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 computationMon, 20 Oct 2008 11:54:58 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t1224525457edh6lnk5t7c0txu.htm/, Retrieved Sun, 19 May 2024 13:21:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17805, Retrieved Sun, 19 May 2024 13:21:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Pearson Correlation] [Investigating Ass...] [2008-10-20 14:53:02] [79c17183721a40a589db5f9f561947d8]
-    D  [Pearson Correlation] [Investigating Ass...] [2008-10-20 15:13:17] [79c17183721a40a589db5f9f561947d8]
F RM D      [Percentiles] [Investigating Ass...] [2008-10-20 17:54:58] [3bb0537fcae9c337e49b9ce75ff3d4da] [Current]
Feedback Forum
2008-10-27 11:10:23 [Steven Hulsmans] [reply
Berekening correct uitgevoerd. Indien we gaan kijken bij 0,10 in de 5e kolom kunnen we afleiden dat ongeveer 10% van de data eronder ligt, terwijl 90% erboven.

Post a new message
Dataseries X:
110,40
96,40
101,90
106,20
81,00
94,70
101,00
109,40
102,30
90,70
96,20
96,10
106,00
103,10
102,00
104,70
86,00
92,10
106,90
112,60
101,70
92,00
97,40
97,00
105,40
102,70
98,10
104,50
87,40
89,90
109,80
111,70
98,60
96,90
95,10
97,00
112,70
102,90
97,40
111,40
87,40
96,80
114,10
110,30
103,90
101,60
94,60
95,90
104,70
102,80
98,10
113,90
80,90
95,70
113,20
105,90
108,80
102,30
99,00
100,70
115,50




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17805&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17805&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17805&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







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)
0.0280.92280.92481818280.980.97680.9
0.0483.283.4868686.568183.681
0.0686.92487.00887.487.487.487.486.39287.4
0.0887.487.487.487.489.487.487.487.4
0.189.9890.0690.790.790.789.990.5489.9
0.1291.11691.272929292.0290.791.42890.7
0.1492.05492.06892.192.193.192.192.03292.1
0.169494.494.694.694.6694.692.394.6
0.1894.69894.76494.794.795.0294.795.03694.7
0.295.2295.3495.795.795.795.195.4695.1
0.2295.78495.82895.995.995.9495.795.77295.9
0.2496.02896.07696.196.196.1496.195.92496.1
0.2696.18696.22496.296.296.3296.296.37696.2
0.2896.43296.54496.896.896.7296.496.65696.4
0.396.8396.8696.996.996.996.896.8496.9
0.3296.95296.9849797979796.91697
0.349797.032979797.169797.36897
0.3697.38497.497.497.497.497.497.497.4
0.3897.52697.79298.198.197.9697.497.70898.1
0.498.198.198.198.198.198.198.198.1
0.4298.4198.61698.698.698.6898.698.98498.6
0.4498.93699.476999999.6899100.22499
0.46100.718100.856101101100.88100.7100.844101
0.48101.168101.456101.6101.6101.48101101.144101.6
0.5101.65101.7101.7101.7101.7101.7101.7101.7
0.52101.844101.924101.9101.9101.92101.9101.976101.9
0.54101.994102.144102102102.12102102.156102
0.56102.3102.3102.3102.3102.3102.3102.3102.3
0.58102.452102.684102.7102.7102.62102.3102.316102.7
0.6102.76102.82102.8102.8102.8102.8102.88102.8
0.62102.882102.988102.9102.9102.94102.9103.012102.9
0.64103.132103.644103.9103.9103.42103.1103.356103.9
0.66104.056104.452104.5104.5104.26103.9103.948104.5
0.68104.596104.7104.7104.7104.66104.5104.7104.7
0.7104.7104.98104.7104.7104.7104.7105.12104.7
0.72105.344105.72105.4105.4105.5105.4105.58105.9
0.74105.914105.988106106105.94105.9105.912106
0.76106.072106.284106.2106.2106.12106106.816106.2
0.78106.606107.584106.9106.9106.76106.9108.116106.9
0.8108.42109.16108.8108.8108.8108.8109.04109.4
0.82109.408109.736109.8109.8109.48109.4109.464109.8
0.84109.92110.308110.3110.3110109.8110.392110.3
0.86110.346110.72110.4110.4110.36110.3111.08110.4
0.88111.08111.568111.4111.4111.2111.4111.532111.7
0.9111.67112.42111.7111.7111.7111.7111.88112.6
0.92112.612112.72112.7112.7112.62112.6113.18112.7
0.94112.87113.396113.2113.2112.9112.7113.704113.2
0.96113.592114.004113.9113.9113.62113.9113.996114.1
0.98114.056115.164114.1114.1114.06114.1114.436115.5

\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 & 80.922 & 80.924 & 81 & 81 & 82 & 80.9 & 80.976 & 80.9 \tabularnewline
0.04 & 83.2 & 83.4 & 86 & 86 & 86.56 & 81 & 83.6 & 81 \tabularnewline
0.06 & 86.924 & 87.008 & 87.4 & 87.4 & 87.4 & 87.4 & 86.392 & 87.4 \tabularnewline
0.08 & 87.4 & 87.4 & 87.4 & 87.4 & 89.4 & 87.4 & 87.4 & 87.4 \tabularnewline
0.1 & 89.98 & 90.06 & 90.7 & 90.7 & 90.7 & 89.9 & 90.54 & 89.9 \tabularnewline
0.12 & 91.116 & 91.272 & 92 & 92 & 92.02 & 90.7 & 91.428 & 90.7 \tabularnewline
0.14 & 92.054 & 92.068 & 92.1 & 92.1 & 93.1 & 92.1 & 92.032 & 92.1 \tabularnewline
0.16 & 94 & 94.4 & 94.6 & 94.6 & 94.66 & 94.6 & 92.3 & 94.6 \tabularnewline
0.18 & 94.698 & 94.764 & 94.7 & 94.7 & 95.02 & 94.7 & 95.036 & 94.7 \tabularnewline
0.2 & 95.22 & 95.34 & 95.7 & 95.7 & 95.7 & 95.1 & 95.46 & 95.1 \tabularnewline
0.22 & 95.784 & 95.828 & 95.9 & 95.9 & 95.94 & 95.7 & 95.772 & 95.9 \tabularnewline
0.24 & 96.028 & 96.076 & 96.1 & 96.1 & 96.14 & 96.1 & 95.924 & 96.1 \tabularnewline
0.26 & 96.186 & 96.224 & 96.2 & 96.2 & 96.32 & 96.2 & 96.376 & 96.2 \tabularnewline
0.28 & 96.432 & 96.544 & 96.8 & 96.8 & 96.72 & 96.4 & 96.656 & 96.4 \tabularnewline
0.3 & 96.83 & 96.86 & 96.9 & 96.9 & 96.9 & 96.8 & 96.84 & 96.9 \tabularnewline
0.32 & 96.952 & 96.984 & 97 & 97 & 97 & 97 & 96.916 & 97 \tabularnewline
0.34 & 97 & 97.032 & 97 & 97 & 97.16 & 97 & 97.368 & 97 \tabularnewline
0.36 & 97.384 & 97.4 & 97.4 & 97.4 & 97.4 & 97.4 & 97.4 & 97.4 \tabularnewline
0.38 & 97.526 & 97.792 & 98.1 & 98.1 & 97.96 & 97.4 & 97.708 & 98.1 \tabularnewline
0.4 & 98.1 & 98.1 & 98.1 & 98.1 & 98.1 & 98.1 & 98.1 & 98.1 \tabularnewline
0.42 & 98.41 & 98.616 & 98.6 & 98.6 & 98.68 & 98.6 & 98.984 & 98.6 \tabularnewline
0.44 & 98.936 & 99.476 & 99 & 99 & 99.68 & 99 & 100.224 & 99 \tabularnewline
0.46 & 100.718 & 100.856 & 101 & 101 & 100.88 & 100.7 & 100.844 & 101 \tabularnewline
0.48 & 101.168 & 101.456 & 101.6 & 101.6 & 101.48 & 101 & 101.144 & 101.6 \tabularnewline
0.5 & 101.65 & 101.7 & 101.7 & 101.7 & 101.7 & 101.7 & 101.7 & 101.7 \tabularnewline
0.52 & 101.844 & 101.924 & 101.9 & 101.9 & 101.92 & 101.9 & 101.976 & 101.9 \tabularnewline
0.54 & 101.994 & 102.144 & 102 & 102 & 102.12 & 102 & 102.156 & 102 \tabularnewline
0.56 & 102.3 & 102.3 & 102.3 & 102.3 & 102.3 & 102.3 & 102.3 & 102.3 \tabularnewline
0.58 & 102.452 & 102.684 & 102.7 & 102.7 & 102.62 & 102.3 & 102.316 & 102.7 \tabularnewline
0.6 & 102.76 & 102.82 & 102.8 & 102.8 & 102.8 & 102.8 & 102.88 & 102.8 \tabularnewline
0.62 & 102.882 & 102.988 & 102.9 & 102.9 & 102.94 & 102.9 & 103.012 & 102.9 \tabularnewline
0.64 & 103.132 & 103.644 & 103.9 & 103.9 & 103.42 & 103.1 & 103.356 & 103.9 \tabularnewline
0.66 & 104.056 & 104.452 & 104.5 & 104.5 & 104.26 & 103.9 & 103.948 & 104.5 \tabularnewline
0.68 & 104.596 & 104.7 & 104.7 & 104.7 & 104.66 & 104.5 & 104.7 & 104.7 \tabularnewline
0.7 & 104.7 & 104.98 & 104.7 & 104.7 & 104.7 & 104.7 & 105.12 & 104.7 \tabularnewline
0.72 & 105.344 & 105.72 & 105.4 & 105.4 & 105.5 & 105.4 & 105.58 & 105.9 \tabularnewline
0.74 & 105.914 & 105.988 & 106 & 106 & 105.94 & 105.9 & 105.912 & 106 \tabularnewline
0.76 & 106.072 & 106.284 & 106.2 & 106.2 & 106.12 & 106 & 106.816 & 106.2 \tabularnewline
0.78 & 106.606 & 107.584 & 106.9 & 106.9 & 106.76 & 106.9 & 108.116 & 106.9 \tabularnewline
0.8 & 108.42 & 109.16 & 108.8 & 108.8 & 108.8 & 108.8 & 109.04 & 109.4 \tabularnewline
0.82 & 109.408 & 109.736 & 109.8 & 109.8 & 109.48 & 109.4 & 109.464 & 109.8 \tabularnewline
0.84 & 109.92 & 110.308 & 110.3 & 110.3 & 110 & 109.8 & 110.392 & 110.3 \tabularnewline
0.86 & 110.346 & 110.72 & 110.4 & 110.4 & 110.36 & 110.3 & 111.08 & 110.4 \tabularnewline
0.88 & 111.08 & 111.568 & 111.4 & 111.4 & 111.2 & 111.4 & 111.532 & 111.7 \tabularnewline
0.9 & 111.67 & 112.42 & 111.7 & 111.7 & 111.7 & 111.7 & 111.88 & 112.6 \tabularnewline
0.92 & 112.612 & 112.72 & 112.7 & 112.7 & 112.62 & 112.6 & 113.18 & 112.7 \tabularnewline
0.94 & 112.87 & 113.396 & 113.2 & 113.2 & 112.9 & 112.7 & 113.704 & 113.2 \tabularnewline
0.96 & 113.592 & 114.004 & 113.9 & 113.9 & 113.62 & 113.9 & 113.996 & 114.1 \tabularnewline
0.98 & 114.056 & 115.164 & 114.1 & 114.1 & 114.06 & 114.1 & 114.436 & 115.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17805&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]80.922[/C][C]80.924[/C][C]81[/C][C]81[/C][C]82[/C][C]80.9[/C][C]80.976[/C][C]80.9[/C][/ROW]
[ROW][C]0.04[/C][C]83.2[/C][C]83.4[/C][C]86[/C][C]86[/C][C]86.56[/C][C]81[/C][C]83.6[/C][C]81[/C][/ROW]
[ROW][C]0.06[/C][C]86.924[/C][C]87.008[/C][C]87.4[/C][C]87.4[/C][C]87.4[/C][C]87.4[/C][C]86.392[/C][C]87.4[/C][/ROW]
[ROW][C]0.08[/C][C]87.4[/C][C]87.4[/C][C]87.4[/C][C]87.4[/C][C]89.4[/C][C]87.4[/C][C]87.4[/C][C]87.4[/C][/ROW]
[ROW][C]0.1[/C][C]89.98[/C][C]90.06[/C][C]90.7[/C][C]90.7[/C][C]90.7[/C][C]89.9[/C][C]90.54[/C][C]89.9[/C][/ROW]
[ROW][C]0.12[/C][C]91.116[/C][C]91.272[/C][C]92[/C][C]92[/C][C]92.02[/C][C]90.7[/C][C]91.428[/C][C]90.7[/C][/ROW]
[ROW][C]0.14[/C][C]92.054[/C][C]92.068[/C][C]92.1[/C][C]92.1[/C][C]93.1[/C][C]92.1[/C][C]92.032[/C][C]92.1[/C][/ROW]
[ROW][C]0.16[/C][C]94[/C][C]94.4[/C][C]94.6[/C][C]94.6[/C][C]94.66[/C][C]94.6[/C][C]92.3[/C][C]94.6[/C][/ROW]
[ROW][C]0.18[/C][C]94.698[/C][C]94.764[/C][C]94.7[/C][C]94.7[/C][C]95.02[/C][C]94.7[/C][C]95.036[/C][C]94.7[/C][/ROW]
[ROW][C]0.2[/C][C]95.22[/C][C]95.34[/C][C]95.7[/C][C]95.7[/C][C]95.7[/C][C]95.1[/C][C]95.46[/C][C]95.1[/C][/ROW]
[ROW][C]0.22[/C][C]95.784[/C][C]95.828[/C][C]95.9[/C][C]95.9[/C][C]95.94[/C][C]95.7[/C][C]95.772[/C][C]95.9[/C][/ROW]
[ROW][C]0.24[/C][C]96.028[/C][C]96.076[/C][C]96.1[/C][C]96.1[/C][C]96.14[/C][C]96.1[/C][C]95.924[/C][C]96.1[/C][/ROW]
[ROW][C]0.26[/C][C]96.186[/C][C]96.224[/C][C]96.2[/C][C]96.2[/C][C]96.32[/C][C]96.2[/C][C]96.376[/C][C]96.2[/C][/ROW]
[ROW][C]0.28[/C][C]96.432[/C][C]96.544[/C][C]96.8[/C][C]96.8[/C][C]96.72[/C][C]96.4[/C][C]96.656[/C][C]96.4[/C][/ROW]
[ROW][C]0.3[/C][C]96.83[/C][C]96.86[/C][C]96.9[/C][C]96.9[/C][C]96.9[/C][C]96.8[/C][C]96.84[/C][C]96.9[/C][/ROW]
[ROW][C]0.32[/C][C]96.952[/C][C]96.984[/C][C]97[/C][C]97[/C][C]97[/C][C]97[/C][C]96.916[/C][C]97[/C][/ROW]
[ROW][C]0.34[/C][C]97[/C][C]97.032[/C][C]97[/C][C]97[/C][C]97.16[/C][C]97[/C][C]97.368[/C][C]97[/C][/ROW]
[ROW][C]0.36[/C][C]97.384[/C][C]97.4[/C][C]97.4[/C][C]97.4[/C][C]97.4[/C][C]97.4[/C][C]97.4[/C][C]97.4[/C][/ROW]
[ROW][C]0.38[/C][C]97.526[/C][C]97.792[/C][C]98.1[/C][C]98.1[/C][C]97.96[/C][C]97.4[/C][C]97.708[/C][C]98.1[/C][/ROW]
[ROW][C]0.4[/C][C]98.1[/C][C]98.1[/C][C]98.1[/C][C]98.1[/C][C]98.1[/C][C]98.1[/C][C]98.1[/C][C]98.1[/C][/ROW]
[ROW][C]0.42[/C][C]98.41[/C][C]98.616[/C][C]98.6[/C][C]98.6[/C][C]98.68[/C][C]98.6[/C][C]98.984[/C][C]98.6[/C][/ROW]
[ROW][C]0.44[/C][C]98.936[/C][C]99.476[/C][C]99[/C][C]99[/C][C]99.68[/C][C]99[/C][C]100.224[/C][C]99[/C][/ROW]
[ROW][C]0.46[/C][C]100.718[/C][C]100.856[/C][C]101[/C][C]101[/C][C]100.88[/C][C]100.7[/C][C]100.844[/C][C]101[/C][/ROW]
[ROW][C]0.48[/C][C]101.168[/C][C]101.456[/C][C]101.6[/C][C]101.6[/C][C]101.48[/C][C]101[/C][C]101.144[/C][C]101.6[/C][/ROW]
[ROW][C]0.5[/C][C]101.65[/C][C]101.7[/C][C]101.7[/C][C]101.7[/C][C]101.7[/C][C]101.7[/C][C]101.7[/C][C]101.7[/C][/ROW]
[ROW][C]0.52[/C][C]101.844[/C][C]101.924[/C][C]101.9[/C][C]101.9[/C][C]101.92[/C][C]101.9[/C][C]101.976[/C][C]101.9[/C][/ROW]
[ROW][C]0.54[/C][C]101.994[/C][C]102.144[/C][C]102[/C][C]102[/C][C]102.12[/C][C]102[/C][C]102.156[/C][C]102[/C][/ROW]
[ROW][C]0.56[/C][C]102.3[/C][C]102.3[/C][C]102.3[/C][C]102.3[/C][C]102.3[/C][C]102.3[/C][C]102.3[/C][C]102.3[/C][/ROW]
[ROW][C]0.58[/C][C]102.452[/C][C]102.684[/C][C]102.7[/C][C]102.7[/C][C]102.62[/C][C]102.3[/C][C]102.316[/C][C]102.7[/C][/ROW]
[ROW][C]0.6[/C][C]102.76[/C][C]102.82[/C][C]102.8[/C][C]102.8[/C][C]102.8[/C][C]102.8[/C][C]102.88[/C][C]102.8[/C][/ROW]
[ROW][C]0.62[/C][C]102.882[/C][C]102.988[/C][C]102.9[/C][C]102.9[/C][C]102.94[/C][C]102.9[/C][C]103.012[/C][C]102.9[/C][/ROW]
[ROW][C]0.64[/C][C]103.132[/C][C]103.644[/C][C]103.9[/C][C]103.9[/C][C]103.42[/C][C]103.1[/C][C]103.356[/C][C]103.9[/C][/ROW]
[ROW][C]0.66[/C][C]104.056[/C][C]104.452[/C][C]104.5[/C][C]104.5[/C][C]104.26[/C][C]103.9[/C][C]103.948[/C][C]104.5[/C][/ROW]
[ROW][C]0.68[/C][C]104.596[/C][C]104.7[/C][C]104.7[/C][C]104.7[/C][C]104.66[/C][C]104.5[/C][C]104.7[/C][C]104.7[/C][/ROW]
[ROW][C]0.7[/C][C]104.7[/C][C]104.98[/C][C]104.7[/C][C]104.7[/C][C]104.7[/C][C]104.7[/C][C]105.12[/C][C]104.7[/C][/ROW]
[ROW][C]0.72[/C][C]105.344[/C][C]105.72[/C][C]105.4[/C][C]105.4[/C][C]105.5[/C][C]105.4[/C][C]105.58[/C][C]105.9[/C][/ROW]
[ROW][C]0.74[/C][C]105.914[/C][C]105.988[/C][C]106[/C][C]106[/C][C]105.94[/C][C]105.9[/C][C]105.912[/C][C]106[/C][/ROW]
[ROW][C]0.76[/C][C]106.072[/C][C]106.284[/C][C]106.2[/C][C]106.2[/C][C]106.12[/C][C]106[/C][C]106.816[/C][C]106.2[/C][/ROW]
[ROW][C]0.78[/C][C]106.606[/C][C]107.584[/C][C]106.9[/C][C]106.9[/C][C]106.76[/C][C]106.9[/C][C]108.116[/C][C]106.9[/C][/ROW]
[ROW][C]0.8[/C][C]108.42[/C][C]109.16[/C][C]108.8[/C][C]108.8[/C][C]108.8[/C][C]108.8[/C][C]109.04[/C][C]109.4[/C][/ROW]
[ROW][C]0.82[/C][C]109.408[/C][C]109.736[/C][C]109.8[/C][C]109.8[/C][C]109.48[/C][C]109.4[/C][C]109.464[/C][C]109.8[/C][/ROW]
[ROW][C]0.84[/C][C]109.92[/C][C]110.308[/C][C]110.3[/C][C]110.3[/C][C]110[/C][C]109.8[/C][C]110.392[/C][C]110.3[/C][/ROW]
[ROW][C]0.86[/C][C]110.346[/C][C]110.72[/C][C]110.4[/C][C]110.4[/C][C]110.36[/C][C]110.3[/C][C]111.08[/C][C]110.4[/C][/ROW]
[ROW][C]0.88[/C][C]111.08[/C][C]111.568[/C][C]111.4[/C][C]111.4[/C][C]111.2[/C][C]111.4[/C][C]111.532[/C][C]111.7[/C][/ROW]
[ROW][C]0.9[/C][C]111.67[/C][C]112.42[/C][C]111.7[/C][C]111.7[/C][C]111.7[/C][C]111.7[/C][C]111.88[/C][C]112.6[/C][/ROW]
[ROW][C]0.92[/C][C]112.612[/C][C]112.72[/C][C]112.7[/C][C]112.7[/C][C]112.62[/C][C]112.6[/C][C]113.18[/C][C]112.7[/C][/ROW]
[ROW][C]0.94[/C][C]112.87[/C][C]113.396[/C][C]113.2[/C][C]113.2[/C][C]112.9[/C][C]112.7[/C][C]113.704[/C][C]113.2[/C][/ROW]
[ROW][C]0.96[/C][C]113.592[/C][C]114.004[/C][C]113.9[/C][C]113.9[/C][C]113.62[/C][C]113.9[/C][C]113.996[/C][C]114.1[/C][/ROW]
[ROW][C]0.98[/C][C]114.056[/C][C]115.164[/C][C]114.1[/C][C]114.1[/C][C]114.06[/C][C]114.1[/C][C]114.436[/C][C]115.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17805&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17805&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)
0.0280.92280.92481818280.980.97680.9
0.0483.283.4868686.568183.681
0.0686.92487.00887.487.487.487.486.39287.4
0.0887.487.487.487.489.487.487.487.4
0.189.9890.0690.790.790.789.990.5489.9
0.1291.11691.272929292.0290.791.42890.7
0.1492.05492.06892.192.193.192.192.03292.1
0.169494.494.694.694.6694.692.394.6
0.1894.69894.76494.794.795.0294.795.03694.7
0.295.2295.3495.795.795.795.195.4695.1
0.2295.78495.82895.995.995.9495.795.77295.9
0.2496.02896.07696.196.196.1496.195.92496.1
0.2696.18696.22496.296.296.3296.296.37696.2
0.2896.43296.54496.896.896.7296.496.65696.4
0.396.8396.8696.996.996.996.896.8496.9
0.3296.95296.9849797979796.91697
0.349797.032979797.169797.36897
0.3697.38497.497.497.497.497.497.497.4
0.3897.52697.79298.198.197.9697.497.70898.1
0.498.198.198.198.198.198.198.198.1
0.4298.4198.61698.698.698.6898.698.98498.6
0.4498.93699.476999999.6899100.22499
0.46100.718100.856101101100.88100.7100.844101
0.48101.168101.456101.6101.6101.48101101.144101.6
0.5101.65101.7101.7101.7101.7101.7101.7101.7
0.52101.844101.924101.9101.9101.92101.9101.976101.9
0.54101.994102.144102102102.12102102.156102
0.56102.3102.3102.3102.3102.3102.3102.3102.3
0.58102.452102.684102.7102.7102.62102.3102.316102.7
0.6102.76102.82102.8102.8102.8102.8102.88102.8
0.62102.882102.988102.9102.9102.94102.9103.012102.9
0.64103.132103.644103.9103.9103.42103.1103.356103.9
0.66104.056104.452104.5104.5104.26103.9103.948104.5
0.68104.596104.7104.7104.7104.66104.5104.7104.7
0.7104.7104.98104.7104.7104.7104.7105.12104.7
0.72105.344105.72105.4105.4105.5105.4105.58105.9
0.74105.914105.988106106105.94105.9105.912106
0.76106.072106.284106.2106.2106.12106106.816106.2
0.78106.606107.584106.9106.9106.76106.9108.116106.9
0.8108.42109.16108.8108.8108.8108.8109.04109.4
0.82109.408109.736109.8109.8109.48109.4109.464109.8
0.84109.92110.308110.3110.3110109.8110.392110.3
0.86110.346110.72110.4110.4110.36110.3111.08110.4
0.88111.08111.568111.4111.4111.2111.4111.532111.7
0.9111.67112.42111.7111.7111.7111.7111.88112.6
0.92112.612112.72112.7112.7112.62112.6113.18112.7
0.94112.87113.396113.2113.2112.9112.7113.704113.2
0.96113.592114.004113.9113.9113.62113.9113.996114.1
0.98114.056115.164114.1114.1114.06114.1114.436115.5



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')