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 computationMon, 20 Oct 2008 09:05:54 -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/t12245151945q0jck19vl2u5zq.htm/, Retrieved Sun, 19 May 2024 14:46:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17426, Retrieved Sun, 19 May 2024 14:46:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Percentiles] [Q6] [2008-10-20 15:05:54] [5f3e73ccf1ddc75508eed47fa51813d3] [Current]
Feedback Forum
2008-10-27 10:35:21 [Stéphanie Thijs] [reply
De berekening en de methode zijn juist. De student had wel nog 10% van elke staart moeten afhouden. De waarden die overeenkomen met het 0,1ste percentiel en het 0,9de percentiel vormen het betrouwbaarheidsinterval van 80%, nl [89,98; 111,67]. D.w.z. dat er 80% kans bestaat dat een waarde van deze dataset zich tussen deze twee waarden gaat bevinden.
2008-10-27 16:44:11 [Bernard Femont] [reply
Het betrouwbaarheidsinterval wordt gevormd door 10 % van beide staarten van de reeks eraf te doen (begin en einde) hierdoor verkrijgt men een kans dat er 80% van de waardes van de dataset hierbinnen zullen liggen.
De data is correct ingegeven en geanalyseerd.
2008-10-27 18:40:36 [Nathalie Boden] [reply
We zien dat de berekeningen en de methodes correct zijn uitgevoerd. Wel moet er rekening gehouden worden dat er telkens 10% van de staart weghalen.Zo zien we dat er 80% kans bestaat dat de waarden van de totale productie tussen 89.98 en 111.67 liggen.

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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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17426&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17426&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17426&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.0280.92280.92481818280.980.97680.9
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=17426&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=17426&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17426&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')