Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationMon, 12 Nov 2007 11:22:23 -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/2007/Nov/12/t1194891457tv8cg4h0x38wjcx.htm/, Retrieved Mon, 29 Apr 2024 02:47:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5289, Retrieved Mon, 29 Apr 2024 02:47:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Percentiles: werk...] [2007-11-12 18:22:23] [94abaf6e1c7b1fd4f9d5e2c2d987f350] [Current]
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Dataseries X:
373
371
354
357
363
364
363
358
357
357
380
378
376
380
379
384
392
394
392
396
392
396
419
421
420
418
410
418
426
428
430
424
423
427
441
449
452
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5289&T=0

[TABLE]
[ROW][C]Summary of compuational 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]5 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=5289&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5289&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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)
0.02355.38355.44357357357354355.56354
0.04357357357357357357357357
0.06357.38357.44358358359.6357357.56357
0.08362.2362.6363363363363358.4363
0.1363.3363.4364364365.4363363.6363
0.12369.32370.16371371372.28371364.84371
0.14373.66374.08376376376.16373374.92373
0.16377.36377.68378378378.52378376.32378
0.18379.14379.32380380379.96379379.68379
0.2380380380380381.6380380380
0.22384.48386.24392392390.72384389.76384
0.24392392392392392392392392
0.26392392.48392392393.44392393.52392
0.28394.88395.44396396396394394.56396
0.3396398396396402396404396
0.32407.44408.72410410410.24406407.28410
0.34414.92416.32416416416.96416417.68416
0.36418418418418418418418418
0.38418418.12418418418.36418418.88418
0.4419.2419.6420420419.8419419.4420
0.42420.66421.16421421421.48421422.84421
0.44423.12423.56424424423.68423423.44424
0.46424424.08424424424.24424425.92424
0.48426.04426.52427427426.56426426.48427
0.5427427427427427427427427
0.52427.96428.96428428428.88428429.04428
0.54430.42430.96431431430.88430430.04431
0.56433.64435.76434434435.28434436.24434
0.58439.02440.76441441440.28438438.24441
0.6441.8442.4442442442.2442442.6442
0.62443.26443.88444444443.64443443.12444
0.64447.6450.08449449449.24449450.92449
0.66452.18452.84453453452.52452452.16453
0.68454.28455455455454.92455455455
0.7455.1455.8456456455.4455455.2456
0.72456456.84456456456456458.16456
0.74459.02459.76460460459.28459459.24460
0.76460.48461461461460.72460461461
0.78461461461461461461461461
0.8461.4462462462461.6461462462
0.82462462462462462462462462
0.84462.32463463463462.48462463463
0.86463464.28463463463463463.72465
0.88465465.24465465465465466.76465
0.9466.4467.6467467466.6467467.4468
0.92468.48471471471468.72468471471
0.94471471.56471471471471471.44472
0.96472472.16472472472472475.84472
0.98474.16476476476474.24476476476

\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 & 355.38 & 355.44 & 357 & 357 & 357 & 354 & 355.56 & 354 \tabularnewline
0.04 & 357 & 357 & 357 & 357 & 357 & 357 & 357 & 357 \tabularnewline
0.06 & 357.38 & 357.44 & 358 & 358 & 359.6 & 357 & 357.56 & 357 \tabularnewline
0.08 & 362.2 & 362.6 & 363 & 363 & 363 & 363 & 358.4 & 363 \tabularnewline
0.1 & 363.3 & 363.4 & 364 & 364 & 365.4 & 363 & 363.6 & 363 \tabularnewline
0.12 & 369.32 & 370.16 & 371 & 371 & 372.28 & 371 & 364.84 & 371 \tabularnewline
0.14 & 373.66 & 374.08 & 376 & 376 & 376.16 & 373 & 374.92 & 373 \tabularnewline
0.16 & 377.36 & 377.68 & 378 & 378 & 378.52 & 378 & 376.32 & 378 \tabularnewline
0.18 & 379.14 & 379.32 & 380 & 380 & 379.96 & 379 & 379.68 & 379 \tabularnewline
0.2 & 380 & 380 & 380 & 380 & 381.6 & 380 & 380 & 380 \tabularnewline
0.22 & 384.48 & 386.24 & 392 & 392 & 390.72 & 384 & 389.76 & 384 \tabularnewline
0.24 & 392 & 392 & 392 & 392 & 392 & 392 & 392 & 392 \tabularnewline
0.26 & 392 & 392.48 & 392 & 392 & 393.44 & 392 & 393.52 & 392 \tabularnewline
0.28 & 394.88 & 395.44 & 396 & 396 & 396 & 394 & 394.56 & 396 \tabularnewline
0.3 & 396 & 398 & 396 & 396 & 402 & 396 & 404 & 396 \tabularnewline
0.32 & 407.44 & 408.72 & 410 & 410 & 410.24 & 406 & 407.28 & 410 \tabularnewline
0.34 & 414.92 & 416.32 & 416 & 416 & 416.96 & 416 & 417.68 & 416 \tabularnewline
0.36 & 418 & 418 & 418 & 418 & 418 & 418 & 418 & 418 \tabularnewline
0.38 & 418 & 418.12 & 418 & 418 & 418.36 & 418 & 418.88 & 418 \tabularnewline
0.4 & 419.2 & 419.6 & 420 & 420 & 419.8 & 419 & 419.4 & 420 \tabularnewline
0.42 & 420.66 & 421.16 & 421 & 421 & 421.48 & 421 & 422.84 & 421 \tabularnewline
0.44 & 423.12 & 423.56 & 424 & 424 & 423.68 & 423 & 423.44 & 424 \tabularnewline
0.46 & 424 & 424.08 & 424 & 424 & 424.24 & 424 & 425.92 & 424 \tabularnewline
0.48 & 426.04 & 426.52 & 427 & 427 & 426.56 & 426 & 426.48 & 427 \tabularnewline
0.5 & 427 & 427 & 427 & 427 & 427 & 427 & 427 & 427 \tabularnewline
0.52 & 427.96 & 428.96 & 428 & 428 & 428.88 & 428 & 429.04 & 428 \tabularnewline
0.54 & 430.42 & 430.96 & 431 & 431 & 430.88 & 430 & 430.04 & 431 \tabularnewline
0.56 & 433.64 & 435.76 & 434 & 434 & 435.28 & 434 & 436.24 & 434 \tabularnewline
0.58 & 439.02 & 440.76 & 441 & 441 & 440.28 & 438 & 438.24 & 441 \tabularnewline
0.6 & 441.8 & 442.4 & 442 & 442 & 442.2 & 442 & 442.6 & 442 \tabularnewline
0.62 & 443.26 & 443.88 & 444 & 444 & 443.64 & 443 & 443.12 & 444 \tabularnewline
0.64 & 447.6 & 450.08 & 449 & 449 & 449.24 & 449 & 450.92 & 449 \tabularnewline
0.66 & 452.18 & 452.84 & 453 & 453 & 452.52 & 452 & 452.16 & 453 \tabularnewline
0.68 & 454.28 & 455 & 455 & 455 & 454.92 & 455 & 455 & 455 \tabularnewline
0.7 & 455.1 & 455.8 & 456 & 456 & 455.4 & 455 & 455.2 & 456 \tabularnewline
0.72 & 456 & 456.84 & 456 & 456 & 456 & 456 & 458.16 & 456 \tabularnewline
0.74 & 459.02 & 459.76 & 460 & 460 & 459.28 & 459 & 459.24 & 460 \tabularnewline
0.76 & 460.48 & 461 & 461 & 461 & 460.72 & 460 & 461 & 461 \tabularnewline
0.78 & 461 & 461 & 461 & 461 & 461 & 461 & 461 & 461 \tabularnewline
0.8 & 461.4 & 462 & 462 & 462 & 461.6 & 461 & 462 & 462 \tabularnewline
0.82 & 462 & 462 & 462 & 462 & 462 & 462 & 462 & 462 \tabularnewline
0.84 & 462.32 & 463 & 463 & 463 & 462.48 & 462 & 463 & 463 \tabularnewline
0.86 & 463 & 464.28 & 463 & 463 & 463 & 463 & 463.72 & 465 \tabularnewline
0.88 & 465 & 465.24 & 465 & 465 & 465 & 465 & 466.76 & 465 \tabularnewline
0.9 & 466.4 & 467.6 & 467 & 467 & 466.6 & 467 & 467.4 & 468 \tabularnewline
0.92 & 468.48 & 471 & 471 & 471 & 468.72 & 468 & 471 & 471 \tabularnewline
0.94 & 471 & 471.56 & 471 & 471 & 471 & 471 & 471.44 & 472 \tabularnewline
0.96 & 472 & 472.16 & 472 & 472 & 472 & 472 & 475.84 & 472 \tabularnewline
0.98 & 474.16 & 476 & 476 & 476 & 474.24 & 476 & 476 & 476 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5289&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]355.38[/C][C]355.44[/C][C]357[/C][C]357[/C][C]357[/C][C]354[/C][C]355.56[/C][C]354[/C][/ROW]
[ROW][C]0.04[/C][C]357[/C][C]357[/C][C]357[/C][C]357[/C][C]357[/C][C]357[/C][C]357[/C][C]357[/C][/ROW]
[ROW][C]0.06[/C][C]357.38[/C][C]357.44[/C][C]358[/C][C]358[/C][C]359.6[/C][C]357[/C][C]357.56[/C][C]357[/C][/ROW]
[ROW][C]0.08[/C][C]362.2[/C][C]362.6[/C][C]363[/C][C]363[/C][C]363[/C][C]363[/C][C]358.4[/C][C]363[/C][/ROW]
[ROW][C]0.1[/C][C]363.3[/C][C]363.4[/C][C]364[/C][C]364[/C][C]365.4[/C][C]363[/C][C]363.6[/C][C]363[/C][/ROW]
[ROW][C]0.12[/C][C]369.32[/C][C]370.16[/C][C]371[/C][C]371[/C][C]372.28[/C][C]371[/C][C]364.84[/C][C]371[/C][/ROW]
[ROW][C]0.14[/C][C]373.66[/C][C]374.08[/C][C]376[/C][C]376[/C][C]376.16[/C][C]373[/C][C]374.92[/C][C]373[/C][/ROW]
[ROW][C]0.16[/C][C]377.36[/C][C]377.68[/C][C]378[/C][C]378[/C][C]378.52[/C][C]378[/C][C]376.32[/C][C]378[/C][/ROW]
[ROW][C]0.18[/C][C]379.14[/C][C]379.32[/C][C]380[/C][C]380[/C][C]379.96[/C][C]379[/C][C]379.68[/C][C]379[/C][/ROW]
[ROW][C]0.2[/C][C]380[/C][C]380[/C][C]380[/C][C]380[/C][C]381.6[/C][C]380[/C][C]380[/C][C]380[/C][/ROW]
[ROW][C]0.22[/C][C]384.48[/C][C]386.24[/C][C]392[/C][C]392[/C][C]390.72[/C][C]384[/C][C]389.76[/C][C]384[/C][/ROW]
[ROW][C]0.24[/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]0.26[/C][C]392[/C][C]392.48[/C][C]392[/C][C]392[/C][C]393.44[/C][C]392[/C][C]393.52[/C][C]392[/C][/ROW]
[ROW][C]0.28[/C][C]394.88[/C][C]395.44[/C][C]396[/C][C]396[/C][C]396[/C][C]394[/C][C]394.56[/C][C]396[/C][/ROW]
[ROW][C]0.3[/C][C]396[/C][C]398[/C][C]396[/C][C]396[/C][C]402[/C][C]396[/C][C]404[/C][C]396[/C][/ROW]
[ROW][C]0.32[/C][C]407.44[/C][C]408.72[/C][C]410[/C][C]410[/C][C]410.24[/C][C]406[/C][C]407.28[/C][C]410[/C][/ROW]
[ROW][C]0.34[/C][C]414.92[/C][C]416.32[/C][C]416[/C][C]416[/C][C]416.96[/C][C]416[/C][C]417.68[/C][C]416[/C][/ROW]
[ROW][C]0.36[/C][C]418[/C][C]418[/C][C]418[/C][C]418[/C][C]418[/C][C]418[/C][C]418[/C][C]418[/C][/ROW]
[ROW][C]0.38[/C][C]418[/C][C]418.12[/C][C]418[/C][C]418[/C][C]418.36[/C][C]418[/C][C]418.88[/C][C]418[/C][/ROW]
[ROW][C]0.4[/C][C]419.2[/C][C]419.6[/C][C]420[/C][C]420[/C][C]419.8[/C][C]419[/C][C]419.4[/C][C]420[/C][/ROW]
[ROW][C]0.42[/C][C]420.66[/C][C]421.16[/C][C]421[/C][C]421[/C][C]421.48[/C][C]421[/C][C]422.84[/C][C]421[/C][/ROW]
[ROW][C]0.44[/C][C]423.12[/C][C]423.56[/C][C]424[/C][C]424[/C][C]423.68[/C][C]423[/C][C]423.44[/C][C]424[/C][/ROW]
[ROW][C]0.46[/C][C]424[/C][C]424.08[/C][C]424[/C][C]424[/C][C]424.24[/C][C]424[/C][C]425.92[/C][C]424[/C][/ROW]
[ROW][C]0.48[/C][C]426.04[/C][C]426.52[/C][C]427[/C][C]427[/C][C]426.56[/C][C]426[/C][C]426.48[/C][C]427[/C][/ROW]
[ROW][C]0.5[/C][C]427[/C][C]427[/C][C]427[/C][C]427[/C][C]427[/C][C]427[/C][C]427[/C][C]427[/C][/ROW]
[ROW][C]0.52[/C][C]427.96[/C][C]428.96[/C][C]428[/C][C]428[/C][C]428.88[/C][C]428[/C][C]429.04[/C][C]428[/C][/ROW]
[ROW][C]0.54[/C][C]430.42[/C][C]430.96[/C][C]431[/C][C]431[/C][C]430.88[/C][C]430[/C][C]430.04[/C][C]431[/C][/ROW]
[ROW][C]0.56[/C][C]433.64[/C][C]435.76[/C][C]434[/C][C]434[/C][C]435.28[/C][C]434[/C][C]436.24[/C][C]434[/C][/ROW]
[ROW][C]0.58[/C][C]439.02[/C][C]440.76[/C][C]441[/C][C]441[/C][C]440.28[/C][C]438[/C][C]438.24[/C][C]441[/C][/ROW]
[ROW][C]0.6[/C][C]441.8[/C][C]442.4[/C][C]442[/C][C]442[/C][C]442.2[/C][C]442[/C][C]442.6[/C][C]442[/C][/ROW]
[ROW][C]0.62[/C][C]443.26[/C][C]443.88[/C][C]444[/C][C]444[/C][C]443.64[/C][C]443[/C][C]443.12[/C][C]444[/C][/ROW]
[ROW][C]0.64[/C][C]447.6[/C][C]450.08[/C][C]449[/C][C]449[/C][C]449.24[/C][C]449[/C][C]450.92[/C][C]449[/C][/ROW]
[ROW][C]0.66[/C][C]452.18[/C][C]452.84[/C][C]453[/C][C]453[/C][C]452.52[/C][C]452[/C][C]452.16[/C][C]453[/C][/ROW]
[ROW][C]0.68[/C][C]454.28[/C][C]455[/C][C]455[/C][C]455[/C][C]454.92[/C][C]455[/C][C]455[/C][C]455[/C][/ROW]
[ROW][C]0.7[/C][C]455.1[/C][C]455.8[/C][C]456[/C][C]456[/C][C]455.4[/C][C]455[/C][C]455.2[/C][C]456[/C][/ROW]
[ROW][C]0.72[/C][C]456[/C][C]456.84[/C][C]456[/C][C]456[/C][C]456[/C][C]456[/C][C]458.16[/C][C]456[/C][/ROW]
[ROW][C]0.74[/C][C]459.02[/C][C]459.76[/C][C]460[/C][C]460[/C][C]459.28[/C][C]459[/C][C]459.24[/C][C]460[/C][/ROW]
[ROW][C]0.76[/C][C]460.48[/C][C]461[/C][C]461[/C][C]461[/C][C]460.72[/C][C]460[/C][C]461[/C][C]461[/C][/ROW]
[ROW][C]0.78[/C][C]461[/C][C]461[/C][C]461[/C][C]461[/C][C]461[/C][C]461[/C][C]461[/C][C]461[/C][/ROW]
[ROW][C]0.8[/C][C]461.4[/C][C]462[/C][C]462[/C][C]462[/C][C]461.6[/C][C]461[/C][C]462[/C][C]462[/C][/ROW]
[ROW][C]0.82[/C][C]462[/C][C]462[/C][C]462[/C][C]462[/C][C]462[/C][C]462[/C][C]462[/C][C]462[/C][/ROW]
[ROW][C]0.84[/C][C]462.32[/C][C]463[/C][C]463[/C][C]463[/C][C]462.48[/C][C]462[/C][C]463[/C][C]463[/C][/ROW]
[ROW][C]0.86[/C][C]463[/C][C]464.28[/C][C]463[/C][C]463[/C][C]463[/C][C]463[/C][C]463.72[/C][C]465[/C][/ROW]
[ROW][C]0.88[/C][C]465[/C][C]465.24[/C][C]465[/C][C]465[/C][C]465[/C][C]465[/C][C]466.76[/C][C]465[/C][/ROW]
[ROW][C]0.9[/C][C]466.4[/C][C]467.6[/C][C]467[/C][C]467[/C][C]466.6[/C][C]467[/C][C]467.4[/C][C]468[/C][/ROW]
[ROW][C]0.92[/C][C]468.48[/C][C]471[/C][C]471[/C][C]471[/C][C]468.72[/C][C]468[/C][C]471[/C][C]471[/C][/ROW]
[ROW][C]0.94[/C][C]471[/C][C]471.56[/C][C]471[/C][C]471[/C][C]471[/C][C]471[/C][C]471.44[/C][C]472[/C][/ROW]
[ROW][C]0.96[/C][C]472[/C][C]472.16[/C][C]472[/C][C]472[/C][C]472[/C][C]472[/C][C]475.84[/C][C]472[/C][/ROW]
[ROW][C]0.98[/C][C]474.16[/C][C]476[/C][C]476[/C][C]476[/C][C]474.24[/C][C]476[/C][C]476[/C][C]476[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5289&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5289&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)
0.02355.38355.44357357357354355.56354
0.04357357357357357357357357
0.06357.38357.44358358359.6357357.56357
0.08362.2362.6363363363363358.4363
0.1363.3363.4364364365.4363363.6363
0.12369.32370.16371371372.28371364.84371
0.14373.66374.08376376376.16373374.92373
0.16377.36377.68378378378.52378376.32378
0.18379.14379.32380380379.96379379.68379
0.2380380380380381.6380380380
0.22384.48386.24392392390.72384389.76384
0.24392392392392392392392392
0.26392392.48392392393.44392393.52392
0.28394.88395.44396396396394394.56396
0.3396398396396402396404396
0.32407.44408.72410410410.24406407.28410
0.34414.92416.32416416416.96416417.68416
0.36418418418418418418418418
0.38418418.12418418418.36418418.88418
0.4419.2419.6420420419.8419419.4420
0.42420.66421.16421421421.48421422.84421
0.44423.12423.56424424423.68423423.44424
0.46424424.08424424424.24424425.92424
0.48426.04426.52427427426.56426426.48427
0.5427427427427427427427427
0.52427.96428.96428428428.88428429.04428
0.54430.42430.96431431430.88430430.04431
0.56433.64435.76434434435.28434436.24434
0.58439.02440.76441441440.28438438.24441
0.6441.8442.4442442442.2442442.6442
0.62443.26443.88444444443.64443443.12444
0.64447.6450.08449449449.24449450.92449
0.66452.18452.84453453452.52452452.16453
0.68454.28455455455454.92455455455
0.7455.1455.8456456455.4455455.2456
0.72456456.84456456456456458.16456
0.74459.02459.76460460459.28459459.24460
0.76460.48461461461460.72460461461
0.78461461461461461461461461
0.8461.4462462462461.6461462462
0.82462462462462462462462462
0.84462.32463463463462.48462463463
0.86463464.28463463463463463.72465
0.88465465.24465465465465466.76465
0.9466.4467.6467467466.6467467.4468
0.92468.48471471471468.72468471471
0.94471471.56471471471471471.44472
0.96472472.16472472472472475.84472
0.98474.16476476476474.24476476476



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)
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')