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 computationFri, 11 Dec 2009 05:52:33 -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/2009/Dec/11/t1260535980563cqn4ar90fk14.htm/, Retrieved Sat, 27 Apr 2024 11:50:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66140, Retrieved Sat, 27 Apr 2024 11:50:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [4 plot] [2009-12-10 21:41:19] [830e13ac5e5ac1e5b21c6af0c149b21d]
-    D  [Univariate Explorative Data Analysis] [4 plot] [2009-12-11 12:16:05] [830e13ac5e5ac1e5b21c6af0c149b21d]
- RMP       [Percentiles] [Percentile] [2009-12-11 12:52:33] [9f6463b67b1eb7bae5c03a796abf0348] [Current]
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Dataseries X:
12610
10862
52929
56902
81776
87876
82103
72846
60632
33521
15342
7758
8668
13082
38157
58263
81153
88476
72329
75845
61108
37665
12755
2793
12935
19533
33404
52074
70735
69702
61656
82993
53990
32283
15686
2713
12842
19244
48488
54464
84192
84458
85793
75163
68212
49233
24302
5402
15058
33559
70358
85934
94452
129305
113882
107256
94274
57842
26611
14521




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=66140&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=66140&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66140&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)
0.0227292730.6279327933262.6227132775.42713
0.043836.63940.96540254026250.1627934254.042793
0.066815.66956.96775877588249.477586203.047758
0.0884868558.88668866810247.6886687867.28668
0.11086211036.8108621173612435.21086212435.210862
0.121263912656.4127551275512761.961261012708.612610
0.1412789.812801.98128421284212866.181275512795.0212842
0.1612897.812912.68129351293512999.681293512864.3212935
0.1813052.613079.06130821308213974.181308212937.9413082
0.21452114628.41452114789.514950.61452114950.614521
0.2215114.815177.28153421534215336.321505815222.7215058
0.2415479.615562.16156861568616255.281534215465.8415686
0.2617820.818745.88192441924419342.261924416184.1219244
0.2819475.219914.52195331953322012.881953323920.4819533
0.32430224994.72430225456.525918.32430225918.324302
0.3227745.429560.44322833228331602.362661129333.5632283
0.3432731.433112.54334043340433411.023228332574.4633404
0.3633474.233516.32335213352133530.123352133408.6833521
0.3833551.434298.08335593355935283.523355936925.9233559
0.43766537861.8376653791137960.23766537960.237665
0.4240223.244562.22484884848846215.183815742082.7848488
0.444878649113.8492334923349203.24848848607.249233
0.4650937.652125.3520745207452193.75207452877.752074
0.485275853226.08529295292953268.525292953692.9252929
0.55399054227539905422754227539905422754227
0.5254951.656219.36569025690256121.845446455146.6456902
0.545727857785.6578425784257710.45690256958.457842
0.5658094.658642.04582635826358357.765826360252.9658263
0.5860158.260812.88606326063260736.726063260927.1260632
0.66110861436.8611086138261327.26110861327.261656
0.6262967.267031.92682126821265458.486165662836.0868212
0.646880869728.24697026970269344.46821270331.7669702
0.6670095.670456.02703587035870318.647035870636.9870358
0.6870659.671500.12707357073570926.287073571563.8870735
0.77232972690.97232972587.572484.17232972484.172846
0.7273309.474977.64751637516373958.167284673031.3675163
0.7475435.876588.12758457584575613.127516380409.8875845
0.7679029.881377.28811538115380303.728115381551.7281153
0.7881651.481965.66817768177681782.548177681913.3482103
0.88210382815821038254882281821038228182993
0.8283232.884197.32841928419283448.628299384452.6884192
0.8484298.484778.4844588445884340.968419285472.684458
0.868525985857.86857938579385445.98579385869.1485793
0.8885905.887254.56859348593485922.728593486555.4487876
0.98787688416878768817687936878768793688476
0.9289635.694295.36942749427490099.448847694430.6494274
0.9494345.298805.36944529445294355.8894274102902.6494452
0.96102134.4110966.56107256107256102646.56107256110171.44113882
0.98112556.8125911.94113882113882112689.32113882117275.06129305

\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 & 2729 & 2730.6 & 2793 & 2793 & 3262.62 & 2713 & 2775.4 & 2713 \tabularnewline
0.04 & 3836.6 & 3940.96 & 5402 & 5402 & 6250.16 & 2793 & 4254.04 & 2793 \tabularnewline
0.06 & 6815.6 & 6956.96 & 7758 & 7758 & 8249.4 & 7758 & 6203.04 & 7758 \tabularnewline
0.08 & 8486 & 8558.8 & 8668 & 8668 & 10247.68 & 8668 & 7867.2 & 8668 \tabularnewline
0.1 & 10862 & 11036.8 & 10862 & 11736 & 12435.2 & 10862 & 12435.2 & 10862 \tabularnewline
0.12 & 12639 & 12656.4 & 12755 & 12755 & 12761.96 & 12610 & 12708.6 & 12610 \tabularnewline
0.14 & 12789.8 & 12801.98 & 12842 & 12842 & 12866.18 & 12755 & 12795.02 & 12842 \tabularnewline
0.16 & 12897.8 & 12912.68 & 12935 & 12935 & 12999.68 & 12935 & 12864.32 & 12935 \tabularnewline
0.18 & 13052.6 & 13079.06 & 13082 & 13082 & 13974.18 & 13082 & 12937.94 & 13082 \tabularnewline
0.2 & 14521 & 14628.4 & 14521 & 14789.5 & 14950.6 & 14521 & 14950.6 & 14521 \tabularnewline
0.22 & 15114.8 & 15177.28 & 15342 & 15342 & 15336.32 & 15058 & 15222.72 & 15058 \tabularnewline
0.24 & 15479.6 & 15562.16 & 15686 & 15686 & 16255.28 & 15342 & 15465.84 & 15686 \tabularnewline
0.26 & 17820.8 & 18745.88 & 19244 & 19244 & 19342.26 & 19244 & 16184.12 & 19244 \tabularnewline
0.28 & 19475.2 & 19914.52 & 19533 & 19533 & 22012.88 & 19533 & 23920.48 & 19533 \tabularnewline
0.3 & 24302 & 24994.7 & 24302 & 25456.5 & 25918.3 & 24302 & 25918.3 & 24302 \tabularnewline
0.32 & 27745.4 & 29560.44 & 32283 & 32283 & 31602.36 & 26611 & 29333.56 & 32283 \tabularnewline
0.34 & 32731.4 & 33112.54 & 33404 & 33404 & 33411.02 & 32283 & 32574.46 & 33404 \tabularnewline
0.36 & 33474.2 & 33516.32 & 33521 & 33521 & 33530.12 & 33521 & 33408.68 & 33521 \tabularnewline
0.38 & 33551.4 & 34298.08 & 33559 & 33559 & 35283.52 & 33559 & 36925.92 & 33559 \tabularnewline
0.4 & 37665 & 37861.8 & 37665 & 37911 & 37960.2 & 37665 & 37960.2 & 37665 \tabularnewline
0.42 & 40223.2 & 44562.22 & 48488 & 48488 & 46215.18 & 38157 & 42082.78 & 48488 \tabularnewline
0.44 & 48786 & 49113.8 & 49233 & 49233 & 49203.2 & 48488 & 48607.2 & 49233 \tabularnewline
0.46 & 50937.6 & 52125.3 & 52074 & 52074 & 52193.7 & 52074 & 52877.7 & 52074 \tabularnewline
0.48 & 52758 & 53226.08 & 52929 & 52929 & 53268.52 & 52929 & 53692.92 & 52929 \tabularnewline
0.5 & 53990 & 54227 & 53990 & 54227 & 54227 & 53990 & 54227 & 54227 \tabularnewline
0.52 & 54951.6 & 56219.36 & 56902 & 56902 & 56121.84 & 54464 & 55146.64 & 56902 \tabularnewline
0.54 & 57278 & 57785.6 & 57842 & 57842 & 57710.4 & 56902 & 56958.4 & 57842 \tabularnewline
0.56 & 58094.6 & 58642.04 & 58263 & 58263 & 58357.76 & 58263 & 60252.96 & 58263 \tabularnewline
0.58 & 60158.2 & 60812.88 & 60632 & 60632 & 60736.72 & 60632 & 60927.12 & 60632 \tabularnewline
0.6 & 61108 & 61436.8 & 61108 & 61382 & 61327.2 & 61108 & 61327.2 & 61656 \tabularnewline
0.62 & 62967.2 & 67031.92 & 68212 & 68212 & 65458.48 & 61656 & 62836.08 & 68212 \tabularnewline
0.64 & 68808 & 69728.24 & 69702 & 69702 & 69344.4 & 68212 & 70331.76 & 69702 \tabularnewline
0.66 & 70095.6 & 70456.02 & 70358 & 70358 & 70318.64 & 70358 & 70636.98 & 70358 \tabularnewline
0.68 & 70659.6 & 71500.12 & 70735 & 70735 & 70926.28 & 70735 & 71563.88 & 70735 \tabularnewline
0.7 & 72329 & 72690.9 & 72329 & 72587.5 & 72484.1 & 72329 & 72484.1 & 72846 \tabularnewline
0.72 & 73309.4 & 74977.64 & 75163 & 75163 & 73958.16 & 72846 & 73031.36 & 75163 \tabularnewline
0.74 & 75435.8 & 76588.12 & 75845 & 75845 & 75613.12 & 75163 & 80409.88 & 75845 \tabularnewline
0.76 & 79029.8 & 81377.28 & 81153 & 81153 & 80303.72 & 81153 & 81551.72 & 81153 \tabularnewline
0.78 & 81651.4 & 81965.66 & 81776 & 81776 & 81782.54 & 81776 & 81913.34 & 82103 \tabularnewline
0.8 & 82103 & 82815 & 82103 & 82548 & 82281 & 82103 & 82281 & 82993 \tabularnewline
0.82 & 83232.8 & 84197.32 & 84192 & 84192 & 83448.62 & 82993 & 84452.68 & 84192 \tabularnewline
0.84 & 84298.4 & 84778.4 & 84458 & 84458 & 84340.96 & 84192 & 85472.6 & 84458 \tabularnewline
0.86 & 85259 & 85857.86 & 85793 & 85793 & 85445.9 & 85793 & 85869.14 & 85793 \tabularnewline
0.88 & 85905.8 & 87254.56 & 85934 & 85934 & 85922.72 & 85934 & 86555.44 & 87876 \tabularnewline
0.9 & 87876 & 88416 & 87876 & 88176 & 87936 & 87876 & 87936 & 88476 \tabularnewline
0.92 & 89635.6 & 94295.36 & 94274 & 94274 & 90099.44 & 88476 & 94430.64 & 94274 \tabularnewline
0.94 & 94345.2 & 98805.36 & 94452 & 94452 & 94355.88 & 94274 & 102902.64 & 94452 \tabularnewline
0.96 & 102134.4 & 110966.56 & 107256 & 107256 & 102646.56 & 107256 & 110171.44 & 113882 \tabularnewline
0.98 & 112556.8 & 125911.94 & 113882 & 113882 & 112689.32 & 113882 & 117275.06 & 129305 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66140&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]2729[/C][C]2730.6[/C][C]2793[/C][C]2793[/C][C]3262.62[/C][C]2713[/C][C]2775.4[/C][C]2713[/C][/ROW]
[ROW][C]0.04[/C][C]3836.6[/C][C]3940.96[/C][C]5402[/C][C]5402[/C][C]6250.16[/C][C]2793[/C][C]4254.04[/C][C]2793[/C][/ROW]
[ROW][C]0.06[/C][C]6815.6[/C][C]6956.96[/C][C]7758[/C][C]7758[/C][C]8249.4[/C][C]7758[/C][C]6203.04[/C][C]7758[/C][/ROW]
[ROW][C]0.08[/C][C]8486[/C][C]8558.8[/C][C]8668[/C][C]8668[/C][C]10247.68[/C][C]8668[/C][C]7867.2[/C][C]8668[/C][/ROW]
[ROW][C]0.1[/C][C]10862[/C][C]11036.8[/C][C]10862[/C][C]11736[/C][C]12435.2[/C][C]10862[/C][C]12435.2[/C][C]10862[/C][/ROW]
[ROW][C]0.12[/C][C]12639[/C][C]12656.4[/C][C]12755[/C][C]12755[/C][C]12761.96[/C][C]12610[/C][C]12708.6[/C][C]12610[/C][/ROW]
[ROW][C]0.14[/C][C]12789.8[/C][C]12801.98[/C][C]12842[/C][C]12842[/C][C]12866.18[/C][C]12755[/C][C]12795.02[/C][C]12842[/C][/ROW]
[ROW][C]0.16[/C][C]12897.8[/C][C]12912.68[/C][C]12935[/C][C]12935[/C][C]12999.68[/C][C]12935[/C][C]12864.32[/C][C]12935[/C][/ROW]
[ROW][C]0.18[/C][C]13052.6[/C][C]13079.06[/C][C]13082[/C][C]13082[/C][C]13974.18[/C][C]13082[/C][C]12937.94[/C][C]13082[/C][/ROW]
[ROW][C]0.2[/C][C]14521[/C][C]14628.4[/C][C]14521[/C][C]14789.5[/C][C]14950.6[/C][C]14521[/C][C]14950.6[/C][C]14521[/C][/ROW]
[ROW][C]0.22[/C][C]15114.8[/C][C]15177.28[/C][C]15342[/C][C]15342[/C][C]15336.32[/C][C]15058[/C][C]15222.72[/C][C]15058[/C][/ROW]
[ROW][C]0.24[/C][C]15479.6[/C][C]15562.16[/C][C]15686[/C][C]15686[/C][C]16255.28[/C][C]15342[/C][C]15465.84[/C][C]15686[/C][/ROW]
[ROW][C]0.26[/C][C]17820.8[/C][C]18745.88[/C][C]19244[/C][C]19244[/C][C]19342.26[/C][C]19244[/C][C]16184.12[/C][C]19244[/C][/ROW]
[ROW][C]0.28[/C][C]19475.2[/C][C]19914.52[/C][C]19533[/C][C]19533[/C][C]22012.88[/C][C]19533[/C][C]23920.48[/C][C]19533[/C][/ROW]
[ROW][C]0.3[/C][C]24302[/C][C]24994.7[/C][C]24302[/C][C]25456.5[/C][C]25918.3[/C][C]24302[/C][C]25918.3[/C][C]24302[/C][/ROW]
[ROW][C]0.32[/C][C]27745.4[/C][C]29560.44[/C][C]32283[/C][C]32283[/C][C]31602.36[/C][C]26611[/C][C]29333.56[/C][C]32283[/C][/ROW]
[ROW][C]0.34[/C][C]32731.4[/C][C]33112.54[/C][C]33404[/C][C]33404[/C][C]33411.02[/C][C]32283[/C][C]32574.46[/C][C]33404[/C][/ROW]
[ROW][C]0.36[/C][C]33474.2[/C][C]33516.32[/C][C]33521[/C][C]33521[/C][C]33530.12[/C][C]33521[/C][C]33408.68[/C][C]33521[/C][/ROW]
[ROW][C]0.38[/C][C]33551.4[/C][C]34298.08[/C][C]33559[/C][C]33559[/C][C]35283.52[/C][C]33559[/C][C]36925.92[/C][C]33559[/C][/ROW]
[ROW][C]0.4[/C][C]37665[/C][C]37861.8[/C][C]37665[/C][C]37911[/C][C]37960.2[/C][C]37665[/C][C]37960.2[/C][C]37665[/C][/ROW]
[ROW][C]0.42[/C][C]40223.2[/C][C]44562.22[/C][C]48488[/C][C]48488[/C][C]46215.18[/C][C]38157[/C][C]42082.78[/C][C]48488[/C][/ROW]
[ROW][C]0.44[/C][C]48786[/C][C]49113.8[/C][C]49233[/C][C]49233[/C][C]49203.2[/C][C]48488[/C][C]48607.2[/C][C]49233[/C][/ROW]
[ROW][C]0.46[/C][C]50937.6[/C][C]52125.3[/C][C]52074[/C][C]52074[/C][C]52193.7[/C][C]52074[/C][C]52877.7[/C][C]52074[/C][/ROW]
[ROW][C]0.48[/C][C]52758[/C][C]53226.08[/C][C]52929[/C][C]52929[/C][C]53268.52[/C][C]52929[/C][C]53692.92[/C][C]52929[/C][/ROW]
[ROW][C]0.5[/C][C]53990[/C][C]54227[/C][C]53990[/C][C]54227[/C][C]54227[/C][C]53990[/C][C]54227[/C][C]54227[/C][/ROW]
[ROW][C]0.52[/C][C]54951.6[/C][C]56219.36[/C][C]56902[/C][C]56902[/C][C]56121.84[/C][C]54464[/C][C]55146.64[/C][C]56902[/C][/ROW]
[ROW][C]0.54[/C][C]57278[/C][C]57785.6[/C][C]57842[/C][C]57842[/C][C]57710.4[/C][C]56902[/C][C]56958.4[/C][C]57842[/C][/ROW]
[ROW][C]0.56[/C][C]58094.6[/C][C]58642.04[/C][C]58263[/C][C]58263[/C][C]58357.76[/C][C]58263[/C][C]60252.96[/C][C]58263[/C][/ROW]
[ROW][C]0.58[/C][C]60158.2[/C][C]60812.88[/C][C]60632[/C][C]60632[/C][C]60736.72[/C][C]60632[/C][C]60927.12[/C][C]60632[/C][/ROW]
[ROW][C]0.6[/C][C]61108[/C][C]61436.8[/C][C]61108[/C][C]61382[/C][C]61327.2[/C][C]61108[/C][C]61327.2[/C][C]61656[/C][/ROW]
[ROW][C]0.62[/C][C]62967.2[/C][C]67031.92[/C][C]68212[/C][C]68212[/C][C]65458.48[/C][C]61656[/C][C]62836.08[/C][C]68212[/C][/ROW]
[ROW][C]0.64[/C][C]68808[/C][C]69728.24[/C][C]69702[/C][C]69702[/C][C]69344.4[/C][C]68212[/C][C]70331.76[/C][C]69702[/C][/ROW]
[ROW][C]0.66[/C][C]70095.6[/C][C]70456.02[/C][C]70358[/C][C]70358[/C][C]70318.64[/C][C]70358[/C][C]70636.98[/C][C]70358[/C][/ROW]
[ROW][C]0.68[/C][C]70659.6[/C][C]71500.12[/C][C]70735[/C][C]70735[/C][C]70926.28[/C][C]70735[/C][C]71563.88[/C][C]70735[/C][/ROW]
[ROW][C]0.7[/C][C]72329[/C][C]72690.9[/C][C]72329[/C][C]72587.5[/C][C]72484.1[/C][C]72329[/C][C]72484.1[/C][C]72846[/C][/ROW]
[ROW][C]0.72[/C][C]73309.4[/C][C]74977.64[/C][C]75163[/C][C]75163[/C][C]73958.16[/C][C]72846[/C][C]73031.36[/C][C]75163[/C][/ROW]
[ROW][C]0.74[/C][C]75435.8[/C][C]76588.12[/C][C]75845[/C][C]75845[/C][C]75613.12[/C][C]75163[/C][C]80409.88[/C][C]75845[/C][/ROW]
[ROW][C]0.76[/C][C]79029.8[/C][C]81377.28[/C][C]81153[/C][C]81153[/C][C]80303.72[/C][C]81153[/C][C]81551.72[/C][C]81153[/C][/ROW]
[ROW][C]0.78[/C][C]81651.4[/C][C]81965.66[/C][C]81776[/C][C]81776[/C][C]81782.54[/C][C]81776[/C][C]81913.34[/C][C]82103[/C][/ROW]
[ROW][C]0.8[/C][C]82103[/C][C]82815[/C][C]82103[/C][C]82548[/C][C]82281[/C][C]82103[/C][C]82281[/C][C]82993[/C][/ROW]
[ROW][C]0.82[/C][C]83232.8[/C][C]84197.32[/C][C]84192[/C][C]84192[/C][C]83448.62[/C][C]82993[/C][C]84452.68[/C][C]84192[/C][/ROW]
[ROW][C]0.84[/C][C]84298.4[/C][C]84778.4[/C][C]84458[/C][C]84458[/C][C]84340.96[/C][C]84192[/C][C]85472.6[/C][C]84458[/C][/ROW]
[ROW][C]0.86[/C][C]85259[/C][C]85857.86[/C][C]85793[/C][C]85793[/C][C]85445.9[/C][C]85793[/C][C]85869.14[/C][C]85793[/C][/ROW]
[ROW][C]0.88[/C][C]85905.8[/C][C]87254.56[/C][C]85934[/C][C]85934[/C][C]85922.72[/C][C]85934[/C][C]86555.44[/C][C]87876[/C][/ROW]
[ROW][C]0.9[/C][C]87876[/C][C]88416[/C][C]87876[/C][C]88176[/C][C]87936[/C][C]87876[/C][C]87936[/C][C]88476[/C][/ROW]
[ROW][C]0.92[/C][C]89635.6[/C][C]94295.36[/C][C]94274[/C][C]94274[/C][C]90099.44[/C][C]88476[/C][C]94430.64[/C][C]94274[/C][/ROW]
[ROW][C]0.94[/C][C]94345.2[/C][C]98805.36[/C][C]94452[/C][C]94452[/C][C]94355.88[/C][C]94274[/C][C]102902.64[/C][C]94452[/C][/ROW]
[ROW][C]0.96[/C][C]102134.4[/C][C]110966.56[/C][C]107256[/C][C]107256[/C][C]102646.56[/C][C]107256[/C][C]110171.44[/C][C]113882[/C][/ROW]
[ROW][C]0.98[/C][C]112556.8[/C][C]125911.94[/C][C]113882[/C][C]113882[/C][C]112689.32[/C][C]113882[/C][C]117275.06[/C][C]129305[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66140&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66140&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)
0.0227292730.6279327933262.6227132775.42713
0.043836.63940.96540254026250.1627934254.042793
0.066815.66956.96775877588249.477586203.047758
0.0884868558.88668866810247.6886687867.28668
0.11086211036.8108621173612435.21086212435.210862
0.121263912656.4127551275512761.961261012708.612610
0.1412789.812801.98128421284212866.181275512795.0212842
0.1612897.812912.68129351293512999.681293512864.3212935
0.1813052.613079.06130821308213974.181308212937.9413082
0.21452114628.41452114789.514950.61452114950.614521
0.2215114.815177.28153421534215336.321505815222.7215058
0.2415479.615562.16156861568616255.281534215465.8415686
0.2617820.818745.88192441924419342.261924416184.1219244
0.2819475.219914.52195331953322012.881953323920.4819533
0.32430224994.72430225456.525918.32430225918.324302
0.3227745.429560.44322833228331602.362661129333.5632283
0.3432731.433112.54334043340433411.023228332574.4633404
0.3633474.233516.32335213352133530.123352133408.6833521
0.3833551.434298.08335593355935283.523355936925.9233559
0.43766537861.8376653791137960.23766537960.237665
0.4240223.244562.22484884848846215.183815742082.7848488
0.444878649113.8492334923349203.24848848607.249233
0.4650937.652125.3520745207452193.75207452877.752074
0.485275853226.08529295292953268.525292953692.9252929
0.55399054227539905422754227539905422754227
0.5254951.656219.36569025690256121.845446455146.6456902
0.545727857785.6578425784257710.45690256958.457842
0.5658094.658642.04582635826358357.765826360252.9658263
0.5860158.260812.88606326063260736.726063260927.1260632
0.66110861436.8611086138261327.26110861327.261656
0.6262967.267031.92682126821265458.486165662836.0868212
0.646880869728.24697026970269344.46821270331.7669702
0.6670095.670456.02703587035870318.647035870636.9870358
0.6870659.671500.12707357073570926.287073571563.8870735
0.77232972690.97232972587.572484.17232972484.172846
0.7273309.474977.64751637516373958.167284673031.3675163
0.7475435.876588.12758457584575613.127516380409.8875845
0.7679029.881377.28811538115380303.728115381551.7281153
0.7881651.481965.66817768177681782.548177681913.3482103
0.88210382815821038254882281821038228182993
0.8283232.884197.32841928419283448.628299384452.6884192
0.8484298.484778.4844588445884340.968419285472.684458
0.868525985857.86857938579385445.98579385869.1485793
0.8885905.887254.56859348593485922.728593486555.4487876
0.98787688416878768817687936878768793688476
0.9289635.694295.36942749427490099.448847694430.6494274
0.9494345.298805.36944529445294355.8894274102902.6494452
0.96102134.4110966.56107256107256102646.56107256110171.44113882
0.98112556.8125911.94113882113882112689.32113882117275.06129305



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')