Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationFri, 23 Nov 2007 03:49:40 -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/23/t1195814536y6hb1w9akaep8tb.htm/, Retrieved Sun, 28 Apr 2024 19:53:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6146, Retrieved Sun, 28 Apr 2024 19:53:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordspercentiles - totaal
Estimated Impact218
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [investigating ass...] [2007-11-23 10:49:40] [ac6f409873aab27747ac7f3d36ded223] [Current]
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Dataseries X:
513
503
471
471
476
475
470
461
455
456
517
525
523
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6146&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6146&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6146&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







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)
0.02455.46455.48456456458.2455455.52455
0.04460.6460.8461461468.92461456.2461
0.06470.38470.44471471471470470.56470
0.08471471471471474.04471471471
0.1475.3475.4476476480.6475475.6475
0.12493.48496.24499499500.28499478.76499
0.14501.44501.72503503503.32501502.28501
0.16505.72506.36507507508.04507503.64507
0.18509509509509509509509509
0.2509.6509.8510510510.4510509.2510
0.22511.06511.28512512511.84511511.72511
0.24512.52512.76513513514.12513512.24513
0.26516.92517517517517517517517
0.28517.88518.44519519519517517.56519
0.3519519.8519519521.4519522.2519
0.32523.72524.36525525525.04523523.64525
0.34525.82526.96526526528.88526531.04526
0.36533.4535.2537537536.6532533.8537
0.38540.7542.12542542542.36542542.88542
0.4543.2543.6544544543.8543543.4544
0.42545.98547.16547547547.48547548.84547
0.44549.72552.36555555553.08549551.64555
0.46555555555555555555555555
0.48555.08556.04557557556.12555555.96557
0.5559561561561561561561561
0.52561561.48561561561.44561561.52561
0.54563.26564.88565565564.64562562.12565
0.56565565.44565565565.32565565.56565
0.58566.34566.92567567566.76566566.08567
0.6568.6569569569569569569569
0.62570.04572.52573573571.56569569.48573
0.64573573573573573573573573
0.66573.18573.84574574573.52573573.16574
0.68576.56578.64578578577.84578579.36578
0.7580580580580580580580580
0.72582.24585.12584584583.36584586.88584
0.74588.02588.76589589588.28588588.24589
0.76589.48590.24590590589.72589590.76590
0.78590.94592.44591591591.32591591.56593
0.8593.4594594594593.6593594594
0.82594594.68594594594.04594594.32595
0.84595595.32595595595595596.68595
0.86596.56605.96597597596.84597602.04611
0.88611611.12611611611611611.88611
0.9611.7612.6612612611.8612612.4613
0.92614.12620620620614.68613620620
0.94620620.56620620620620620.44621
0.96621.4626.08626626621.6621627.92626
0.98627.08628.52628628627.12628628.48629

\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 & 455.46 & 455.48 & 456 & 456 & 458.2 & 455 & 455.52 & 455 \tabularnewline
0.04 & 460.6 & 460.8 & 461 & 461 & 468.92 & 461 & 456.2 & 461 \tabularnewline
0.06 & 470.38 & 470.44 & 471 & 471 & 471 & 470 & 470.56 & 470 \tabularnewline
0.08 & 471 & 471 & 471 & 471 & 474.04 & 471 & 471 & 471 \tabularnewline
0.1 & 475.3 & 475.4 & 476 & 476 & 480.6 & 475 & 475.6 & 475 \tabularnewline
0.12 & 493.48 & 496.24 & 499 & 499 & 500.28 & 499 & 478.76 & 499 \tabularnewline
0.14 & 501.44 & 501.72 & 503 & 503 & 503.32 & 501 & 502.28 & 501 \tabularnewline
0.16 & 505.72 & 506.36 & 507 & 507 & 508.04 & 507 & 503.64 & 507 \tabularnewline
0.18 & 509 & 509 & 509 & 509 & 509 & 509 & 509 & 509 \tabularnewline
0.2 & 509.6 & 509.8 & 510 & 510 & 510.4 & 510 & 509.2 & 510 \tabularnewline
0.22 & 511.06 & 511.28 & 512 & 512 & 511.84 & 511 & 511.72 & 511 \tabularnewline
0.24 & 512.52 & 512.76 & 513 & 513 & 514.12 & 513 & 512.24 & 513 \tabularnewline
0.26 & 516.92 & 517 & 517 & 517 & 517 & 517 & 517 & 517 \tabularnewline
0.28 & 517.88 & 518.44 & 519 & 519 & 519 & 517 & 517.56 & 519 \tabularnewline
0.3 & 519 & 519.8 & 519 & 519 & 521.4 & 519 & 522.2 & 519 \tabularnewline
0.32 & 523.72 & 524.36 & 525 & 525 & 525.04 & 523 & 523.64 & 525 \tabularnewline
0.34 & 525.82 & 526.96 & 526 & 526 & 528.88 & 526 & 531.04 & 526 \tabularnewline
0.36 & 533.4 & 535.2 & 537 & 537 & 536.6 & 532 & 533.8 & 537 \tabularnewline
0.38 & 540.7 & 542.12 & 542 & 542 & 542.36 & 542 & 542.88 & 542 \tabularnewline
0.4 & 543.2 & 543.6 & 544 & 544 & 543.8 & 543 & 543.4 & 544 \tabularnewline
0.42 & 545.98 & 547.16 & 547 & 547 & 547.48 & 547 & 548.84 & 547 \tabularnewline
0.44 & 549.72 & 552.36 & 555 & 555 & 553.08 & 549 & 551.64 & 555 \tabularnewline
0.46 & 555 & 555 & 555 & 555 & 555 & 555 & 555 & 555 \tabularnewline
0.48 & 555.08 & 556.04 & 557 & 557 & 556.12 & 555 & 555.96 & 557 \tabularnewline
0.5 & 559 & 561 & 561 & 561 & 561 & 561 & 561 & 561 \tabularnewline
0.52 & 561 & 561.48 & 561 & 561 & 561.44 & 561 & 561.52 & 561 \tabularnewline
0.54 & 563.26 & 564.88 & 565 & 565 & 564.64 & 562 & 562.12 & 565 \tabularnewline
0.56 & 565 & 565.44 & 565 & 565 & 565.32 & 565 & 565.56 & 565 \tabularnewline
0.58 & 566.34 & 566.92 & 567 & 567 & 566.76 & 566 & 566.08 & 567 \tabularnewline
0.6 & 568.6 & 569 & 569 & 569 & 569 & 569 & 569 & 569 \tabularnewline
0.62 & 570.04 & 572.52 & 573 & 573 & 571.56 & 569 & 569.48 & 573 \tabularnewline
0.64 & 573 & 573 & 573 & 573 & 573 & 573 & 573 & 573 \tabularnewline
0.66 & 573.18 & 573.84 & 574 & 574 & 573.52 & 573 & 573.16 & 574 \tabularnewline
0.68 & 576.56 & 578.64 & 578 & 578 & 577.84 & 578 & 579.36 & 578 \tabularnewline
0.7 & 580 & 580 & 580 & 580 & 580 & 580 & 580 & 580 \tabularnewline
0.72 & 582.24 & 585.12 & 584 & 584 & 583.36 & 584 & 586.88 & 584 \tabularnewline
0.74 & 588.02 & 588.76 & 589 & 589 & 588.28 & 588 & 588.24 & 589 \tabularnewline
0.76 & 589.48 & 590.24 & 590 & 590 & 589.72 & 589 & 590.76 & 590 \tabularnewline
0.78 & 590.94 & 592.44 & 591 & 591 & 591.32 & 591 & 591.56 & 593 \tabularnewline
0.8 & 593.4 & 594 & 594 & 594 & 593.6 & 593 & 594 & 594 \tabularnewline
0.82 & 594 & 594.68 & 594 & 594 & 594.04 & 594 & 594.32 & 595 \tabularnewline
0.84 & 595 & 595.32 & 595 & 595 & 595 & 595 & 596.68 & 595 \tabularnewline
0.86 & 596.56 & 605.96 & 597 & 597 & 596.84 & 597 & 602.04 & 611 \tabularnewline
0.88 & 611 & 611.12 & 611 & 611 & 611 & 611 & 611.88 & 611 \tabularnewline
0.9 & 611.7 & 612.6 & 612 & 612 & 611.8 & 612 & 612.4 & 613 \tabularnewline
0.92 & 614.12 & 620 & 620 & 620 & 614.68 & 613 & 620 & 620 \tabularnewline
0.94 & 620 & 620.56 & 620 & 620 & 620 & 620 & 620.44 & 621 \tabularnewline
0.96 & 621.4 & 626.08 & 626 & 626 & 621.6 & 621 & 627.92 & 626 \tabularnewline
0.98 & 627.08 & 628.52 & 628 & 628 & 627.12 & 628 & 628.48 & 629 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6146&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]455.46[/C][C]455.48[/C][C]456[/C][C]456[/C][C]458.2[/C][C]455[/C][C]455.52[/C][C]455[/C][/ROW]
[ROW][C]0.04[/C][C]460.6[/C][C]460.8[/C][C]461[/C][C]461[/C][C]468.92[/C][C]461[/C][C]456.2[/C][C]461[/C][/ROW]
[ROW][C]0.06[/C][C]470.38[/C][C]470.44[/C][C]471[/C][C]471[/C][C]471[/C][C]470[/C][C]470.56[/C][C]470[/C][/ROW]
[ROW][C]0.08[/C][C]471[/C][C]471[/C][C]471[/C][C]471[/C][C]474.04[/C][C]471[/C][C]471[/C][C]471[/C][/ROW]
[ROW][C]0.1[/C][C]475.3[/C][C]475.4[/C][C]476[/C][C]476[/C][C]480.6[/C][C]475[/C][C]475.6[/C][C]475[/C][/ROW]
[ROW][C]0.12[/C][C]493.48[/C][C]496.24[/C][C]499[/C][C]499[/C][C]500.28[/C][C]499[/C][C]478.76[/C][C]499[/C][/ROW]
[ROW][C]0.14[/C][C]501.44[/C][C]501.72[/C][C]503[/C][C]503[/C][C]503.32[/C][C]501[/C][C]502.28[/C][C]501[/C][/ROW]
[ROW][C]0.16[/C][C]505.72[/C][C]506.36[/C][C]507[/C][C]507[/C][C]508.04[/C][C]507[/C][C]503.64[/C][C]507[/C][/ROW]
[ROW][C]0.18[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][C]509[/C][/ROW]
[ROW][C]0.2[/C][C]509.6[/C][C]509.8[/C][C]510[/C][C]510[/C][C]510.4[/C][C]510[/C][C]509.2[/C][C]510[/C][/ROW]
[ROW][C]0.22[/C][C]511.06[/C][C]511.28[/C][C]512[/C][C]512[/C][C]511.84[/C][C]511[/C][C]511.72[/C][C]511[/C][/ROW]
[ROW][C]0.24[/C][C]512.52[/C][C]512.76[/C][C]513[/C][C]513[/C][C]514.12[/C][C]513[/C][C]512.24[/C][C]513[/C][/ROW]
[ROW][C]0.26[/C][C]516.92[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][C]517[/C][/ROW]
[ROW][C]0.28[/C][C]517.88[/C][C]518.44[/C][C]519[/C][C]519[/C][C]519[/C][C]517[/C][C]517.56[/C][C]519[/C][/ROW]
[ROW][C]0.3[/C][C]519[/C][C]519.8[/C][C]519[/C][C]519[/C][C]521.4[/C][C]519[/C][C]522.2[/C][C]519[/C][/ROW]
[ROW][C]0.32[/C][C]523.72[/C][C]524.36[/C][C]525[/C][C]525[/C][C]525.04[/C][C]523[/C][C]523.64[/C][C]525[/C][/ROW]
[ROW][C]0.34[/C][C]525.82[/C][C]526.96[/C][C]526[/C][C]526[/C][C]528.88[/C][C]526[/C][C]531.04[/C][C]526[/C][/ROW]
[ROW][C]0.36[/C][C]533.4[/C][C]535.2[/C][C]537[/C][C]537[/C][C]536.6[/C][C]532[/C][C]533.8[/C][C]537[/C][/ROW]
[ROW][C]0.38[/C][C]540.7[/C][C]542.12[/C][C]542[/C][C]542[/C][C]542.36[/C][C]542[/C][C]542.88[/C][C]542[/C][/ROW]
[ROW][C]0.4[/C][C]543.2[/C][C]543.6[/C][C]544[/C][C]544[/C][C]543.8[/C][C]543[/C][C]543.4[/C][C]544[/C][/ROW]
[ROW][C]0.42[/C][C]545.98[/C][C]547.16[/C][C]547[/C][C]547[/C][C]547.48[/C][C]547[/C][C]548.84[/C][C]547[/C][/ROW]
[ROW][C]0.44[/C][C]549.72[/C][C]552.36[/C][C]555[/C][C]555[/C][C]553.08[/C][C]549[/C][C]551.64[/C][C]555[/C][/ROW]
[ROW][C]0.46[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][C]555[/C][/ROW]
[ROW][C]0.48[/C][C]555.08[/C][C]556.04[/C][C]557[/C][C]557[/C][C]556.12[/C][C]555[/C][C]555.96[/C][C]557[/C][/ROW]
[ROW][C]0.5[/C][C]559[/C][C]561[/C][C]561[/C][C]561[/C][C]561[/C][C]561[/C][C]561[/C][C]561[/C][/ROW]
[ROW][C]0.52[/C][C]561[/C][C]561.48[/C][C]561[/C][C]561[/C][C]561.44[/C][C]561[/C][C]561.52[/C][C]561[/C][/ROW]
[ROW][C]0.54[/C][C]563.26[/C][C]564.88[/C][C]565[/C][C]565[/C][C]564.64[/C][C]562[/C][C]562.12[/C][C]565[/C][/ROW]
[ROW][C]0.56[/C][C]565[/C][C]565.44[/C][C]565[/C][C]565[/C][C]565.32[/C][C]565[/C][C]565.56[/C][C]565[/C][/ROW]
[ROW][C]0.58[/C][C]566.34[/C][C]566.92[/C][C]567[/C][C]567[/C][C]566.76[/C][C]566[/C][C]566.08[/C][C]567[/C][/ROW]
[ROW][C]0.6[/C][C]568.6[/C][C]569[/C][C]569[/C][C]569[/C][C]569[/C][C]569[/C][C]569[/C][C]569[/C][/ROW]
[ROW][C]0.62[/C][C]570.04[/C][C]572.52[/C][C]573[/C][C]573[/C][C]571.56[/C][C]569[/C][C]569.48[/C][C]573[/C][/ROW]
[ROW][C]0.64[/C][C]573[/C][C]573[/C][C]573[/C][C]573[/C][C]573[/C][C]573[/C][C]573[/C][C]573[/C][/ROW]
[ROW][C]0.66[/C][C]573.18[/C][C]573.84[/C][C]574[/C][C]574[/C][C]573.52[/C][C]573[/C][C]573.16[/C][C]574[/C][/ROW]
[ROW][C]0.68[/C][C]576.56[/C][C]578.64[/C][C]578[/C][C]578[/C][C]577.84[/C][C]578[/C][C]579.36[/C][C]578[/C][/ROW]
[ROW][C]0.7[/C][C]580[/C][C]580[/C][C]580[/C][C]580[/C][C]580[/C][C]580[/C][C]580[/C][C]580[/C][/ROW]
[ROW][C]0.72[/C][C]582.24[/C][C]585.12[/C][C]584[/C][C]584[/C][C]583.36[/C][C]584[/C][C]586.88[/C][C]584[/C][/ROW]
[ROW][C]0.74[/C][C]588.02[/C][C]588.76[/C][C]589[/C][C]589[/C][C]588.28[/C][C]588[/C][C]588.24[/C][C]589[/C][/ROW]
[ROW][C]0.76[/C][C]589.48[/C][C]590.24[/C][C]590[/C][C]590[/C][C]589.72[/C][C]589[/C][C]590.76[/C][C]590[/C][/ROW]
[ROW][C]0.78[/C][C]590.94[/C][C]592.44[/C][C]591[/C][C]591[/C][C]591.32[/C][C]591[/C][C]591.56[/C][C]593[/C][/ROW]
[ROW][C]0.8[/C][C]593.4[/C][C]594[/C][C]594[/C][C]594[/C][C]593.6[/C][C]593[/C][C]594[/C][C]594[/C][/ROW]
[ROW][C]0.82[/C][C]594[/C][C]594.68[/C][C]594[/C][C]594[/C][C]594.04[/C][C]594[/C][C]594.32[/C][C]595[/C][/ROW]
[ROW][C]0.84[/C][C]595[/C][C]595.32[/C][C]595[/C][C]595[/C][C]595[/C][C]595[/C][C]596.68[/C][C]595[/C][/ROW]
[ROW][C]0.86[/C][C]596.56[/C][C]605.96[/C][C]597[/C][C]597[/C][C]596.84[/C][C]597[/C][C]602.04[/C][C]611[/C][/ROW]
[ROW][C]0.88[/C][C]611[/C][C]611.12[/C][C]611[/C][C]611[/C][C]611[/C][C]611[/C][C]611.88[/C][C]611[/C][/ROW]
[ROW][C]0.9[/C][C]611.7[/C][C]612.6[/C][C]612[/C][C]612[/C][C]611.8[/C][C]612[/C][C]612.4[/C][C]613[/C][/ROW]
[ROW][C]0.92[/C][C]614.12[/C][C]620[/C][C]620[/C][C]620[/C][C]614.68[/C][C]613[/C][C]620[/C][C]620[/C][/ROW]
[ROW][C]0.94[/C][C]620[/C][C]620.56[/C][C]620[/C][C]620[/C][C]620[/C][C]620[/C][C]620.44[/C][C]621[/C][/ROW]
[ROW][C]0.96[/C][C]621.4[/C][C]626.08[/C][C]626[/C][C]626[/C][C]621.6[/C][C]621[/C][C]627.92[/C][C]626[/C][/ROW]
[ROW][C]0.98[/C][C]627.08[/C][C]628.52[/C][C]628[/C][C]628[/C][C]627.12[/C][C]628[/C][C]628.48[/C][C]629[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6146&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6146&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)
0.02455.46455.48456456458.2455455.52455
0.04460.6460.8461461468.92461456.2461
0.06470.38470.44471471471470470.56470
0.08471471471471474.04471471471
0.1475.3475.4476476480.6475475.6475
0.12493.48496.24499499500.28499478.76499
0.14501.44501.72503503503.32501502.28501
0.16505.72506.36507507508.04507503.64507
0.18509509509509509509509509
0.2509.6509.8510510510.4510509.2510
0.22511.06511.28512512511.84511511.72511
0.24512.52512.76513513514.12513512.24513
0.26516.92517517517517517517517
0.28517.88518.44519519519517517.56519
0.3519519.8519519521.4519522.2519
0.32523.72524.36525525525.04523523.64525
0.34525.82526.96526526528.88526531.04526
0.36533.4535.2537537536.6532533.8537
0.38540.7542.12542542542.36542542.88542
0.4543.2543.6544544543.8543543.4544
0.42545.98547.16547547547.48547548.84547
0.44549.72552.36555555553.08549551.64555
0.46555555555555555555555555
0.48555.08556.04557557556.12555555.96557
0.5559561561561561561561561
0.52561561.48561561561.44561561.52561
0.54563.26564.88565565564.64562562.12565
0.56565565.44565565565.32565565.56565
0.58566.34566.92567567566.76566566.08567
0.6568.6569569569569569569569
0.62570.04572.52573573571.56569569.48573
0.64573573573573573573573573
0.66573.18573.84574574573.52573573.16574
0.68576.56578.64578578577.84578579.36578
0.7580580580580580580580580
0.72582.24585.12584584583.36584586.88584
0.74588.02588.76589589588.28588588.24589
0.76589.48590.24590590589.72589590.76590
0.78590.94592.44591591591.32591591.56593
0.8593.4594594594593.6593594594
0.82594594.68594594594.04594594.32595
0.84595595.32595595595595596.68595
0.86596.56605.96597597596.84597602.04611
0.88611611.12611611611611611.88611
0.9611.7612.6612612611.8612612.4613
0.92614.12620620620614.68613620620
0.94620620.56620620620620620.44621
0.96621.4626.08626626621.6621627.92626
0.98627.08628.52628628627.12628628.48629



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')