Free Statistics

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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 computationSat, 13 Dec 2008 01:33:15 -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/2008/Dec/13/t12291573794wd0d7e0r9pvakf.htm/, Retrieved Sun, 19 May 2024 05:36:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32891, Retrieved Sun, 19 May 2024 05:36:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact219
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [Normal QQ-Plot Co...] [2008-12-13 08:33:15] [28deb8481dba3cc87d2d53a86e0e0d0b] [Current]
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Dataseries X:
98,5
97,0
103,3
99,6
100,1
102,9
95,9
94,5
107,4
116,0
102,8
99,8
109,6
103,0
111,6
106,3
97,9
108,8
103,9
101,2
122,9
123,9
111,7
120,9
99,6
103,3
119,4
106,5
101,9
124,6
106,5
107,8
127,4
120,1
118,5
127,7
107,7
104,5
118,8
110,3
109,6
119,1
96,5
106,7
126,3
116,2
118,8
115,2
110,0
111,4
129,6
108,1
117,8
122,9
100,6
111,8
127,0
128,6
124,8
118,5
114,7
112,6
128,7
111,0
115,8
126,0
111,1
113,2
120,1
130,6
124,0
119,4
116,7
116,5
119,6
126,5
111,3
123,5
114,2
103,7
129,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32891&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]5 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=32891&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32891&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 time5 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)
0.0295.36895.39695.995.996.2695.995.00495.9
0.0496.6296.64979797.1896.596.8696.5
0.0697.77497.82897.997.998.3897.997.07297.9
0.0899.02899.11699.699.699.698.598.98499.6
0.199.6299.6499.899.899.899.699.7699.6
0.12100.016100.052100.1100.1100.4100.199.848100.1
0.14100.804100.888101.2101.2101.34100.6100.912100.6
0.16101.872102.008101.9101.9102.62101.9102.692101.9
0.18102.858102.876102.9102.9102.94102.9102.824102.9
0.2103.06103.12103.3103.3103.3103103.18103
0.22103.3103.316103.3103.3103.54103.3103.684103.3
0.24103.788103.836103.9103.9104.02103.7103.764103.9
0.26104.608105.076106.3106.3105.94104.5105.724104.5
0.28106.436106.492106.5106.5106.5106.5106.308106.5
0.3106.56106.62106.7106.7106.7106.5106.58106.7
0.32107.344107.472107.4107.4107.58107.4107.628107.4
0.34107.754107.788107.8107.8107.86107.8107.712107.8
0.36108.212108.464108.8108.8108.66108.1108.436108.8
0.38109.424109.6109.6109.6109.6109.6109.6109.6
0.4109.76109.92110110110109.6109.68110
0.42110.314110.608111111110.72110.3110.692110.3
0.44111.064111.116111.1111.1111.14111.1111.284111.1
0.46111.326111.372111.4111.4111.38111.3111.328111.4
0.48111.576111.636111.6111.6111.64111.6111.664111.6
0.5111.75111.8111.8111.8111.8111.8111.8111.8
0.52112.672112.984113.2113.2112.96112.6112.816113.2
0.54113.94114.34114.2114.2114.3114.2114.56114.2
0.56114.88115.16115.2115.2115.1114.7114.74115.2
0.58115.788115.912115.8115.8115.88115.8115.888116
0.6116.12116.26116.2116.2116.2116.2116.44116.2
0.62116.544116.668116.7116.7116.62116.5116.532116.7
0.64117.624118.136117.8117.8117.94117.8118.164117.8
0.66118.5118.536118.5118.5118.5118.5118.764118.5
0.68118.8118.8118.8118.8118.8118.8118.8118.8
0.7119.01119.22119.1119.1119.1119.1119.28119.1
0.72119.4119.408119.4119.4119.4119.4119.592119.4
0.74119.588119.94119.6119.6119.7119.6119.76120.1
0.76120.1120.356120.1120.1120.1120.1120.644120.1
0.78121.26122.82122.9122.9121.7120.9120.98122.9
0.8122.9123.26122.9122.9122.9122.9123.14123.5
0.82123.668123.924123.9123.9123.74123.5123.976123.9
0.84124.024124.528124.6124.6124.12124124.072124.6
0.86124.732125.424124.8124.8124.76124.8125.376126
0.88126.084126.332126.3126.3126.12126126.468126.3
0.9126.48126.9126.5126.5126.5126.5126.6127
0.92127.208127.532127.4127.4127.24127.4127.568127.4
0.94127.826128.608128.6128.6127.88127.7128.692128.6
0.96128.676129.276128.7128.7128.68128.7128.924129.5
0.98129.538129.96129.6129.6129.54129.5130.24129.6

\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 & 95.368 & 95.396 & 95.9 & 95.9 & 96.26 & 95.9 & 95.004 & 95.9 \tabularnewline
0.04 & 96.62 & 96.64 & 97 & 97 & 97.18 & 96.5 & 96.86 & 96.5 \tabularnewline
0.06 & 97.774 & 97.828 & 97.9 & 97.9 & 98.38 & 97.9 & 97.072 & 97.9 \tabularnewline
0.08 & 99.028 & 99.116 & 99.6 & 99.6 & 99.6 & 98.5 & 98.984 & 99.6 \tabularnewline
0.1 & 99.62 & 99.64 & 99.8 & 99.8 & 99.8 & 99.6 & 99.76 & 99.6 \tabularnewline
0.12 & 100.016 & 100.052 & 100.1 & 100.1 & 100.4 & 100.1 & 99.848 & 100.1 \tabularnewline
0.14 & 100.804 & 100.888 & 101.2 & 101.2 & 101.34 & 100.6 & 100.912 & 100.6 \tabularnewline
0.16 & 101.872 & 102.008 & 101.9 & 101.9 & 102.62 & 101.9 & 102.692 & 101.9 \tabularnewline
0.18 & 102.858 & 102.876 & 102.9 & 102.9 & 102.94 & 102.9 & 102.824 & 102.9 \tabularnewline
0.2 & 103.06 & 103.12 & 103.3 & 103.3 & 103.3 & 103 & 103.18 & 103 \tabularnewline
0.22 & 103.3 & 103.316 & 103.3 & 103.3 & 103.54 & 103.3 & 103.684 & 103.3 \tabularnewline
0.24 & 103.788 & 103.836 & 103.9 & 103.9 & 104.02 & 103.7 & 103.764 & 103.9 \tabularnewline
0.26 & 104.608 & 105.076 & 106.3 & 106.3 & 105.94 & 104.5 & 105.724 & 104.5 \tabularnewline
0.28 & 106.436 & 106.492 & 106.5 & 106.5 & 106.5 & 106.5 & 106.308 & 106.5 \tabularnewline
0.3 & 106.56 & 106.62 & 106.7 & 106.7 & 106.7 & 106.5 & 106.58 & 106.7 \tabularnewline
0.32 & 107.344 & 107.472 & 107.4 & 107.4 & 107.58 & 107.4 & 107.628 & 107.4 \tabularnewline
0.34 & 107.754 & 107.788 & 107.8 & 107.8 & 107.86 & 107.8 & 107.712 & 107.8 \tabularnewline
0.36 & 108.212 & 108.464 & 108.8 & 108.8 & 108.66 & 108.1 & 108.436 & 108.8 \tabularnewline
0.38 & 109.424 & 109.6 & 109.6 & 109.6 & 109.6 & 109.6 & 109.6 & 109.6 \tabularnewline
0.4 & 109.76 & 109.92 & 110 & 110 & 110 & 109.6 & 109.68 & 110 \tabularnewline
0.42 & 110.314 & 110.608 & 111 & 111 & 110.72 & 110.3 & 110.692 & 110.3 \tabularnewline
0.44 & 111.064 & 111.116 & 111.1 & 111.1 & 111.14 & 111.1 & 111.284 & 111.1 \tabularnewline
0.46 & 111.326 & 111.372 & 111.4 & 111.4 & 111.38 & 111.3 & 111.328 & 111.4 \tabularnewline
0.48 & 111.576 & 111.636 & 111.6 & 111.6 & 111.64 & 111.6 & 111.664 & 111.6 \tabularnewline
0.5 & 111.75 & 111.8 & 111.8 & 111.8 & 111.8 & 111.8 & 111.8 & 111.8 \tabularnewline
0.52 & 112.672 & 112.984 & 113.2 & 113.2 & 112.96 & 112.6 & 112.816 & 113.2 \tabularnewline
0.54 & 113.94 & 114.34 & 114.2 & 114.2 & 114.3 & 114.2 & 114.56 & 114.2 \tabularnewline
0.56 & 114.88 & 115.16 & 115.2 & 115.2 & 115.1 & 114.7 & 114.74 & 115.2 \tabularnewline
0.58 & 115.788 & 115.912 & 115.8 & 115.8 & 115.88 & 115.8 & 115.888 & 116 \tabularnewline
0.6 & 116.12 & 116.26 & 116.2 & 116.2 & 116.2 & 116.2 & 116.44 & 116.2 \tabularnewline
0.62 & 116.544 & 116.668 & 116.7 & 116.7 & 116.62 & 116.5 & 116.532 & 116.7 \tabularnewline
0.64 & 117.624 & 118.136 & 117.8 & 117.8 & 117.94 & 117.8 & 118.164 & 117.8 \tabularnewline
0.66 & 118.5 & 118.536 & 118.5 & 118.5 & 118.5 & 118.5 & 118.764 & 118.5 \tabularnewline
0.68 & 118.8 & 118.8 & 118.8 & 118.8 & 118.8 & 118.8 & 118.8 & 118.8 \tabularnewline
0.7 & 119.01 & 119.22 & 119.1 & 119.1 & 119.1 & 119.1 & 119.28 & 119.1 \tabularnewline
0.72 & 119.4 & 119.408 & 119.4 & 119.4 & 119.4 & 119.4 & 119.592 & 119.4 \tabularnewline
0.74 & 119.588 & 119.94 & 119.6 & 119.6 & 119.7 & 119.6 & 119.76 & 120.1 \tabularnewline
0.76 & 120.1 & 120.356 & 120.1 & 120.1 & 120.1 & 120.1 & 120.644 & 120.1 \tabularnewline
0.78 & 121.26 & 122.82 & 122.9 & 122.9 & 121.7 & 120.9 & 120.98 & 122.9 \tabularnewline
0.8 & 122.9 & 123.26 & 122.9 & 122.9 & 122.9 & 122.9 & 123.14 & 123.5 \tabularnewline
0.82 & 123.668 & 123.924 & 123.9 & 123.9 & 123.74 & 123.5 & 123.976 & 123.9 \tabularnewline
0.84 & 124.024 & 124.528 & 124.6 & 124.6 & 124.12 & 124 & 124.072 & 124.6 \tabularnewline
0.86 & 124.732 & 125.424 & 124.8 & 124.8 & 124.76 & 124.8 & 125.376 & 126 \tabularnewline
0.88 & 126.084 & 126.332 & 126.3 & 126.3 & 126.12 & 126 & 126.468 & 126.3 \tabularnewline
0.9 & 126.48 & 126.9 & 126.5 & 126.5 & 126.5 & 126.5 & 126.6 & 127 \tabularnewline
0.92 & 127.208 & 127.532 & 127.4 & 127.4 & 127.24 & 127.4 & 127.568 & 127.4 \tabularnewline
0.94 & 127.826 & 128.608 & 128.6 & 128.6 & 127.88 & 127.7 & 128.692 & 128.6 \tabularnewline
0.96 & 128.676 & 129.276 & 128.7 & 128.7 & 128.68 & 128.7 & 128.924 & 129.5 \tabularnewline
0.98 & 129.538 & 129.96 & 129.6 & 129.6 & 129.54 & 129.5 & 130.24 & 129.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32891&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]95.368[/C][C]95.396[/C][C]95.9[/C][C]95.9[/C][C]96.26[/C][C]95.9[/C][C]95.004[/C][C]95.9[/C][/ROW]
[ROW][C]0.04[/C][C]96.62[/C][C]96.64[/C][C]97[/C][C]97[/C][C]97.18[/C][C]96.5[/C][C]96.86[/C][C]96.5[/C][/ROW]
[ROW][C]0.06[/C][C]97.774[/C][C]97.828[/C][C]97.9[/C][C]97.9[/C][C]98.38[/C][C]97.9[/C][C]97.072[/C][C]97.9[/C][/ROW]
[ROW][C]0.08[/C][C]99.028[/C][C]99.116[/C][C]99.6[/C][C]99.6[/C][C]99.6[/C][C]98.5[/C][C]98.984[/C][C]99.6[/C][/ROW]
[ROW][C]0.1[/C][C]99.62[/C][C]99.64[/C][C]99.8[/C][C]99.8[/C][C]99.8[/C][C]99.6[/C][C]99.76[/C][C]99.6[/C][/ROW]
[ROW][C]0.12[/C][C]100.016[/C][C]100.052[/C][C]100.1[/C][C]100.1[/C][C]100.4[/C][C]100.1[/C][C]99.848[/C][C]100.1[/C][/ROW]
[ROW][C]0.14[/C][C]100.804[/C][C]100.888[/C][C]101.2[/C][C]101.2[/C][C]101.34[/C][C]100.6[/C][C]100.912[/C][C]100.6[/C][/ROW]
[ROW][C]0.16[/C][C]101.872[/C][C]102.008[/C][C]101.9[/C][C]101.9[/C][C]102.62[/C][C]101.9[/C][C]102.692[/C][C]101.9[/C][/ROW]
[ROW][C]0.18[/C][C]102.858[/C][C]102.876[/C][C]102.9[/C][C]102.9[/C][C]102.94[/C][C]102.9[/C][C]102.824[/C][C]102.9[/C][/ROW]
[ROW][C]0.2[/C][C]103.06[/C][C]103.12[/C][C]103.3[/C][C]103.3[/C][C]103.3[/C][C]103[/C][C]103.18[/C][C]103[/C][/ROW]
[ROW][C]0.22[/C][C]103.3[/C][C]103.316[/C][C]103.3[/C][C]103.3[/C][C]103.54[/C][C]103.3[/C][C]103.684[/C][C]103.3[/C][/ROW]
[ROW][C]0.24[/C][C]103.788[/C][C]103.836[/C][C]103.9[/C][C]103.9[/C][C]104.02[/C][C]103.7[/C][C]103.764[/C][C]103.9[/C][/ROW]
[ROW][C]0.26[/C][C]104.608[/C][C]105.076[/C][C]106.3[/C][C]106.3[/C][C]105.94[/C][C]104.5[/C][C]105.724[/C][C]104.5[/C][/ROW]
[ROW][C]0.28[/C][C]106.436[/C][C]106.492[/C][C]106.5[/C][C]106.5[/C][C]106.5[/C][C]106.5[/C][C]106.308[/C][C]106.5[/C][/ROW]
[ROW][C]0.3[/C][C]106.56[/C][C]106.62[/C][C]106.7[/C][C]106.7[/C][C]106.7[/C][C]106.5[/C][C]106.58[/C][C]106.7[/C][/ROW]
[ROW][C]0.32[/C][C]107.344[/C][C]107.472[/C][C]107.4[/C][C]107.4[/C][C]107.58[/C][C]107.4[/C][C]107.628[/C][C]107.4[/C][/ROW]
[ROW][C]0.34[/C][C]107.754[/C][C]107.788[/C][C]107.8[/C][C]107.8[/C][C]107.86[/C][C]107.8[/C][C]107.712[/C][C]107.8[/C][/ROW]
[ROW][C]0.36[/C][C]108.212[/C][C]108.464[/C][C]108.8[/C][C]108.8[/C][C]108.66[/C][C]108.1[/C][C]108.436[/C][C]108.8[/C][/ROW]
[ROW][C]0.38[/C][C]109.424[/C][C]109.6[/C][C]109.6[/C][C]109.6[/C][C]109.6[/C][C]109.6[/C][C]109.6[/C][C]109.6[/C][/ROW]
[ROW][C]0.4[/C][C]109.76[/C][C]109.92[/C][C]110[/C][C]110[/C][C]110[/C][C]109.6[/C][C]109.68[/C][C]110[/C][/ROW]
[ROW][C]0.42[/C][C]110.314[/C][C]110.608[/C][C]111[/C][C]111[/C][C]110.72[/C][C]110.3[/C][C]110.692[/C][C]110.3[/C][/ROW]
[ROW][C]0.44[/C][C]111.064[/C][C]111.116[/C][C]111.1[/C][C]111.1[/C][C]111.14[/C][C]111.1[/C][C]111.284[/C][C]111.1[/C][/ROW]
[ROW][C]0.46[/C][C]111.326[/C][C]111.372[/C][C]111.4[/C][C]111.4[/C][C]111.38[/C][C]111.3[/C][C]111.328[/C][C]111.4[/C][/ROW]
[ROW][C]0.48[/C][C]111.576[/C][C]111.636[/C][C]111.6[/C][C]111.6[/C][C]111.64[/C][C]111.6[/C][C]111.664[/C][C]111.6[/C][/ROW]
[ROW][C]0.5[/C][C]111.75[/C][C]111.8[/C][C]111.8[/C][C]111.8[/C][C]111.8[/C][C]111.8[/C][C]111.8[/C][C]111.8[/C][/ROW]
[ROW][C]0.52[/C][C]112.672[/C][C]112.984[/C][C]113.2[/C][C]113.2[/C][C]112.96[/C][C]112.6[/C][C]112.816[/C][C]113.2[/C][/ROW]
[ROW][C]0.54[/C][C]113.94[/C][C]114.34[/C][C]114.2[/C][C]114.2[/C][C]114.3[/C][C]114.2[/C][C]114.56[/C][C]114.2[/C][/ROW]
[ROW][C]0.56[/C][C]114.88[/C][C]115.16[/C][C]115.2[/C][C]115.2[/C][C]115.1[/C][C]114.7[/C][C]114.74[/C][C]115.2[/C][/ROW]
[ROW][C]0.58[/C][C]115.788[/C][C]115.912[/C][C]115.8[/C][C]115.8[/C][C]115.88[/C][C]115.8[/C][C]115.888[/C][C]116[/C][/ROW]
[ROW][C]0.6[/C][C]116.12[/C][C]116.26[/C][C]116.2[/C][C]116.2[/C][C]116.2[/C][C]116.2[/C][C]116.44[/C][C]116.2[/C][/ROW]
[ROW][C]0.62[/C][C]116.544[/C][C]116.668[/C][C]116.7[/C][C]116.7[/C][C]116.62[/C][C]116.5[/C][C]116.532[/C][C]116.7[/C][/ROW]
[ROW][C]0.64[/C][C]117.624[/C][C]118.136[/C][C]117.8[/C][C]117.8[/C][C]117.94[/C][C]117.8[/C][C]118.164[/C][C]117.8[/C][/ROW]
[ROW][C]0.66[/C][C]118.5[/C][C]118.536[/C][C]118.5[/C][C]118.5[/C][C]118.5[/C][C]118.5[/C][C]118.764[/C][C]118.5[/C][/ROW]
[ROW][C]0.68[/C][C]118.8[/C][C]118.8[/C][C]118.8[/C][C]118.8[/C][C]118.8[/C][C]118.8[/C][C]118.8[/C][C]118.8[/C][/ROW]
[ROW][C]0.7[/C][C]119.01[/C][C]119.22[/C][C]119.1[/C][C]119.1[/C][C]119.1[/C][C]119.1[/C][C]119.28[/C][C]119.1[/C][/ROW]
[ROW][C]0.72[/C][C]119.4[/C][C]119.408[/C][C]119.4[/C][C]119.4[/C][C]119.4[/C][C]119.4[/C][C]119.592[/C][C]119.4[/C][/ROW]
[ROW][C]0.74[/C][C]119.588[/C][C]119.94[/C][C]119.6[/C][C]119.6[/C][C]119.7[/C][C]119.6[/C][C]119.76[/C][C]120.1[/C][/ROW]
[ROW][C]0.76[/C][C]120.1[/C][C]120.356[/C][C]120.1[/C][C]120.1[/C][C]120.1[/C][C]120.1[/C][C]120.644[/C][C]120.1[/C][/ROW]
[ROW][C]0.78[/C][C]121.26[/C][C]122.82[/C][C]122.9[/C][C]122.9[/C][C]121.7[/C][C]120.9[/C][C]120.98[/C][C]122.9[/C][/ROW]
[ROW][C]0.8[/C][C]122.9[/C][C]123.26[/C][C]122.9[/C][C]122.9[/C][C]122.9[/C][C]122.9[/C][C]123.14[/C][C]123.5[/C][/ROW]
[ROW][C]0.82[/C][C]123.668[/C][C]123.924[/C][C]123.9[/C][C]123.9[/C][C]123.74[/C][C]123.5[/C][C]123.976[/C][C]123.9[/C][/ROW]
[ROW][C]0.84[/C][C]124.024[/C][C]124.528[/C][C]124.6[/C][C]124.6[/C][C]124.12[/C][C]124[/C][C]124.072[/C][C]124.6[/C][/ROW]
[ROW][C]0.86[/C][C]124.732[/C][C]125.424[/C][C]124.8[/C][C]124.8[/C][C]124.76[/C][C]124.8[/C][C]125.376[/C][C]126[/C][/ROW]
[ROW][C]0.88[/C][C]126.084[/C][C]126.332[/C][C]126.3[/C][C]126.3[/C][C]126.12[/C][C]126[/C][C]126.468[/C][C]126.3[/C][/ROW]
[ROW][C]0.9[/C][C]126.48[/C][C]126.9[/C][C]126.5[/C][C]126.5[/C][C]126.5[/C][C]126.5[/C][C]126.6[/C][C]127[/C][/ROW]
[ROW][C]0.92[/C][C]127.208[/C][C]127.532[/C][C]127.4[/C][C]127.4[/C][C]127.24[/C][C]127.4[/C][C]127.568[/C][C]127.4[/C][/ROW]
[ROW][C]0.94[/C][C]127.826[/C][C]128.608[/C][C]128.6[/C][C]128.6[/C][C]127.88[/C][C]127.7[/C][C]128.692[/C][C]128.6[/C][/ROW]
[ROW][C]0.96[/C][C]128.676[/C][C]129.276[/C][C]128.7[/C][C]128.7[/C][C]128.68[/C][C]128.7[/C][C]128.924[/C][C]129.5[/C][/ROW]
[ROW][C]0.98[/C][C]129.538[/C][C]129.96[/C][C]129.6[/C][C]129.6[/C][C]129.54[/C][C]129.5[/C][C]130.24[/C][C]129.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32891&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32891&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)
0.0295.36895.39695.995.996.2695.995.00495.9
0.0496.6296.64979797.1896.596.8696.5
0.0697.77497.82897.997.998.3897.997.07297.9
0.0899.02899.11699.699.699.698.598.98499.6
0.199.6299.6499.899.899.899.699.7699.6
0.12100.016100.052100.1100.1100.4100.199.848100.1
0.14100.804100.888101.2101.2101.34100.6100.912100.6
0.16101.872102.008101.9101.9102.62101.9102.692101.9
0.18102.858102.876102.9102.9102.94102.9102.824102.9
0.2103.06103.12103.3103.3103.3103103.18103
0.22103.3103.316103.3103.3103.54103.3103.684103.3
0.24103.788103.836103.9103.9104.02103.7103.764103.9
0.26104.608105.076106.3106.3105.94104.5105.724104.5
0.28106.436106.492106.5106.5106.5106.5106.308106.5
0.3106.56106.62106.7106.7106.7106.5106.58106.7
0.32107.344107.472107.4107.4107.58107.4107.628107.4
0.34107.754107.788107.8107.8107.86107.8107.712107.8
0.36108.212108.464108.8108.8108.66108.1108.436108.8
0.38109.424109.6109.6109.6109.6109.6109.6109.6
0.4109.76109.92110110110109.6109.68110
0.42110.314110.608111111110.72110.3110.692110.3
0.44111.064111.116111.1111.1111.14111.1111.284111.1
0.46111.326111.372111.4111.4111.38111.3111.328111.4
0.48111.576111.636111.6111.6111.64111.6111.664111.6
0.5111.75111.8111.8111.8111.8111.8111.8111.8
0.52112.672112.984113.2113.2112.96112.6112.816113.2
0.54113.94114.34114.2114.2114.3114.2114.56114.2
0.56114.88115.16115.2115.2115.1114.7114.74115.2
0.58115.788115.912115.8115.8115.88115.8115.888116
0.6116.12116.26116.2116.2116.2116.2116.44116.2
0.62116.544116.668116.7116.7116.62116.5116.532116.7
0.64117.624118.136117.8117.8117.94117.8118.164117.8
0.66118.5118.536118.5118.5118.5118.5118.764118.5
0.68118.8118.8118.8118.8118.8118.8118.8118.8
0.7119.01119.22119.1119.1119.1119.1119.28119.1
0.72119.4119.408119.4119.4119.4119.4119.592119.4
0.74119.588119.94119.6119.6119.7119.6119.76120.1
0.76120.1120.356120.1120.1120.1120.1120.644120.1
0.78121.26122.82122.9122.9121.7120.9120.98122.9
0.8122.9123.26122.9122.9122.9122.9123.14123.5
0.82123.668123.924123.9123.9123.74123.5123.976123.9
0.84124.024124.528124.6124.6124.12124124.072124.6
0.86124.732125.424124.8124.8124.76124.8125.376126
0.88126.084126.332126.3126.3126.12126126.468126.3
0.9126.48126.9126.5126.5126.5126.5126.6127
0.92127.208127.532127.4127.4127.24127.4127.568127.4
0.94127.826128.608128.6128.6127.88127.7128.692128.6
0.96128.676129.276128.7128.7128.68128.7128.924129.5
0.98129.538129.96129.6129.6129.54129.5130.24129.6



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')