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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationTue, 23 Nov 2010 16:52:03 +0000
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/Nov/23/t1290531024yb87rj4o3payvfd.htm/, Retrieved Fri, 29 Mar 2024 13:49:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=99424, Retrieved Fri, 29 Mar 2024 13:49:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-19 12:03:37] [74be16979710d4c4e7c6647856088456]
- RM D  [Percentiles] [] [2010-11-16 19:22:04] [b98453cac15ba1066b407e146608df68]
-    D      [Percentiles] [] [2010-11-23 16:52:03] [27f38de572a508a633f0ad2411de6a3e] [Current]
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Dataseries X:
43071
45552
36329
37703
50519
36798
37056
44927
37635
62924
8170
27438
27429
33666
27733
33228
25699
303936
30169
35117
34870
56676
7054
29722
41629
41117
39341
39486
48138
45633
41756
47221
50530
68184
8771
37898
41888
40439
40898
38401
52073
41547
38529
51321
41519
69116
12657
34801
37967
39401
33425
36222
48428
40891
36432
50669
39556
68906




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=99424&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=99424&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=99424&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'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)
0.027232.567254.88817081708254.1470547969.127054
0.048362.328386.36877187719859.0881708554.648170
0.0610636.2810869.44126571265718134.64877110558.5612657
0.0821003.8822047.24256992569926667.82569916308.7625699
0.12708327256274292742927435.3274292587227429
0.1227437.6427461.6274382743827685.82743827709.427438
0.1427971.6828250.14297222972229682.222773329204.8627733
0.1629847.1629918.68301693016930536.082972229972.3229722
0.1831514.9632065.58332283322833279.223016931331.4233228
0.233346.233385.6334253342533521.43342533267.433425
0.2233608.1633661.18336663366634278.93366633429.8233666
0.2434710.234812.04348013480134847.923480134858.9634801
0.2634889.7634953.98351173511735072.543487035033.0234870
0.2835382.235691.6362223622236177.83511735647.436222
0.336264.836296.9363293632936339.33622236254.136329
0.3236386.6836419.64364323643236519.843643236341.3636432
0.3436695.5236813.48367983679836896.043679837040.5236798
0.3637025.0437194.96370563705637357.083705637496.0437056
0.3837637.7237663.56377033770337679.883763537674.4437635
0.43774237820378983789837859377033778137898
0.4237922.8437951.82379673796737962.863789837913.1837967
0.4438192.6838383.64384013840138411.243840137984.3638401
0.4638488.0438642.68385293852938707.643852939227.3238529
0.4839211.0839360.2393413934139362.63934139381.839341
0.53940139443.53940139443.539443.53940139443.539443.5
0.5239497.239533.6395563955639530.83948639508.439556
0.5439838.5640315.38404394043940244.743955639679.6240439
0.5640655.9640891.28408914089140854.844043940897.7240891
0.5840895.4840946.18408984089840911.144089841068.8240898
0.641073.241277.8411174111741197.44111741358.241117
0.6241502.9241535.24415194151941528.524151941530.7641547
0.6441556.8441609.32416294162941586.364154741566.6841629
0.6641664.5641748.38417564175641707.744162941636.6241756
0.6841814.0842029.96418884188841856.324175642929.0441888
0.742597.843627.8430714307142952.74307144370.243071
0.7244481.5645227449274492744952449274525244927
0.744550245605.46455524555245566.584555245579.5445633
0.7645760.0446966.92472214722146141.164563345887.0847221
0.7847441.0848143.8481384813847642.824722148422.248138
0.84825448846.24842848428483124813850100.848428
0.8249598.9650523.18505195051949975.345051950525.8250519
0.8450526.9250607.84505305053050528.685053050591.1650669
0.8650652.3251151.48506695066950682.045066950838.5251321
0.8851351.0852012.84520735207351441.325132151381.1652073
0.952993.657300.8566765667653453.95207362299.256676
0.9258925.2864396.8629246292459425.125667666711.262924
0.9465659.268516.12681846818465974.86818468573.8868184
0.9668674.9669040.4689066890668703.846890668981.669116
0.9869082.4261668.4691166911669086.669116111383.6303936

\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 & 7232.56 & 7254.88 & 8170 & 8170 & 8254.14 & 7054 & 7969.12 & 7054 \tabularnewline
0.04 & 8362.32 & 8386.36 & 8771 & 8771 & 9859.08 & 8170 & 8554.64 & 8170 \tabularnewline
0.06 & 10636.28 & 10869.44 & 12657 & 12657 & 18134.64 & 8771 & 10558.56 & 12657 \tabularnewline
0.08 & 21003.88 & 22047.24 & 25699 & 25699 & 26667.8 & 25699 & 16308.76 & 25699 \tabularnewline
0.1 & 27083 & 27256 & 27429 & 27429 & 27435.3 & 27429 & 25872 & 27429 \tabularnewline
0.12 & 27437.64 & 27461.6 & 27438 & 27438 & 27685.8 & 27438 & 27709.4 & 27438 \tabularnewline
0.14 & 27971.68 & 28250.14 & 29722 & 29722 & 29682.22 & 27733 & 29204.86 & 27733 \tabularnewline
0.16 & 29847.16 & 29918.68 & 30169 & 30169 & 30536.08 & 29722 & 29972.32 & 29722 \tabularnewline
0.18 & 31514.96 & 32065.58 & 33228 & 33228 & 33279.22 & 30169 & 31331.42 & 33228 \tabularnewline
0.2 & 33346.2 & 33385.6 & 33425 & 33425 & 33521.4 & 33425 & 33267.4 & 33425 \tabularnewline
0.22 & 33608.16 & 33661.18 & 33666 & 33666 & 34278.9 & 33666 & 33429.82 & 33666 \tabularnewline
0.24 & 34710.2 & 34812.04 & 34801 & 34801 & 34847.92 & 34801 & 34858.96 & 34801 \tabularnewline
0.26 & 34889.76 & 34953.98 & 35117 & 35117 & 35072.54 & 34870 & 35033.02 & 34870 \tabularnewline
0.28 & 35382.2 & 35691.6 & 36222 & 36222 & 36177.8 & 35117 & 35647.4 & 36222 \tabularnewline
0.3 & 36264.8 & 36296.9 & 36329 & 36329 & 36339.3 & 36222 & 36254.1 & 36329 \tabularnewline
0.32 & 36386.68 & 36419.64 & 36432 & 36432 & 36519.84 & 36432 & 36341.36 & 36432 \tabularnewline
0.34 & 36695.52 & 36813.48 & 36798 & 36798 & 36896.04 & 36798 & 37040.52 & 36798 \tabularnewline
0.36 & 37025.04 & 37194.96 & 37056 & 37056 & 37357.08 & 37056 & 37496.04 & 37056 \tabularnewline
0.38 & 37637.72 & 37663.56 & 37703 & 37703 & 37679.88 & 37635 & 37674.44 & 37635 \tabularnewline
0.4 & 37742 & 37820 & 37898 & 37898 & 37859 & 37703 & 37781 & 37898 \tabularnewline
0.42 & 37922.84 & 37951.82 & 37967 & 37967 & 37962.86 & 37898 & 37913.18 & 37967 \tabularnewline
0.44 & 38192.68 & 38383.64 & 38401 & 38401 & 38411.24 & 38401 & 37984.36 & 38401 \tabularnewline
0.46 & 38488.04 & 38642.68 & 38529 & 38529 & 38707.64 & 38529 & 39227.32 & 38529 \tabularnewline
0.48 & 39211.08 & 39360.2 & 39341 & 39341 & 39362.6 & 39341 & 39381.8 & 39341 \tabularnewline
0.5 & 39401 & 39443.5 & 39401 & 39443.5 & 39443.5 & 39401 & 39443.5 & 39443.5 \tabularnewline
0.52 & 39497.2 & 39533.6 & 39556 & 39556 & 39530.8 & 39486 & 39508.4 & 39556 \tabularnewline
0.54 & 39838.56 & 40315.38 & 40439 & 40439 & 40244.74 & 39556 & 39679.62 & 40439 \tabularnewline
0.56 & 40655.96 & 40891.28 & 40891 & 40891 & 40854.84 & 40439 & 40897.72 & 40891 \tabularnewline
0.58 & 40895.48 & 40946.18 & 40898 & 40898 & 40911.14 & 40898 & 41068.82 & 40898 \tabularnewline
0.6 & 41073.2 & 41277.8 & 41117 & 41117 & 41197.4 & 41117 & 41358.2 & 41117 \tabularnewline
0.62 & 41502.92 & 41535.24 & 41519 & 41519 & 41528.52 & 41519 & 41530.76 & 41547 \tabularnewline
0.64 & 41556.84 & 41609.32 & 41629 & 41629 & 41586.36 & 41547 & 41566.68 & 41629 \tabularnewline
0.66 & 41664.56 & 41748.38 & 41756 & 41756 & 41707.74 & 41629 & 41636.62 & 41756 \tabularnewline
0.68 & 41814.08 & 42029.96 & 41888 & 41888 & 41856.32 & 41756 & 42929.04 & 41888 \tabularnewline
0.7 & 42597.8 & 43627.8 & 43071 & 43071 & 42952.7 & 43071 & 44370.2 & 43071 \tabularnewline
0.72 & 44481.56 & 45227 & 44927 & 44927 & 44952 & 44927 & 45252 & 44927 \tabularnewline
0.74 & 45502 & 45605.46 & 45552 & 45552 & 45566.58 & 45552 & 45579.54 & 45633 \tabularnewline
0.76 & 45760.04 & 46966.92 & 47221 & 47221 & 46141.16 & 45633 & 45887.08 & 47221 \tabularnewline
0.78 & 47441.08 & 48143.8 & 48138 & 48138 & 47642.82 & 47221 & 48422.2 & 48138 \tabularnewline
0.8 & 48254 & 48846.2 & 48428 & 48428 & 48312 & 48138 & 50100.8 & 48428 \tabularnewline
0.82 & 49598.96 & 50523.18 & 50519 & 50519 & 49975.34 & 50519 & 50525.82 & 50519 \tabularnewline
0.84 & 50526.92 & 50607.84 & 50530 & 50530 & 50528.68 & 50530 & 50591.16 & 50669 \tabularnewline
0.86 & 50652.32 & 51151.48 & 50669 & 50669 & 50682.04 & 50669 & 50838.52 & 51321 \tabularnewline
0.88 & 51351.08 & 52012.84 & 52073 & 52073 & 51441.32 & 51321 & 51381.16 & 52073 \tabularnewline
0.9 & 52993.6 & 57300.8 & 56676 & 56676 & 53453.9 & 52073 & 62299.2 & 56676 \tabularnewline
0.92 & 58925.28 & 64396.8 & 62924 & 62924 & 59425.12 & 56676 & 66711.2 & 62924 \tabularnewline
0.94 & 65659.2 & 68516.12 & 68184 & 68184 & 65974.8 & 68184 & 68573.88 & 68184 \tabularnewline
0.96 & 68674.96 & 69040.4 & 68906 & 68906 & 68703.84 & 68906 & 68981.6 & 69116 \tabularnewline
0.98 & 69082.4 & 261668.4 & 69116 & 69116 & 69086.6 & 69116 & 111383.6 & 303936 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=99424&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]7232.56[/C][C]7254.88[/C][C]8170[/C][C]8170[/C][C]8254.14[/C][C]7054[/C][C]7969.12[/C][C]7054[/C][/ROW]
[ROW][C]0.04[/C][C]8362.32[/C][C]8386.36[/C][C]8771[/C][C]8771[/C][C]9859.08[/C][C]8170[/C][C]8554.64[/C][C]8170[/C][/ROW]
[ROW][C]0.06[/C][C]10636.28[/C][C]10869.44[/C][C]12657[/C][C]12657[/C][C]18134.64[/C][C]8771[/C][C]10558.56[/C][C]12657[/C][/ROW]
[ROW][C]0.08[/C][C]21003.88[/C][C]22047.24[/C][C]25699[/C][C]25699[/C][C]26667.8[/C][C]25699[/C][C]16308.76[/C][C]25699[/C][/ROW]
[ROW][C]0.1[/C][C]27083[/C][C]27256[/C][C]27429[/C][C]27429[/C][C]27435.3[/C][C]27429[/C][C]25872[/C][C]27429[/C][/ROW]
[ROW][C]0.12[/C][C]27437.64[/C][C]27461.6[/C][C]27438[/C][C]27438[/C][C]27685.8[/C][C]27438[/C][C]27709.4[/C][C]27438[/C][/ROW]
[ROW][C]0.14[/C][C]27971.68[/C][C]28250.14[/C][C]29722[/C][C]29722[/C][C]29682.22[/C][C]27733[/C][C]29204.86[/C][C]27733[/C][/ROW]
[ROW][C]0.16[/C][C]29847.16[/C][C]29918.68[/C][C]30169[/C][C]30169[/C][C]30536.08[/C][C]29722[/C][C]29972.32[/C][C]29722[/C][/ROW]
[ROW][C]0.18[/C][C]31514.96[/C][C]32065.58[/C][C]33228[/C][C]33228[/C][C]33279.22[/C][C]30169[/C][C]31331.42[/C][C]33228[/C][/ROW]
[ROW][C]0.2[/C][C]33346.2[/C][C]33385.6[/C][C]33425[/C][C]33425[/C][C]33521.4[/C][C]33425[/C][C]33267.4[/C][C]33425[/C][/ROW]
[ROW][C]0.22[/C][C]33608.16[/C][C]33661.18[/C][C]33666[/C][C]33666[/C][C]34278.9[/C][C]33666[/C][C]33429.82[/C][C]33666[/C][/ROW]
[ROW][C]0.24[/C][C]34710.2[/C][C]34812.04[/C][C]34801[/C][C]34801[/C][C]34847.92[/C][C]34801[/C][C]34858.96[/C][C]34801[/C][/ROW]
[ROW][C]0.26[/C][C]34889.76[/C][C]34953.98[/C][C]35117[/C][C]35117[/C][C]35072.54[/C][C]34870[/C][C]35033.02[/C][C]34870[/C][/ROW]
[ROW][C]0.28[/C][C]35382.2[/C][C]35691.6[/C][C]36222[/C][C]36222[/C][C]36177.8[/C][C]35117[/C][C]35647.4[/C][C]36222[/C][/ROW]
[ROW][C]0.3[/C][C]36264.8[/C][C]36296.9[/C][C]36329[/C][C]36329[/C][C]36339.3[/C][C]36222[/C][C]36254.1[/C][C]36329[/C][/ROW]
[ROW][C]0.32[/C][C]36386.68[/C][C]36419.64[/C][C]36432[/C][C]36432[/C][C]36519.84[/C][C]36432[/C][C]36341.36[/C][C]36432[/C][/ROW]
[ROW][C]0.34[/C][C]36695.52[/C][C]36813.48[/C][C]36798[/C][C]36798[/C][C]36896.04[/C][C]36798[/C][C]37040.52[/C][C]36798[/C][/ROW]
[ROW][C]0.36[/C][C]37025.04[/C][C]37194.96[/C][C]37056[/C][C]37056[/C][C]37357.08[/C][C]37056[/C][C]37496.04[/C][C]37056[/C][/ROW]
[ROW][C]0.38[/C][C]37637.72[/C][C]37663.56[/C][C]37703[/C][C]37703[/C][C]37679.88[/C][C]37635[/C][C]37674.44[/C][C]37635[/C][/ROW]
[ROW][C]0.4[/C][C]37742[/C][C]37820[/C][C]37898[/C][C]37898[/C][C]37859[/C][C]37703[/C][C]37781[/C][C]37898[/C][/ROW]
[ROW][C]0.42[/C][C]37922.84[/C][C]37951.82[/C][C]37967[/C][C]37967[/C][C]37962.86[/C][C]37898[/C][C]37913.18[/C][C]37967[/C][/ROW]
[ROW][C]0.44[/C][C]38192.68[/C][C]38383.64[/C][C]38401[/C][C]38401[/C][C]38411.24[/C][C]38401[/C][C]37984.36[/C][C]38401[/C][/ROW]
[ROW][C]0.46[/C][C]38488.04[/C][C]38642.68[/C][C]38529[/C][C]38529[/C][C]38707.64[/C][C]38529[/C][C]39227.32[/C][C]38529[/C][/ROW]
[ROW][C]0.48[/C][C]39211.08[/C][C]39360.2[/C][C]39341[/C][C]39341[/C][C]39362.6[/C][C]39341[/C][C]39381.8[/C][C]39341[/C][/ROW]
[ROW][C]0.5[/C][C]39401[/C][C]39443.5[/C][C]39401[/C][C]39443.5[/C][C]39443.5[/C][C]39401[/C][C]39443.5[/C][C]39443.5[/C][/ROW]
[ROW][C]0.52[/C][C]39497.2[/C][C]39533.6[/C][C]39556[/C][C]39556[/C][C]39530.8[/C][C]39486[/C][C]39508.4[/C][C]39556[/C][/ROW]
[ROW][C]0.54[/C][C]39838.56[/C][C]40315.38[/C][C]40439[/C][C]40439[/C][C]40244.74[/C][C]39556[/C][C]39679.62[/C][C]40439[/C][/ROW]
[ROW][C]0.56[/C][C]40655.96[/C][C]40891.28[/C][C]40891[/C][C]40891[/C][C]40854.84[/C][C]40439[/C][C]40897.72[/C][C]40891[/C][/ROW]
[ROW][C]0.58[/C][C]40895.48[/C][C]40946.18[/C][C]40898[/C][C]40898[/C][C]40911.14[/C][C]40898[/C][C]41068.82[/C][C]40898[/C][/ROW]
[ROW][C]0.6[/C][C]41073.2[/C][C]41277.8[/C][C]41117[/C][C]41117[/C][C]41197.4[/C][C]41117[/C][C]41358.2[/C][C]41117[/C][/ROW]
[ROW][C]0.62[/C][C]41502.92[/C][C]41535.24[/C][C]41519[/C][C]41519[/C][C]41528.52[/C][C]41519[/C][C]41530.76[/C][C]41547[/C][/ROW]
[ROW][C]0.64[/C][C]41556.84[/C][C]41609.32[/C][C]41629[/C][C]41629[/C][C]41586.36[/C][C]41547[/C][C]41566.68[/C][C]41629[/C][/ROW]
[ROW][C]0.66[/C][C]41664.56[/C][C]41748.38[/C][C]41756[/C][C]41756[/C][C]41707.74[/C][C]41629[/C][C]41636.62[/C][C]41756[/C][/ROW]
[ROW][C]0.68[/C][C]41814.08[/C][C]42029.96[/C][C]41888[/C][C]41888[/C][C]41856.32[/C][C]41756[/C][C]42929.04[/C][C]41888[/C][/ROW]
[ROW][C]0.7[/C][C]42597.8[/C][C]43627.8[/C][C]43071[/C][C]43071[/C][C]42952.7[/C][C]43071[/C][C]44370.2[/C][C]43071[/C][/ROW]
[ROW][C]0.72[/C][C]44481.56[/C][C]45227[/C][C]44927[/C][C]44927[/C][C]44952[/C][C]44927[/C][C]45252[/C][C]44927[/C][/ROW]
[ROW][C]0.74[/C][C]45502[/C][C]45605.46[/C][C]45552[/C][C]45552[/C][C]45566.58[/C][C]45552[/C][C]45579.54[/C][C]45633[/C][/ROW]
[ROW][C]0.76[/C][C]45760.04[/C][C]46966.92[/C][C]47221[/C][C]47221[/C][C]46141.16[/C][C]45633[/C][C]45887.08[/C][C]47221[/C][/ROW]
[ROW][C]0.78[/C][C]47441.08[/C][C]48143.8[/C][C]48138[/C][C]48138[/C][C]47642.82[/C][C]47221[/C][C]48422.2[/C][C]48138[/C][/ROW]
[ROW][C]0.8[/C][C]48254[/C][C]48846.2[/C][C]48428[/C][C]48428[/C][C]48312[/C][C]48138[/C][C]50100.8[/C][C]48428[/C][/ROW]
[ROW][C]0.82[/C][C]49598.96[/C][C]50523.18[/C][C]50519[/C][C]50519[/C][C]49975.34[/C][C]50519[/C][C]50525.82[/C][C]50519[/C][/ROW]
[ROW][C]0.84[/C][C]50526.92[/C][C]50607.84[/C][C]50530[/C][C]50530[/C][C]50528.68[/C][C]50530[/C][C]50591.16[/C][C]50669[/C][/ROW]
[ROW][C]0.86[/C][C]50652.32[/C][C]51151.48[/C][C]50669[/C][C]50669[/C][C]50682.04[/C][C]50669[/C][C]50838.52[/C][C]51321[/C][/ROW]
[ROW][C]0.88[/C][C]51351.08[/C][C]52012.84[/C][C]52073[/C][C]52073[/C][C]51441.32[/C][C]51321[/C][C]51381.16[/C][C]52073[/C][/ROW]
[ROW][C]0.9[/C][C]52993.6[/C][C]57300.8[/C][C]56676[/C][C]56676[/C][C]53453.9[/C][C]52073[/C][C]62299.2[/C][C]56676[/C][/ROW]
[ROW][C]0.92[/C][C]58925.28[/C][C]64396.8[/C][C]62924[/C][C]62924[/C][C]59425.12[/C][C]56676[/C][C]66711.2[/C][C]62924[/C][/ROW]
[ROW][C]0.94[/C][C]65659.2[/C][C]68516.12[/C][C]68184[/C][C]68184[/C][C]65974.8[/C][C]68184[/C][C]68573.88[/C][C]68184[/C][/ROW]
[ROW][C]0.96[/C][C]68674.96[/C][C]69040.4[/C][C]68906[/C][C]68906[/C][C]68703.84[/C][C]68906[/C][C]68981.6[/C][C]69116[/C][/ROW]
[ROW][C]0.98[/C][C]69082.4[/C][C]261668.4[/C][C]69116[/C][C]69116[/C][C]69086.6[/C][C]69116[/C][C]111383.6[/C][C]303936[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=99424&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=99424&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)
0.027232.567254.88817081708254.1470547969.127054
0.048362.328386.36877187719859.0881708554.648170
0.0610636.2810869.44126571265718134.64877110558.5612657
0.0821003.8822047.24256992569926667.82569916308.7625699
0.12708327256274292742927435.3274292587227429
0.1227437.6427461.6274382743827685.82743827709.427438
0.1427971.6828250.14297222972229682.222773329204.8627733
0.1629847.1629918.68301693016930536.082972229972.3229722
0.1831514.9632065.58332283322833279.223016931331.4233228
0.233346.233385.6334253342533521.43342533267.433425
0.2233608.1633661.18336663366634278.93366633429.8233666
0.2434710.234812.04348013480134847.923480134858.9634801
0.2634889.7634953.98351173511735072.543487035033.0234870
0.2835382.235691.6362223622236177.83511735647.436222
0.336264.836296.9363293632936339.33622236254.136329
0.3236386.6836419.64364323643236519.843643236341.3636432
0.3436695.5236813.48367983679836896.043679837040.5236798
0.3637025.0437194.96370563705637357.083705637496.0437056
0.3837637.7237663.56377033770337679.883763537674.4437635
0.43774237820378983789837859377033778137898
0.4237922.8437951.82379673796737962.863789837913.1837967
0.4438192.6838383.64384013840138411.243840137984.3638401
0.4638488.0438642.68385293852938707.643852939227.3238529
0.4839211.0839360.2393413934139362.63934139381.839341
0.53940139443.53940139443.539443.53940139443.539443.5
0.5239497.239533.6395563955639530.83948639508.439556
0.5439838.5640315.38404394043940244.743955639679.6240439
0.5640655.9640891.28408914089140854.844043940897.7240891
0.5840895.4840946.18408984089840911.144089841068.8240898
0.641073.241277.8411174111741197.44111741358.241117
0.6241502.9241535.24415194151941528.524151941530.7641547
0.6441556.8441609.32416294162941586.364154741566.6841629
0.6641664.5641748.38417564175641707.744162941636.6241756
0.6841814.0842029.96418884188841856.324175642929.0441888
0.742597.843627.8430714307142952.74307144370.243071
0.7244481.5645227449274492744952449274525244927
0.744550245605.46455524555245566.584555245579.5445633
0.7645760.0446966.92472214722146141.164563345887.0847221
0.7847441.0848143.8481384813847642.824722148422.248138
0.84825448846.24842848428483124813850100.848428
0.8249598.9650523.18505195051949975.345051950525.8250519
0.8450526.9250607.84505305053050528.685053050591.1650669
0.8650652.3251151.48506695066950682.045066950838.5251321
0.8851351.0852012.84520735207351441.325132151381.1652073
0.952993.657300.8566765667653453.95207362299.256676
0.9258925.2864396.8629246292459425.125667666711.262924
0.9465659.268516.12681846818465974.86818468573.8868184
0.9668674.9669040.4689066890668703.846890668981.669116
0.9869082.4261668.4691166911669086.669116111383.6303936



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')