Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationMon, 09 Nov 2009 12:34:29 -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/Nov/09/t12577953659v131rwkycl6wx9.htm/, Retrieved Thu, 28 Mar 2024 10:20:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54953, Retrieved Thu, 28 Mar 2024 10:20:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Brutoschuld Overh...] [2009-11-09 19:34:29] [c483349466b1550829c7523719d2d027] [Current]
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Dataseries X:
269285
269829
270911
266844
271244
269907
271296
270157
271322
267179
264101
265518
269419
268714
272482
268351
268175
270674
272764
272599
270333
270846
270491
269160
274027
273784
276663
274525
271344
271115
270798
273911
273985
271917
273338
270601
273547
275363
281229
277793
279913
282500
280041
282166
290304
283519
287816
285226
287595
289741
289148
288301
290155
289648
288225
289351
294735
305333
309030
310215
321935




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54953&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54953&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54953&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







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)
0.02264412.74264441.08265518265518265783.2264101265177.92264101
0.04266101.44266154.48266844266844266978265518266207.52265518
0.06267065.1267085.2267179267179267776.6267179266937.8267179
0.08268055.48268135.16268175268175268315.8268175267218.84268175
0.1268387.3268423.6268714268714268714268351268641.4268351
0.12268856.72268910.24269160269160269185268714268963.76268714
0.14269227.5269245269285269285269338.6269285269200269285
0.16269386.84269408.28269419269419269665269419269295.72269419
0.18269820.8269841.48269829269829269891.4269829269894.52269829
0.2269957270007270157270157270157269907270057269907
0.22270230.92270269.64270333270333270364.6270157270220.36270333
0.24270434.12270472.04270491270491270535270491270351.96270491
0.26270585.6270609.76270601270601270644.8270601270665.24270601
0.28270683.92270718.64270798270798270773.2270674270753.36270674
0.3270812.4270826.8270846270846270846270798270817.2270846
0.32270879.8270900.6270911270911270951.8270911270856.4270911
0.34271061.96271125.32271115271115271166.6271115271233.68271115
0.36271238.84271260.64271244271244271275.2271244271279.36271244
0.38271300.68271310.56271322271322271316.8271296271307.44271322
0.4271330.8271339.6271344271344271344271322271326.4271344
0.42271699.26271939.6271917271917272030271917272459.4271917
0.44272391.6272514.76272482272482272528.8272482272566.24272482
0.46272608.9272684.8272764272764272698272599272678.2272764
0.48272924.72273200.24273338273338273223.2272764272901.76273338
0.5273442.5273547273547273547273547273547273547273547
0.52273717.64273814.48273784273784273809.4273784273880.52273784
0.54273903.38273946.52273911273911273940.6273911273949.48273911
0.56273991.72274015.24274027274027274010.2273985273996.76274027
0.58274216.24274505.08274525274525274425.4274027274046.92274525
0.6275027.8275623275363275363275363275363276403275363
0.62276429277160.2276663276663276889276663277295.8276663
0.64277877.8279234.6279913279913278641277793278471.4279913
0.66279946.28280030.76280041280041279989.8279913279923.24280041
0.68280611.24281378.92281229281229280991.4280041282016.08281229
0.7281884.9282299.6282166282166282166282166282366.4282166
0.72282473.28283152.16282500282500282703.8282500282866.84283519
0.74283757.98285021.16285226285226284201.8283519283723.84285226
0.76286078.84287621.52287595287595286647.4285226287789.48287595
0.78287723.18287963.24287816287816287771.8287816288077.76287816
0.8288143.2288270.6288225288225288225288225288255.4288301
0.82288317.94289012.48289148289148288470.4288301288436.52289148
0.84289196.72289374.76289351289351289229.2289148289624.24289351
0.86289487.62289677.76289648289648289529.2289351289711.24289648
0.88289711.24289972.84289741289741289722.4289741289923.16290155
0.9290113.6290274.2290155290155290155290155290184.8290304
0.92290835.72295158.92294735294735291190.2290304304909.08294735
0.94298338.32306368.16305333305333298974.2294735307994.84305333
0.96307403.32309646.2309030309030307551.2309030309598.8310215
0.98309954.3319122.2310215310215309978310215313027.8321935

\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 & 264412.74 & 264441.08 & 265518 & 265518 & 265783.2 & 264101 & 265177.92 & 264101 \tabularnewline
0.04 & 266101.44 & 266154.48 & 266844 & 266844 & 266978 & 265518 & 266207.52 & 265518 \tabularnewline
0.06 & 267065.1 & 267085.2 & 267179 & 267179 & 267776.6 & 267179 & 266937.8 & 267179 \tabularnewline
0.08 & 268055.48 & 268135.16 & 268175 & 268175 & 268315.8 & 268175 & 267218.84 & 268175 \tabularnewline
0.1 & 268387.3 & 268423.6 & 268714 & 268714 & 268714 & 268351 & 268641.4 & 268351 \tabularnewline
0.12 & 268856.72 & 268910.24 & 269160 & 269160 & 269185 & 268714 & 268963.76 & 268714 \tabularnewline
0.14 & 269227.5 & 269245 & 269285 & 269285 & 269338.6 & 269285 & 269200 & 269285 \tabularnewline
0.16 & 269386.84 & 269408.28 & 269419 & 269419 & 269665 & 269419 & 269295.72 & 269419 \tabularnewline
0.18 & 269820.8 & 269841.48 & 269829 & 269829 & 269891.4 & 269829 & 269894.52 & 269829 \tabularnewline
0.2 & 269957 & 270007 & 270157 & 270157 & 270157 & 269907 & 270057 & 269907 \tabularnewline
0.22 & 270230.92 & 270269.64 & 270333 & 270333 & 270364.6 & 270157 & 270220.36 & 270333 \tabularnewline
0.24 & 270434.12 & 270472.04 & 270491 & 270491 & 270535 & 270491 & 270351.96 & 270491 \tabularnewline
0.26 & 270585.6 & 270609.76 & 270601 & 270601 & 270644.8 & 270601 & 270665.24 & 270601 \tabularnewline
0.28 & 270683.92 & 270718.64 & 270798 & 270798 & 270773.2 & 270674 & 270753.36 & 270674 \tabularnewline
0.3 & 270812.4 & 270826.8 & 270846 & 270846 & 270846 & 270798 & 270817.2 & 270846 \tabularnewline
0.32 & 270879.8 & 270900.6 & 270911 & 270911 & 270951.8 & 270911 & 270856.4 & 270911 \tabularnewline
0.34 & 271061.96 & 271125.32 & 271115 & 271115 & 271166.6 & 271115 & 271233.68 & 271115 \tabularnewline
0.36 & 271238.84 & 271260.64 & 271244 & 271244 & 271275.2 & 271244 & 271279.36 & 271244 \tabularnewline
0.38 & 271300.68 & 271310.56 & 271322 & 271322 & 271316.8 & 271296 & 271307.44 & 271322 \tabularnewline
0.4 & 271330.8 & 271339.6 & 271344 & 271344 & 271344 & 271322 & 271326.4 & 271344 \tabularnewline
0.42 & 271699.26 & 271939.6 & 271917 & 271917 & 272030 & 271917 & 272459.4 & 271917 \tabularnewline
0.44 & 272391.6 & 272514.76 & 272482 & 272482 & 272528.8 & 272482 & 272566.24 & 272482 \tabularnewline
0.46 & 272608.9 & 272684.8 & 272764 & 272764 & 272698 & 272599 & 272678.2 & 272764 \tabularnewline
0.48 & 272924.72 & 273200.24 & 273338 & 273338 & 273223.2 & 272764 & 272901.76 & 273338 \tabularnewline
0.5 & 273442.5 & 273547 & 273547 & 273547 & 273547 & 273547 & 273547 & 273547 \tabularnewline
0.52 & 273717.64 & 273814.48 & 273784 & 273784 & 273809.4 & 273784 & 273880.52 & 273784 \tabularnewline
0.54 & 273903.38 & 273946.52 & 273911 & 273911 & 273940.6 & 273911 & 273949.48 & 273911 \tabularnewline
0.56 & 273991.72 & 274015.24 & 274027 & 274027 & 274010.2 & 273985 & 273996.76 & 274027 \tabularnewline
0.58 & 274216.24 & 274505.08 & 274525 & 274525 & 274425.4 & 274027 & 274046.92 & 274525 \tabularnewline
0.6 & 275027.8 & 275623 & 275363 & 275363 & 275363 & 275363 & 276403 & 275363 \tabularnewline
0.62 & 276429 & 277160.2 & 276663 & 276663 & 276889 & 276663 & 277295.8 & 276663 \tabularnewline
0.64 & 277877.8 & 279234.6 & 279913 & 279913 & 278641 & 277793 & 278471.4 & 279913 \tabularnewline
0.66 & 279946.28 & 280030.76 & 280041 & 280041 & 279989.8 & 279913 & 279923.24 & 280041 \tabularnewline
0.68 & 280611.24 & 281378.92 & 281229 & 281229 & 280991.4 & 280041 & 282016.08 & 281229 \tabularnewline
0.7 & 281884.9 & 282299.6 & 282166 & 282166 & 282166 & 282166 & 282366.4 & 282166 \tabularnewline
0.72 & 282473.28 & 283152.16 & 282500 & 282500 & 282703.8 & 282500 & 282866.84 & 283519 \tabularnewline
0.74 & 283757.98 & 285021.16 & 285226 & 285226 & 284201.8 & 283519 & 283723.84 & 285226 \tabularnewline
0.76 & 286078.84 & 287621.52 & 287595 & 287595 & 286647.4 & 285226 & 287789.48 & 287595 \tabularnewline
0.78 & 287723.18 & 287963.24 & 287816 & 287816 & 287771.8 & 287816 & 288077.76 & 287816 \tabularnewline
0.8 & 288143.2 & 288270.6 & 288225 & 288225 & 288225 & 288225 & 288255.4 & 288301 \tabularnewline
0.82 & 288317.94 & 289012.48 & 289148 & 289148 & 288470.4 & 288301 & 288436.52 & 289148 \tabularnewline
0.84 & 289196.72 & 289374.76 & 289351 & 289351 & 289229.2 & 289148 & 289624.24 & 289351 \tabularnewline
0.86 & 289487.62 & 289677.76 & 289648 & 289648 & 289529.2 & 289351 & 289711.24 & 289648 \tabularnewline
0.88 & 289711.24 & 289972.84 & 289741 & 289741 & 289722.4 & 289741 & 289923.16 & 290155 \tabularnewline
0.9 & 290113.6 & 290274.2 & 290155 & 290155 & 290155 & 290155 & 290184.8 & 290304 \tabularnewline
0.92 & 290835.72 & 295158.92 & 294735 & 294735 & 291190.2 & 290304 & 304909.08 & 294735 \tabularnewline
0.94 & 298338.32 & 306368.16 & 305333 & 305333 & 298974.2 & 294735 & 307994.84 & 305333 \tabularnewline
0.96 & 307403.32 & 309646.2 & 309030 & 309030 & 307551.2 & 309030 & 309598.8 & 310215 \tabularnewline
0.98 & 309954.3 & 319122.2 & 310215 & 310215 & 309978 & 310215 & 313027.8 & 321935 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54953&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]264412.74[/C][C]264441.08[/C][C]265518[/C][C]265518[/C][C]265783.2[/C][C]264101[/C][C]265177.92[/C][C]264101[/C][/ROW]
[ROW][C]0.04[/C][C]266101.44[/C][C]266154.48[/C][C]266844[/C][C]266844[/C][C]266978[/C][C]265518[/C][C]266207.52[/C][C]265518[/C][/ROW]
[ROW][C]0.06[/C][C]267065.1[/C][C]267085.2[/C][C]267179[/C][C]267179[/C][C]267776.6[/C][C]267179[/C][C]266937.8[/C][C]267179[/C][/ROW]
[ROW][C]0.08[/C][C]268055.48[/C][C]268135.16[/C][C]268175[/C][C]268175[/C][C]268315.8[/C][C]268175[/C][C]267218.84[/C][C]268175[/C][/ROW]
[ROW][C]0.1[/C][C]268387.3[/C][C]268423.6[/C][C]268714[/C][C]268714[/C][C]268714[/C][C]268351[/C][C]268641.4[/C][C]268351[/C][/ROW]
[ROW][C]0.12[/C][C]268856.72[/C][C]268910.24[/C][C]269160[/C][C]269160[/C][C]269185[/C][C]268714[/C][C]268963.76[/C][C]268714[/C][/ROW]
[ROW][C]0.14[/C][C]269227.5[/C][C]269245[/C][C]269285[/C][C]269285[/C][C]269338.6[/C][C]269285[/C][C]269200[/C][C]269285[/C][/ROW]
[ROW][C]0.16[/C][C]269386.84[/C][C]269408.28[/C][C]269419[/C][C]269419[/C][C]269665[/C][C]269419[/C][C]269295.72[/C][C]269419[/C][/ROW]
[ROW][C]0.18[/C][C]269820.8[/C][C]269841.48[/C][C]269829[/C][C]269829[/C][C]269891.4[/C][C]269829[/C][C]269894.52[/C][C]269829[/C][/ROW]
[ROW][C]0.2[/C][C]269957[/C][C]270007[/C][C]270157[/C][C]270157[/C][C]270157[/C][C]269907[/C][C]270057[/C][C]269907[/C][/ROW]
[ROW][C]0.22[/C][C]270230.92[/C][C]270269.64[/C][C]270333[/C][C]270333[/C][C]270364.6[/C][C]270157[/C][C]270220.36[/C][C]270333[/C][/ROW]
[ROW][C]0.24[/C][C]270434.12[/C][C]270472.04[/C][C]270491[/C][C]270491[/C][C]270535[/C][C]270491[/C][C]270351.96[/C][C]270491[/C][/ROW]
[ROW][C]0.26[/C][C]270585.6[/C][C]270609.76[/C][C]270601[/C][C]270601[/C][C]270644.8[/C][C]270601[/C][C]270665.24[/C][C]270601[/C][/ROW]
[ROW][C]0.28[/C][C]270683.92[/C][C]270718.64[/C][C]270798[/C][C]270798[/C][C]270773.2[/C][C]270674[/C][C]270753.36[/C][C]270674[/C][/ROW]
[ROW][C]0.3[/C][C]270812.4[/C][C]270826.8[/C][C]270846[/C][C]270846[/C][C]270846[/C][C]270798[/C][C]270817.2[/C][C]270846[/C][/ROW]
[ROW][C]0.32[/C][C]270879.8[/C][C]270900.6[/C][C]270911[/C][C]270911[/C][C]270951.8[/C][C]270911[/C][C]270856.4[/C][C]270911[/C][/ROW]
[ROW][C]0.34[/C][C]271061.96[/C][C]271125.32[/C][C]271115[/C][C]271115[/C][C]271166.6[/C][C]271115[/C][C]271233.68[/C][C]271115[/C][/ROW]
[ROW][C]0.36[/C][C]271238.84[/C][C]271260.64[/C][C]271244[/C][C]271244[/C][C]271275.2[/C][C]271244[/C][C]271279.36[/C][C]271244[/C][/ROW]
[ROW][C]0.38[/C][C]271300.68[/C][C]271310.56[/C][C]271322[/C][C]271322[/C][C]271316.8[/C][C]271296[/C][C]271307.44[/C][C]271322[/C][/ROW]
[ROW][C]0.4[/C][C]271330.8[/C][C]271339.6[/C][C]271344[/C][C]271344[/C][C]271344[/C][C]271322[/C][C]271326.4[/C][C]271344[/C][/ROW]
[ROW][C]0.42[/C][C]271699.26[/C][C]271939.6[/C][C]271917[/C][C]271917[/C][C]272030[/C][C]271917[/C][C]272459.4[/C][C]271917[/C][/ROW]
[ROW][C]0.44[/C][C]272391.6[/C][C]272514.76[/C][C]272482[/C][C]272482[/C][C]272528.8[/C][C]272482[/C][C]272566.24[/C][C]272482[/C][/ROW]
[ROW][C]0.46[/C][C]272608.9[/C][C]272684.8[/C][C]272764[/C][C]272764[/C][C]272698[/C][C]272599[/C][C]272678.2[/C][C]272764[/C][/ROW]
[ROW][C]0.48[/C][C]272924.72[/C][C]273200.24[/C][C]273338[/C][C]273338[/C][C]273223.2[/C][C]272764[/C][C]272901.76[/C][C]273338[/C][/ROW]
[ROW][C]0.5[/C][C]273442.5[/C][C]273547[/C][C]273547[/C][C]273547[/C][C]273547[/C][C]273547[/C][C]273547[/C][C]273547[/C][/ROW]
[ROW][C]0.52[/C][C]273717.64[/C][C]273814.48[/C][C]273784[/C][C]273784[/C][C]273809.4[/C][C]273784[/C][C]273880.52[/C][C]273784[/C][/ROW]
[ROW][C]0.54[/C][C]273903.38[/C][C]273946.52[/C][C]273911[/C][C]273911[/C][C]273940.6[/C][C]273911[/C][C]273949.48[/C][C]273911[/C][/ROW]
[ROW][C]0.56[/C][C]273991.72[/C][C]274015.24[/C][C]274027[/C][C]274027[/C][C]274010.2[/C][C]273985[/C][C]273996.76[/C][C]274027[/C][/ROW]
[ROW][C]0.58[/C][C]274216.24[/C][C]274505.08[/C][C]274525[/C][C]274525[/C][C]274425.4[/C][C]274027[/C][C]274046.92[/C][C]274525[/C][/ROW]
[ROW][C]0.6[/C][C]275027.8[/C][C]275623[/C][C]275363[/C][C]275363[/C][C]275363[/C][C]275363[/C][C]276403[/C][C]275363[/C][/ROW]
[ROW][C]0.62[/C][C]276429[/C][C]277160.2[/C][C]276663[/C][C]276663[/C][C]276889[/C][C]276663[/C][C]277295.8[/C][C]276663[/C][/ROW]
[ROW][C]0.64[/C][C]277877.8[/C][C]279234.6[/C][C]279913[/C][C]279913[/C][C]278641[/C][C]277793[/C][C]278471.4[/C][C]279913[/C][/ROW]
[ROW][C]0.66[/C][C]279946.28[/C][C]280030.76[/C][C]280041[/C][C]280041[/C][C]279989.8[/C][C]279913[/C][C]279923.24[/C][C]280041[/C][/ROW]
[ROW][C]0.68[/C][C]280611.24[/C][C]281378.92[/C][C]281229[/C][C]281229[/C][C]280991.4[/C][C]280041[/C][C]282016.08[/C][C]281229[/C][/ROW]
[ROW][C]0.7[/C][C]281884.9[/C][C]282299.6[/C][C]282166[/C][C]282166[/C][C]282166[/C][C]282166[/C][C]282366.4[/C][C]282166[/C][/ROW]
[ROW][C]0.72[/C][C]282473.28[/C][C]283152.16[/C][C]282500[/C][C]282500[/C][C]282703.8[/C][C]282500[/C][C]282866.84[/C][C]283519[/C][/ROW]
[ROW][C]0.74[/C][C]283757.98[/C][C]285021.16[/C][C]285226[/C][C]285226[/C][C]284201.8[/C][C]283519[/C][C]283723.84[/C][C]285226[/C][/ROW]
[ROW][C]0.76[/C][C]286078.84[/C][C]287621.52[/C][C]287595[/C][C]287595[/C][C]286647.4[/C][C]285226[/C][C]287789.48[/C][C]287595[/C][/ROW]
[ROW][C]0.78[/C][C]287723.18[/C][C]287963.24[/C][C]287816[/C][C]287816[/C][C]287771.8[/C][C]287816[/C][C]288077.76[/C][C]287816[/C][/ROW]
[ROW][C]0.8[/C][C]288143.2[/C][C]288270.6[/C][C]288225[/C][C]288225[/C][C]288225[/C][C]288225[/C][C]288255.4[/C][C]288301[/C][/ROW]
[ROW][C]0.82[/C][C]288317.94[/C][C]289012.48[/C][C]289148[/C][C]289148[/C][C]288470.4[/C][C]288301[/C][C]288436.52[/C][C]289148[/C][/ROW]
[ROW][C]0.84[/C][C]289196.72[/C][C]289374.76[/C][C]289351[/C][C]289351[/C][C]289229.2[/C][C]289148[/C][C]289624.24[/C][C]289351[/C][/ROW]
[ROW][C]0.86[/C][C]289487.62[/C][C]289677.76[/C][C]289648[/C][C]289648[/C][C]289529.2[/C][C]289351[/C][C]289711.24[/C][C]289648[/C][/ROW]
[ROW][C]0.88[/C][C]289711.24[/C][C]289972.84[/C][C]289741[/C][C]289741[/C][C]289722.4[/C][C]289741[/C][C]289923.16[/C][C]290155[/C][/ROW]
[ROW][C]0.9[/C][C]290113.6[/C][C]290274.2[/C][C]290155[/C][C]290155[/C][C]290155[/C][C]290155[/C][C]290184.8[/C][C]290304[/C][/ROW]
[ROW][C]0.92[/C][C]290835.72[/C][C]295158.92[/C][C]294735[/C][C]294735[/C][C]291190.2[/C][C]290304[/C][C]304909.08[/C][C]294735[/C][/ROW]
[ROW][C]0.94[/C][C]298338.32[/C][C]306368.16[/C][C]305333[/C][C]305333[/C][C]298974.2[/C][C]294735[/C][C]307994.84[/C][C]305333[/C][/ROW]
[ROW][C]0.96[/C][C]307403.32[/C][C]309646.2[/C][C]309030[/C][C]309030[/C][C]307551.2[/C][C]309030[/C][C]309598.8[/C][C]310215[/C][/ROW]
[ROW][C]0.98[/C][C]309954.3[/C][C]319122.2[/C][C]310215[/C][C]310215[/C][C]309978[/C][C]310215[/C][C]313027.8[/C][C]321935[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54953&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54953&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)
0.02264412.74264441.08265518265518265783.2264101265177.92264101
0.04266101.44266154.48266844266844266978265518266207.52265518
0.06267065.1267085.2267179267179267776.6267179266937.8267179
0.08268055.48268135.16268175268175268315.8268175267218.84268175
0.1268387.3268423.6268714268714268714268351268641.4268351
0.12268856.72268910.24269160269160269185268714268963.76268714
0.14269227.5269245269285269285269338.6269285269200269285
0.16269386.84269408.28269419269419269665269419269295.72269419
0.18269820.8269841.48269829269829269891.4269829269894.52269829
0.2269957270007270157270157270157269907270057269907
0.22270230.92270269.64270333270333270364.6270157270220.36270333
0.24270434.12270472.04270491270491270535270491270351.96270491
0.26270585.6270609.76270601270601270644.8270601270665.24270601
0.28270683.92270718.64270798270798270773.2270674270753.36270674
0.3270812.4270826.8270846270846270846270798270817.2270846
0.32270879.8270900.6270911270911270951.8270911270856.4270911
0.34271061.96271125.32271115271115271166.6271115271233.68271115
0.36271238.84271260.64271244271244271275.2271244271279.36271244
0.38271300.68271310.56271322271322271316.8271296271307.44271322
0.4271330.8271339.6271344271344271344271322271326.4271344
0.42271699.26271939.6271917271917272030271917272459.4271917
0.44272391.6272514.76272482272482272528.8272482272566.24272482
0.46272608.9272684.8272764272764272698272599272678.2272764
0.48272924.72273200.24273338273338273223.2272764272901.76273338
0.5273442.5273547273547273547273547273547273547273547
0.52273717.64273814.48273784273784273809.4273784273880.52273784
0.54273903.38273946.52273911273911273940.6273911273949.48273911
0.56273991.72274015.24274027274027274010.2273985273996.76274027
0.58274216.24274505.08274525274525274425.4274027274046.92274525
0.6275027.8275623275363275363275363275363276403275363
0.62276429277160.2276663276663276889276663277295.8276663
0.64277877.8279234.6279913279913278641277793278471.4279913
0.66279946.28280030.76280041280041279989.8279913279923.24280041
0.68280611.24281378.92281229281229280991.4280041282016.08281229
0.7281884.9282299.6282166282166282166282166282366.4282166
0.72282473.28283152.16282500282500282703.8282500282866.84283519
0.74283757.98285021.16285226285226284201.8283519283723.84285226
0.76286078.84287621.52287595287595286647.4285226287789.48287595
0.78287723.18287963.24287816287816287771.8287816288077.76287816
0.8288143.2288270.6288225288225288225288225288255.4288301
0.82288317.94289012.48289148289148288470.4288301288436.52289148
0.84289196.72289374.76289351289351289229.2289148289624.24289351
0.86289487.62289677.76289648289648289529.2289351289711.24289648
0.88289711.24289972.84289741289741289722.4289741289923.16290155
0.9290113.6290274.2290155290155290155290155290184.8290304
0.92290835.72295158.92294735294735291190.2290304304909.08294735
0.94298338.32306368.16305333305333298974.2294735307994.84305333
0.96307403.32309646.2309030309030307551.2309030309598.8310215
0.98309954.3319122.2310215310215309978310215313027.8321935



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')