Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationSun, 19 Oct 2008 05:59:40 -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/t1224417610vjl9oj5nv0vmlge.htm/, Retrieved Sun, 19 May 2024 13:58:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=16781, Retrieved Sun, 19 May 2024 13:58:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Werkloosheid BRUS...] [2008-10-19 10:55:47] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMP   [Histogram] [Histogram - Werkl...] [2008-10-19 11:35:25] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RM        [Percentiles] [Percentiles - Bru...] [2008-10-19 11:59:40] [b23db733701c4d62df5e228d507c1c6a] [Current]
Feedback Forum

Post a new message
Dataseries X:
88827
85874
85211
87130
88620
89563
89056
88542
89504
89428
86040
96240
94423
93028
92285
91685
94260
93858
92437
92980
92099
92803
88551
98334
98329
96455
97109
97687
98512
98673
96028
98014
95580
97838
97760
99913
97588
93942
93656
93365
92881
93120
91063
90930
91946
94624
95484
95862
95530
94574
94677
93845
91533
91214
90922
89563
89945
91850
92505
92437




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=16781&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=16781&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16781&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)
0.0285343.685356.86858748587485903.888521185728.1485211
0.0485940.485947.04860408604086432.48587485966.9685874
0.068669486759.4871308713087892.488713086410.687130
0.0888259.688372.56885428854288548.488854287299.4488542
0.18855188557.98855188585.588613.18855188613.188551
0.1288661.488686.24888278882788845.328862088760.7688620
0.1488918.688950.66890568905689152.728882788932.3489056
0.1689279.289338.72894288942889461.448942889145.2889428
0.1889488.889502.48895048950489540.588950489429.5289504
0.28956389563895638956389563895638956389563
0.2289639.489723.44899458994589937.368956389784.5689563
0.2490335.890570.28909229092290923.288994590296.7290922
0.2690926.890928.88909309093090975.229093090923.1290930
0.2891036.491075.08910639106391141.529106391201.9291063
0.39121491309.79121491373.591437.39121491437.391214
0.3291563.491612.04916859168591666.769153391605.9691685
0.349175191807.1918509185091855.769168591727.991850
0.3691907.691942.16919469194691982.729194691853.8491946
0.3892068.492132.48920999209992177.129209992251.5292099
0.49228592345.8922859236192376.29228592376.292285
0.429243792437924379243792437924379243792437
0.4492464.292494.12925059250592502.289243792447.8892505
0.4692683.892807.68928039280392813.929280392876.3292803
0.4892865.492908.72928819288192912.689288192952.2892881
0.59298093004929809300493004929809300493004
0.5293046.493094.24931209312093090.569302893053.7693120
0.549321893350.3933659336593330.79312093134.793365
0.5693539.693686.24936569365693663.569365693814.7693656
0.5893807.293849.94938459384593847.869384593853.0693845
0.69385893908.4938589390093891.69385893891.693942
0.6294005.694202.76942609426094126.449394293999.2494260
0.6494325.294429.04944239442394383.889426094567.9694423
0.6694513.694587945749457494564.94945749461194574
0.689461494649.44946249462494630.369462494651.5694624
0.79467795241.99467795080.594919.19467794919.195484
0.7295493.295526.32955309553095506.089548495487.6895530
0.749555095619.489558095580955639553095822.5295580
0.7695749.295921.76958629586295816.889586295968.2495862
0.7895994.896150.96960289602896032.249602896117.0496240
0.896240964129624096347.596283962409628396455
0.8296585.897118.58971099710996703.529645597578.4297109
0.8497300.697611.76975889758897377.249710997663.2497588
0.8697647.497720.58976879768797661.269768797726.4297687
0.8897745.497813.04977609776097754.169776097784.9697838
0.99783897996.4978389792697855.69783897855.698014
0.929807798329.6983299832998102.29801498333.498329
0.949833198394.52983349833498331.39832998451.4898334
0.9698440.898602.16985129851298447.929851298582.8498673
0.9898640.899640.2986739867398644.029867398945.899913

\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 & 85343.6 & 85356.86 & 85874 & 85874 & 85903.88 & 85211 & 85728.14 & 85211 \tabularnewline
0.04 & 85940.4 & 85947.04 & 86040 & 86040 & 86432.4 & 85874 & 85966.96 & 85874 \tabularnewline
0.06 & 86694 & 86759.4 & 87130 & 87130 & 87892.48 & 87130 & 86410.6 & 87130 \tabularnewline
0.08 & 88259.6 & 88372.56 & 88542 & 88542 & 88548.48 & 88542 & 87299.44 & 88542 \tabularnewline
0.1 & 88551 & 88557.9 & 88551 & 88585.5 & 88613.1 & 88551 & 88613.1 & 88551 \tabularnewline
0.12 & 88661.4 & 88686.24 & 88827 & 88827 & 88845.32 & 88620 & 88760.76 & 88620 \tabularnewline
0.14 & 88918.6 & 88950.66 & 89056 & 89056 & 89152.72 & 88827 & 88932.34 & 89056 \tabularnewline
0.16 & 89279.2 & 89338.72 & 89428 & 89428 & 89461.44 & 89428 & 89145.28 & 89428 \tabularnewline
0.18 & 89488.8 & 89502.48 & 89504 & 89504 & 89540.58 & 89504 & 89429.52 & 89504 \tabularnewline
0.2 & 89563 & 89563 & 89563 & 89563 & 89563 & 89563 & 89563 & 89563 \tabularnewline
0.22 & 89639.4 & 89723.44 & 89945 & 89945 & 89937.36 & 89563 & 89784.56 & 89563 \tabularnewline
0.24 & 90335.8 & 90570.28 & 90922 & 90922 & 90923.28 & 89945 & 90296.72 & 90922 \tabularnewline
0.26 & 90926.8 & 90928.88 & 90930 & 90930 & 90975.22 & 90930 & 90923.12 & 90930 \tabularnewline
0.28 & 91036.4 & 91075.08 & 91063 & 91063 & 91141.52 & 91063 & 91201.92 & 91063 \tabularnewline
0.3 & 91214 & 91309.7 & 91214 & 91373.5 & 91437.3 & 91214 & 91437.3 & 91214 \tabularnewline
0.32 & 91563.4 & 91612.04 & 91685 & 91685 & 91666.76 & 91533 & 91605.96 & 91685 \tabularnewline
0.34 & 91751 & 91807.1 & 91850 & 91850 & 91855.76 & 91685 & 91727.9 & 91850 \tabularnewline
0.36 & 91907.6 & 91942.16 & 91946 & 91946 & 91982.72 & 91946 & 91853.84 & 91946 \tabularnewline
0.38 & 92068.4 & 92132.48 & 92099 & 92099 & 92177.12 & 92099 & 92251.52 & 92099 \tabularnewline
0.4 & 92285 & 92345.8 & 92285 & 92361 & 92376.2 & 92285 & 92376.2 & 92285 \tabularnewline
0.42 & 92437 & 92437 & 92437 & 92437 & 92437 & 92437 & 92437 & 92437 \tabularnewline
0.44 & 92464.2 & 92494.12 & 92505 & 92505 & 92502.28 & 92437 & 92447.88 & 92505 \tabularnewline
0.46 & 92683.8 & 92807.68 & 92803 & 92803 & 92813.92 & 92803 & 92876.32 & 92803 \tabularnewline
0.48 & 92865.4 & 92908.72 & 92881 & 92881 & 92912.68 & 92881 & 92952.28 & 92881 \tabularnewline
0.5 & 92980 & 93004 & 92980 & 93004 & 93004 & 92980 & 93004 & 93004 \tabularnewline
0.52 & 93046.4 & 93094.24 & 93120 & 93120 & 93090.56 & 93028 & 93053.76 & 93120 \tabularnewline
0.54 & 93218 & 93350.3 & 93365 & 93365 & 93330.7 & 93120 & 93134.7 & 93365 \tabularnewline
0.56 & 93539.6 & 93686.24 & 93656 & 93656 & 93663.56 & 93656 & 93814.76 & 93656 \tabularnewline
0.58 & 93807.2 & 93849.94 & 93845 & 93845 & 93847.86 & 93845 & 93853.06 & 93845 \tabularnewline
0.6 & 93858 & 93908.4 & 93858 & 93900 & 93891.6 & 93858 & 93891.6 & 93942 \tabularnewline
0.62 & 94005.6 & 94202.76 & 94260 & 94260 & 94126.44 & 93942 & 93999.24 & 94260 \tabularnewline
0.64 & 94325.2 & 94429.04 & 94423 & 94423 & 94383.88 & 94260 & 94567.96 & 94423 \tabularnewline
0.66 & 94513.6 & 94587 & 94574 & 94574 & 94564.94 & 94574 & 94611 & 94574 \tabularnewline
0.68 & 94614 & 94649.44 & 94624 & 94624 & 94630.36 & 94624 & 94651.56 & 94624 \tabularnewline
0.7 & 94677 & 95241.9 & 94677 & 95080.5 & 94919.1 & 94677 & 94919.1 & 95484 \tabularnewline
0.72 & 95493.2 & 95526.32 & 95530 & 95530 & 95506.08 & 95484 & 95487.68 & 95530 \tabularnewline
0.74 & 95550 & 95619.48 & 95580 & 95580 & 95563 & 95530 & 95822.52 & 95580 \tabularnewline
0.76 & 95749.2 & 95921.76 & 95862 & 95862 & 95816.88 & 95862 & 95968.24 & 95862 \tabularnewline
0.78 & 95994.8 & 96150.96 & 96028 & 96028 & 96032.24 & 96028 & 96117.04 & 96240 \tabularnewline
0.8 & 96240 & 96412 & 96240 & 96347.5 & 96283 & 96240 & 96283 & 96455 \tabularnewline
0.82 & 96585.8 & 97118.58 & 97109 & 97109 & 96703.52 & 96455 & 97578.42 & 97109 \tabularnewline
0.84 & 97300.6 & 97611.76 & 97588 & 97588 & 97377.24 & 97109 & 97663.24 & 97588 \tabularnewline
0.86 & 97647.4 & 97720.58 & 97687 & 97687 & 97661.26 & 97687 & 97726.42 & 97687 \tabularnewline
0.88 & 97745.4 & 97813.04 & 97760 & 97760 & 97754.16 & 97760 & 97784.96 & 97838 \tabularnewline
0.9 & 97838 & 97996.4 & 97838 & 97926 & 97855.6 & 97838 & 97855.6 & 98014 \tabularnewline
0.92 & 98077 & 98329.6 & 98329 & 98329 & 98102.2 & 98014 & 98333.4 & 98329 \tabularnewline
0.94 & 98331 & 98394.52 & 98334 & 98334 & 98331.3 & 98329 & 98451.48 & 98334 \tabularnewline
0.96 & 98440.8 & 98602.16 & 98512 & 98512 & 98447.92 & 98512 & 98582.84 & 98673 \tabularnewline
0.98 & 98640.8 & 99640.2 & 98673 & 98673 & 98644.02 & 98673 & 98945.8 & 99913 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=16781&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]85343.6[/C][C]85356.86[/C][C]85874[/C][C]85874[/C][C]85903.88[/C][C]85211[/C][C]85728.14[/C][C]85211[/C][/ROW]
[ROW][C]0.04[/C][C]85940.4[/C][C]85947.04[/C][C]86040[/C][C]86040[/C][C]86432.4[/C][C]85874[/C][C]85966.96[/C][C]85874[/C][/ROW]
[ROW][C]0.06[/C][C]86694[/C][C]86759.4[/C][C]87130[/C][C]87130[/C][C]87892.48[/C][C]87130[/C][C]86410.6[/C][C]87130[/C][/ROW]
[ROW][C]0.08[/C][C]88259.6[/C][C]88372.56[/C][C]88542[/C][C]88542[/C][C]88548.48[/C][C]88542[/C][C]87299.44[/C][C]88542[/C][/ROW]
[ROW][C]0.1[/C][C]88551[/C][C]88557.9[/C][C]88551[/C][C]88585.5[/C][C]88613.1[/C][C]88551[/C][C]88613.1[/C][C]88551[/C][/ROW]
[ROW][C]0.12[/C][C]88661.4[/C][C]88686.24[/C][C]88827[/C][C]88827[/C][C]88845.32[/C][C]88620[/C][C]88760.76[/C][C]88620[/C][/ROW]
[ROW][C]0.14[/C][C]88918.6[/C][C]88950.66[/C][C]89056[/C][C]89056[/C][C]89152.72[/C][C]88827[/C][C]88932.34[/C][C]89056[/C][/ROW]
[ROW][C]0.16[/C][C]89279.2[/C][C]89338.72[/C][C]89428[/C][C]89428[/C][C]89461.44[/C][C]89428[/C][C]89145.28[/C][C]89428[/C][/ROW]
[ROW][C]0.18[/C][C]89488.8[/C][C]89502.48[/C][C]89504[/C][C]89504[/C][C]89540.58[/C][C]89504[/C][C]89429.52[/C][C]89504[/C][/ROW]
[ROW][C]0.2[/C][C]89563[/C][C]89563[/C][C]89563[/C][C]89563[/C][C]89563[/C][C]89563[/C][C]89563[/C][C]89563[/C][/ROW]
[ROW][C]0.22[/C][C]89639.4[/C][C]89723.44[/C][C]89945[/C][C]89945[/C][C]89937.36[/C][C]89563[/C][C]89784.56[/C][C]89563[/C][/ROW]
[ROW][C]0.24[/C][C]90335.8[/C][C]90570.28[/C][C]90922[/C][C]90922[/C][C]90923.28[/C][C]89945[/C][C]90296.72[/C][C]90922[/C][/ROW]
[ROW][C]0.26[/C][C]90926.8[/C][C]90928.88[/C][C]90930[/C][C]90930[/C][C]90975.22[/C][C]90930[/C][C]90923.12[/C][C]90930[/C][/ROW]
[ROW][C]0.28[/C][C]91036.4[/C][C]91075.08[/C][C]91063[/C][C]91063[/C][C]91141.52[/C][C]91063[/C][C]91201.92[/C][C]91063[/C][/ROW]
[ROW][C]0.3[/C][C]91214[/C][C]91309.7[/C][C]91214[/C][C]91373.5[/C][C]91437.3[/C][C]91214[/C][C]91437.3[/C][C]91214[/C][/ROW]
[ROW][C]0.32[/C][C]91563.4[/C][C]91612.04[/C][C]91685[/C][C]91685[/C][C]91666.76[/C][C]91533[/C][C]91605.96[/C][C]91685[/C][/ROW]
[ROW][C]0.34[/C][C]91751[/C][C]91807.1[/C][C]91850[/C][C]91850[/C][C]91855.76[/C][C]91685[/C][C]91727.9[/C][C]91850[/C][/ROW]
[ROW][C]0.36[/C][C]91907.6[/C][C]91942.16[/C][C]91946[/C][C]91946[/C][C]91982.72[/C][C]91946[/C][C]91853.84[/C][C]91946[/C][/ROW]
[ROW][C]0.38[/C][C]92068.4[/C][C]92132.48[/C][C]92099[/C][C]92099[/C][C]92177.12[/C][C]92099[/C][C]92251.52[/C][C]92099[/C][/ROW]
[ROW][C]0.4[/C][C]92285[/C][C]92345.8[/C][C]92285[/C][C]92361[/C][C]92376.2[/C][C]92285[/C][C]92376.2[/C][C]92285[/C][/ROW]
[ROW][C]0.42[/C][C]92437[/C][C]92437[/C][C]92437[/C][C]92437[/C][C]92437[/C][C]92437[/C][C]92437[/C][C]92437[/C][/ROW]
[ROW][C]0.44[/C][C]92464.2[/C][C]92494.12[/C][C]92505[/C][C]92505[/C][C]92502.28[/C][C]92437[/C][C]92447.88[/C][C]92505[/C][/ROW]
[ROW][C]0.46[/C][C]92683.8[/C][C]92807.68[/C][C]92803[/C][C]92803[/C][C]92813.92[/C][C]92803[/C][C]92876.32[/C][C]92803[/C][/ROW]
[ROW][C]0.48[/C][C]92865.4[/C][C]92908.72[/C][C]92881[/C][C]92881[/C][C]92912.68[/C][C]92881[/C][C]92952.28[/C][C]92881[/C][/ROW]
[ROW][C]0.5[/C][C]92980[/C][C]93004[/C][C]92980[/C][C]93004[/C][C]93004[/C][C]92980[/C][C]93004[/C][C]93004[/C][/ROW]
[ROW][C]0.52[/C][C]93046.4[/C][C]93094.24[/C][C]93120[/C][C]93120[/C][C]93090.56[/C][C]93028[/C][C]93053.76[/C][C]93120[/C][/ROW]
[ROW][C]0.54[/C][C]93218[/C][C]93350.3[/C][C]93365[/C][C]93365[/C][C]93330.7[/C][C]93120[/C][C]93134.7[/C][C]93365[/C][/ROW]
[ROW][C]0.56[/C][C]93539.6[/C][C]93686.24[/C][C]93656[/C][C]93656[/C][C]93663.56[/C][C]93656[/C][C]93814.76[/C][C]93656[/C][/ROW]
[ROW][C]0.58[/C][C]93807.2[/C][C]93849.94[/C][C]93845[/C][C]93845[/C][C]93847.86[/C][C]93845[/C][C]93853.06[/C][C]93845[/C][/ROW]
[ROW][C]0.6[/C][C]93858[/C][C]93908.4[/C][C]93858[/C][C]93900[/C][C]93891.6[/C][C]93858[/C][C]93891.6[/C][C]93942[/C][/ROW]
[ROW][C]0.62[/C][C]94005.6[/C][C]94202.76[/C][C]94260[/C][C]94260[/C][C]94126.44[/C][C]93942[/C][C]93999.24[/C][C]94260[/C][/ROW]
[ROW][C]0.64[/C][C]94325.2[/C][C]94429.04[/C][C]94423[/C][C]94423[/C][C]94383.88[/C][C]94260[/C][C]94567.96[/C][C]94423[/C][/ROW]
[ROW][C]0.66[/C][C]94513.6[/C][C]94587[/C][C]94574[/C][C]94574[/C][C]94564.94[/C][C]94574[/C][C]94611[/C][C]94574[/C][/ROW]
[ROW][C]0.68[/C][C]94614[/C][C]94649.44[/C][C]94624[/C][C]94624[/C][C]94630.36[/C][C]94624[/C][C]94651.56[/C][C]94624[/C][/ROW]
[ROW][C]0.7[/C][C]94677[/C][C]95241.9[/C][C]94677[/C][C]95080.5[/C][C]94919.1[/C][C]94677[/C][C]94919.1[/C][C]95484[/C][/ROW]
[ROW][C]0.72[/C][C]95493.2[/C][C]95526.32[/C][C]95530[/C][C]95530[/C][C]95506.08[/C][C]95484[/C][C]95487.68[/C][C]95530[/C][/ROW]
[ROW][C]0.74[/C][C]95550[/C][C]95619.48[/C][C]95580[/C][C]95580[/C][C]95563[/C][C]95530[/C][C]95822.52[/C][C]95580[/C][/ROW]
[ROW][C]0.76[/C][C]95749.2[/C][C]95921.76[/C][C]95862[/C][C]95862[/C][C]95816.88[/C][C]95862[/C][C]95968.24[/C][C]95862[/C][/ROW]
[ROW][C]0.78[/C][C]95994.8[/C][C]96150.96[/C][C]96028[/C][C]96028[/C][C]96032.24[/C][C]96028[/C][C]96117.04[/C][C]96240[/C][/ROW]
[ROW][C]0.8[/C][C]96240[/C][C]96412[/C][C]96240[/C][C]96347.5[/C][C]96283[/C][C]96240[/C][C]96283[/C][C]96455[/C][/ROW]
[ROW][C]0.82[/C][C]96585.8[/C][C]97118.58[/C][C]97109[/C][C]97109[/C][C]96703.52[/C][C]96455[/C][C]97578.42[/C][C]97109[/C][/ROW]
[ROW][C]0.84[/C][C]97300.6[/C][C]97611.76[/C][C]97588[/C][C]97588[/C][C]97377.24[/C][C]97109[/C][C]97663.24[/C][C]97588[/C][/ROW]
[ROW][C]0.86[/C][C]97647.4[/C][C]97720.58[/C][C]97687[/C][C]97687[/C][C]97661.26[/C][C]97687[/C][C]97726.42[/C][C]97687[/C][/ROW]
[ROW][C]0.88[/C][C]97745.4[/C][C]97813.04[/C][C]97760[/C][C]97760[/C][C]97754.16[/C][C]97760[/C][C]97784.96[/C][C]97838[/C][/ROW]
[ROW][C]0.9[/C][C]97838[/C][C]97996.4[/C][C]97838[/C][C]97926[/C][C]97855.6[/C][C]97838[/C][C]97855.6[/C][C]98014[/C][/ROW]
[ROW][C]0.92[/C][C]98077[/C][C]98329.6[/C][C]98329[/C][C]98329[/C][C]98102.2[/C][C]98014[/C][C]98333.4[/C][C]98329[/C][/ROW]
[ROW][C]0.94[/C][C]98331[/C][C]98394.52[/C][C]98334[/C][C]98334[/C][C]98331.3[/C][C]98329[/C][C]98451.48[/C][C]98334[/C][/ROW]
[ROW][C]0.96[/C][C]98440.8[/C][C]98602.16[/C][C]98512[/C][C]98512[/C][C]98447.92[/C][C]98512[/C][C]98582.84[/C][C]98673[/C][/ROW]
[ROW][C]0.98[/C][C]98640.8[/C][C]99640.2[/C][C]98673[/C][C]98673[/C][C]98644.02[/C][C]98673[/C][C]98945.8[/C][C]99913[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=16781&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=16781&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)
0.0285343.685356.86858748587485903.888521185728.1485211
0.0485940.485947.04860408604086432.48587485966.9685874
0.068669486759.4871308713087892.488713086410.687130
0.0888259.688372.56885428854288548.488854287299.4488542
0.18855188557.98855188585.588613.18855188613.188551
0.1288661.488686.24888278882788845.328862088760.7688620
0.1488918.688950.66890568905689152.728882788932.3489056
0.1689279.289338.72894288942889461.448942889145.2889428
0.1889488.889502.48895048950489540.588950489429.5289504
0.28956389563895638956389563895638956389563
0.2289639.489723.44899458994589937.368956389784.5689563
0.2490335.890570.28909229092290923.288994590296.7290922
0.2690926.890928.88909309093090975.229093090923.1290930
0.2891036.491075.08910639106391141.529106391201.9291063
0.39121491309.79121491373.591437.39121491437.391214
0.3291563.491612.04916859168591666.769153391605.9691685
0.349175191807.1918509185091855.769168591727.991850
0.3691907.691942.16919469194691982.729194691853.8491946
0.3892068.492132.48920999209992177.129209992251.5292099
0.49228592345.8922859236192376.29228592376.292285
0.429243792437924379243792437924379243792437
0.4492464.292494.12925059250592502.289243792447.8892505
0.4692683.892807.68928039280392813.929280392876.3292803
0.4892865.492908.72928819288192912.689288192952.2892881
0.59298093004929809300493004929809300493004
0.5293046.493094.24931209312093090.569302893053.7693120
0.549321893350.3933659336593330.79312093134.793365
0.5693539.693686.24936569365693663.569365693814.7693656
0.5893807.293849.94938459384593847.869384593853.0693845
0.69385893908.4938589390093891.69385893891.693942
0.6294005.694202.76942609426094126.449394293999.2494260
0.6494325.294429.04944239442394383.889426094567.9694423
0.6694513.694587945749457494564.94945749461194574
0.689461494649.44946249462494630.369462494651.5694624
0.79467795241.99467795080.594919.19467794919.195484
0.7295493.295526.32955309553095506.089548495487.6895530
0.749555095619.489558095580955639553095822.5295580
0.7695749.295921.76958629586295816.889586295968.2495862
0.7895994.896150.96960289602896032.249602896117.0496240
0.896240964129624096347.596283962409628396455
0.8296585.897118.58971099710996703.529645597578.4297109
0.8497300.697611.76975889758897377.249710997663.2497588
0.8697647.497720.58976879768797661.269768797726.4297687
0.8897745.497813.04977609776097754.169776097784.9697838
0.99783897996.4978389792697855.69783897855.698014
0.929807798329.6983299832998102.29801498333.498329
0.949833198394.52983349833498331.39832998451.4898334
0.9698440.898602.16985129851298447.929851298582.8498673
0.9898640.899640.2986739867398644.029867398945.899913



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')