]
[ROW][C]0.18[/C][C]326[/C][C]326[/C][C]326[/C][C]326[/C][C]326.28[/C][C]326[/C][C]326[/C][C]326[/C][/ROW]
[ROW][C]0.2[/C][C]327.8[/C][C]328.2[/C][C]329[/C][C]329[/C][C]329.6[/C][C]327[/C][C]327.8[/C][C]329[/C][/ROW]
[ROW][C]0.22[/C][C]332.68[/C][C]333.12[/C][C]334[/C][C]334[/C][C]334.24[/C][C]332[/C][C]332.88[/C][C]334[/C][/ROW]
[ROW][C]0.24[/C][C]336.56[/C][C]337.04[/C][C]338[/C][C]338[/C][C]338.08[/C][C]336[/C][C]336.96[/C][C]338[/C][/ROW]
[ROW][C]0.26[/C][C]340[/C][C]340[/C][C]340[/C][C]340[/C][C]340[/C][C]340[/C][C]340[/C][C]340[/C][/ROW]
[ROW][C]0.28[/C][C]342.16[/C][C]342.44[/C][C]343[/C][C]343[/C][C]342.88[/C][C]342[/C][C]342.56[/C][C]342[/C][/ROW]
[ROW][C]0.3[/C][C]344.2[/C][C]344.8[/C][C]346[/C][C]346[/C][C]345.6[/C][C]344[/C][C]345.2[/C][C]344[/C][/ROW]
[ROW][C]0.32[/C][C]347.08[/C][C]347.72[/C][C]349[/C][C]349[/C][C]348.44[/C][C]347[/C][C]348.28[/C][C]347[/C][/ROW]
[ROW][C]0.34[/C][C]352.92[/C][C]353[/C][C]353[/C][C]353[/C][C]353[/C][C]353[/C][C]353[/C][C]353[/C][/ROW]
[ROW][C]0.36[/C][C]356.68[/C][C]357.28[/C][C]357[/C][C]357[/C][C]357.56[/C][C]357[/C][C]357.72[/C][C]357[/C][/ROW]
[ROW][C]0.38[/C][C]358.86[/C][C]359[/C][C]359[/C][C]359[/C][C]359[/C][C]359[/C][C]359[/C][C]359[/C][/ROW]
[ROW][C]0.4[/C][C]363[/C][C]364.4[/C][C]364[/C][C]364[/C][C]364.8[/C][C]364[/C][C]365.6[/C][C]364[/C][/ROW]
[ROW][C]0.42[/C][C]367.48[/C][C]368.16[/C][C]368[/C][C]368[/C][C]368.32[/C][C]368[/C][C]368.84[/C][C]368[/C][/ROW]
[ROW][C]0.44[/C][C]369.68[/C][C]370.12[/C][C]370[/C][C]370[/C][C]370.24[/C][C]370[/C][C]370.88[/C][C]370[/C][/ROW]
[ROW][C]0.46[/C][C]371.62[/C][C]372.08[/C][C]372[/C][C]372[/C][C]372.16[/C][C]372[/C][C]372.92[/C][C]372[/C][/ROW]
[ROW][C]0.48[/C][C]373.56[/C][C]374.08[/C][C]374[/C][C]374[/C][C]374.16[/C][C]374[/C][C]375.92[/C][C]374[/C][/ROW]
[ROW][C]0.5[/C][C]376[/C][C]376[/C][C]376[/C][C]376[/C][C]376[/C][C]376[/C][C]376[/C][C]376[/C][/ROW]
[ROW][C]0.52[/C][C]377.32[/C][C]378.88[/C][C]379[/C][C]379[/C][C]378.76[/C][C]376[/C][C]376.12[/C][C]379[/C][/ROW]
[ROW][C]0.54[/C][C]379[/C][C]379[/C][C]379[/C][C]379[/C][C]379[/C][C]379[/C][C]379[/C][C]379[/C][/ROW]
[ROW][C]0.56[/C][C]384.32[/C][C]384.88[/C][C]385[/C][C]385[/C][C]384.76[/C][C]384[/C][C]384.12[/C][C]385[/C][/ROW]
[ROW][C]0.58[/C][C]385.26[/C][C]385.84[/C][C]386[/C][C]386[/C][C]385.68[/C][C]385[/C][C]385.16[/C][C]386[/C][/ROW]
[ROW][C]0.6[/C][C]389.2[/C][C]389.8[/C][C]390[/C][C]390[/C][C]389.6[/C][C]389[/C][C]389.2[/C][C]390[/C][/ROW]
[ROW][C]0.62[/C][C]392[/C][C]392[/C][C]392[/C][C]392[/C][C]392[/C][C]392[/C][C]392[/C][C]392[/C][/ROW]
[ROW][C]0.64[/C][C]392.32[/C][C]394.88[/C][C]396[/C][C]396[/C][C]393.76[/C][C]392[/C][C]393.12[/C][C]396[/C][/ROW]
[ROW][C]0.66[/C][C]400[/C][C]400[/C][C]400[/C][C]400[/C][C]400[/C][C]400[/C][C]400[/C][C]400[/C][/ROW]
[ROW][C]0.68[/C][C]404.8[/C][C]405[/C][C]405[/C][C]405[/C][C]405[/C][C]405[/C][C]405[/C][C]405[/C][/ROW]
[ROW][C]0.7[/C][C]412.2[/C][C]416[/C][C]413[/C][C]413[/C][C]414[/C][C]413[/C][C]415[/C][C]418[/C][/ROW]
[ROW][C]0.72[/C][C]418[/C][C]419.12[/C][C]418[/C][C]418[/C][C]418.24[/C][C]418[/C][C]418.88[/C][C]420[/C][/ROW]
[ROW][C]0.74[/C][C]420.78[/C][C]421.52[/C][C]421[/C][C]421[/C][C]421.04[/C][C]421[/C][C]421.48[/C][C]422[/C][/ROW]
[ROW][C]0.76[/C][C]424.16[/C][C]427.4[/C][C]425[/C][C]425[/C][C]424.88[/C][C]425[/C][C]427.6[/C][C]425[/C][/ROW]
[ROW][C]0.78[/C][C]431.98[/C][C]433[/C][C]433[/C][C]433[/C][C]432.64[/C][C]433[/C][C]433[/C][C]433[/C][/ROW]
[ROW][C]0.8[/C][C]434.2[/C][C]436.2[/C][C]435[/C][C]435[/C][C]434.6[/C][C]435[/C][C]436.8[/C][C]435[/C][/ROW]
[ROW][C]0.82[/C][C]441.24[/C][C]447.6[/C][C]444[/C][C]444[/C][C]442.32[/C][C]444[/C][C]450.4[/C][C]444[/C][/ROW]
[ROW][C]0.84[/C][C]454.48[/C][C]455.64[/C][C]455[/C][C]455[/C][C]454.64[/C][C]454[/C][C]456.36[/C][C]455[/C][/ROW]
[ROW][C]0.86[/C][C]458.26[/C][C]460[/C][C]460[/C][C]460[/C][C]458.68[/C][C]457[/C][C]460[/C][C]460[/C][/ROW]
[ROW][C]0.88[/C][C]460.36[/C][C]462.68[/C][C]461[/C][C]461[/C][C]460.48[/C][C]460[/C][C]466.32[/C][C]461[/C][/ROW]
[ROW][C]0.9[/C][C]473.4[/C][C]486.4[/C][C]486[/C][C]486[/C][C]475.2[/C][C]468[/C][C]487.6[/C][C]486[/C][/ROW]
[ROW][C]0.92[/C][C]488[/C][C]490.4[/C][C]488[/C][C]488[/C][C]488[/C][C]488[/C][C]500.6[/C][C]488[/C][/ROW]
[ROW][C]0.94[/C][C]504.8[/C][C]515.76[/C][C]513[/C][C]513[/C][C]505.4[/C][C]503[/C][C]533.24[/C][C]513[/C][/ROW]
[ROW][C]0.96[/C][C]540.32[/C][C]572.16[/C][C]572[/C][C]572[/C][C]541.76[/C][C]536[/C][C]573.84[/C][C]572[/C][/ROW]
[ROW][C]0.98[/C][C]574.12[/C][C]576.24[/C][C]576[/C][C]576[/C][C]574.16[/C][C]574[/C][C]581.76[/C][C]576[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18284&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18284&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)
0.02262.88262.92263263287.84263261.08263
0.04292.64292.76293293293.84293290.24293
0.06294294294294298.56294294294
0.08301.52301.68302302302.68302300.32302
0.1303303303303306303303303
0.12311.2311.8313313313.52313309.2313
0.14316.32316.88318318319.76318315.12318
0.16323.04323.36324324324.72324322.64324
0.18326326326326326.28326326326
0.2327.8328.2329329329.6327327.8329
0.22332.68333.12334334334.24332332.88334
0.24336.56337.04338338338.08336336.96338
0.26340340340340340340340340
0.28342.16342.44343343342.88342342.56342
0.3344.2344.8346346345.6344345.2344
0.32347.08347.72349349348.44347348.28347
0.34352.92353353353353353353353
0.36356.68357.28357357357.56357357.72357
0.38358.86359359359359359359359
0.4363364.4364364364.8364365.6364
0.42367.48368.16368368368.32368368.84368
0.44369.68370.12370370370.24370370.88370
0.46371.62372.08372372372.16372372.92372
0.48373.56374.08374374374.16374375.92374
0.5376376376376376376376376
0.52377.32378.88379379378.76376376.12379
0.54379379379379379379379379
0.56384.32384.88385385384.76384384.12385
0.58385.26385.84386386385.68385385.16386
0.6389.2389.8390390389.6389389.2390
0.62392392392392392392392392
0.64392.32394.88396396393.76392393.12396
0.66400400400400400400400400
0.68404.8405405405405405405405
0.7412.2416413413414413415418
0.72418419.12418418418.24418418.88420
0.74420.78421.52421421421.04421421.48422
0.76424.16427.4425425424.88425427.6425
0.78431.98433433433432.64433433433
0.8434.2436.2435435434.6435436.8435
0.82441.24447.6444444442.32444450.4444
0.84454.48455.64455455454.64454456.36455
0.86458.26460460460458.68457460460
0.88460.36462.68461461460.48460466.32461
0.9473.4486.4486486475.2468487.6486
0.92488490.4488488488488500.6488
0.94504.8515.76513513505.4503533.24513
0.96540.32572.16572572541.76536573.84572
0.98574.12576.24576576574.16574581.76576



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')