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 computationThu, 23 Oct 2008 09:26:39 -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/23/t1224775627y06f43jhbcpvqnp.htm/, Retrieved Fri, 17 May 2024 12:55:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18540, Retrieved Fri, 17 May 2024 12:55:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Tukey lambda PPCC Plot] [Investigating Dis...] [2007-10-21 16:01:20] [b9964c45117f7aac638ab9056d451faa]
F RM D  [Percentiles] [QQ plot - Q1] [2008-10-23 15:01:52] [e5d91604aae608e98a8ea24759233f66]
F    D      [Percentiles] [QQ plot - Q2] [2008-10-23 15:26:39] [55ca0ca4a201c9689dcf5fae352c92eb] [Current]
Feedback Forum
2008-11-01 15:10:27 [Steffi Van Isveldt] [reply
Dit is een correcte berekening om aan te geven dat het hier om een normaalverdeling gaat. Zoals je zelf al aangaf, kan je dit ook via de grafiek van Density plot bekijken.
2008-11-02 21:45:31 [Bernard Femont] [reply
Je kan dit ook via de grafiek van Density plot bekijken. zoals hier wordt weergegeven
2008-11-02 21:46:18 [Bernard Femont] [reply
Je kan dit ook via de grafiek van Density plot bekijken. zoals hier idd wordt weergegeven

Post a new message
Dataseries X:
109.20
88.60
94.30
98.30
86.40
80.60
104.10
108.20
93.40
71.90
94.10
94.90
96.40
91.10
84.40
86.40
88.00
75.10
109.70
103.00
82.10
68.00
96.40
94.30
90.00
88.00
76.10
82.50
81.40
66.50
97.20
94.10
80.70
70.50
87.80
89.50
99.60
84.20
75.10
92.00
80.80
73.10
99.80
90.00
83.10
72.40
78.80
87.30
91.00
80.10
73.60
86.40
74.50
71.20
92.40
81.50
85.30
69.90
84.20
90.70
100.30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18540&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18540&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18540&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Percentiles - Ungrouped Data
pWeighted Average at XnpWeighted Average at X(n+1)pEmpirical Distribution FunctionEmpirical Distribution Function - AveragingEmpirical Distribution Function - InterpolationClosest ObservationTrue Basic - Statistics Graphics ToolkitMS Excel (old versions)
0.0266.8366.86686868.3866.567.6466.5
0.0468.83668.91269.969.970.146868.98868
0.0670.29670.33270.570.570.9270.570.06870.5
0.0871.11671.17271.271.271.7671.270.52871.2
0.171.957272.472.472.471.972.371.9
0.1272.62472.70873.173.173.272.472.79272.4
0.1473.3773.4473.673.673.9673.673.2673.6
0.1674.28474.42874.574.574.8674.573.67274.5
0.1875.08875.175.175.175.175.175.175.1
0.275.375.576.176.176.175.175.775.1
0.2277.23477.82878.878.879.0676.177.07278.8
0.2479.63279.94480.180.180.380.178.95680.1
0.2680.5380.61280.680.680.6680.680.68880.6
0.2880.70880.73680.880.880.7880.780.76480.7
0.380.9881.1681.481.481.480.881.0481.4
0.3281.45281.48481.581.581.6281.581.41681.5
0.3481.94482.13282.182.182.2682.182.46882.1
0.3682.48482.69282.582.582.8682.582.90882.5
0.3883.29883.71684.284.283.9883.183.58484.2
0.484.284.284.284.284.284.284.284.2
0.4284.32484.43684.484.484.5884.485.26484.4
0.4485.15685.60885.385.385.7485.386.09285.3
0.4686.486.486.486.486.486.486.486.4
0.4886.486.486.486.486.486.486.486.4
0.586.8587.387.387.387.387.387.387.3
0.5287.6687.84887.887.887.8487.887.95287.8
0.5487.98888888888888888
0.5688.09688.43288.688.688.368888.16888.6
0.5888.94289.46489.589.589.3288.688.63689.5
0.689.890909090909090
0.629090.308909090.149090.39290
0.6490.71290.904919190.8290.790.79691
0.6691.02691.09291.191.191.069191.00891.1
0.6891.53292.064929291.8291.192.33692
0.792.2892.892.492.492.492.49392.4
0.7293.3293.84893.493.493.5493.493.65294.1
0.7494.194.194.194.194.194.194.194.1
0.7694.17294.394.394.394.2294.194.394.3
0.7894.394.51694.394.394.394.394.68494.3
0.894.7895.894.994.994.994.995.596.4
0.8296.496.496.496.496.496.496.496.4
0.8496.59297.28897.297.296.7296.498.21297.2
0.8697.70698.71698.398.397.8697.299.18498.3
0.8899.18499.71299.699.699.3499.699.68899.8
0.999.78100.299.899.899.899.899.9100.3
0.92100.624103.044103103100.84100.3104.056103
0.94103.374105.248104.1104.1103.44103107.052104.1
0.96106.396108.72108.2108.2106.56108.2108.68109.2
0.98108.98109.58109.2109.2109109.2109.32109.7

\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 & 66.83 & 66.86 & 68 & 68 & 68.38 & 66.5 & 67.64 & 66.5 \tabularnewline
0.04 & 68.836 & 68.912 & 69.9 & 69.9 & 70.14 & 68 & 68.988 & 68 \tabularnewline
0.06 & 70.296 & 70.332 & 70.5 & 70.5 & 70.92 & 70.5 & 70.068 & 70.5 \tabularnewline
0.08 & 71.116 & 71.172 & 71.2 & 71.2 & 71.76 & 71.2 & 70.528 & 71.2 \tabularnewline
0.1 & 71.95 & 72 & 72.4 & 72.4 & 72.4 & 71.9 & 72.3 & 71.9 \tabularnewline
0.12 & 72.624 & 72.708 & 73.1 & 73.1 & 73.2 & 72.4 & 72.792 & 72.4 \tabularnewline
0.14 & 73.37 & 73.44 & 73.6 & 73.6 & 73.96 & 73.6 & 73.26 & 73.6 \tabularnewline
0.16 & 74.284 & 74.428 & 74.5 & 74.5 & 74.86 & 74.5 & 73.672 & 74.5 \tabularnewline
0.18 & 75.088 & 75.1 & 75.1 & 75.1 & 75.1 & 75.1 & 75.1 & 75.1 \tabularnewline
0.2 & 75.3 & 75.5 & 76.1 & 76.1 & 76.1 & 75.1 & 75.7 & 75.1 \tabularnewline
0.22 & 77.234 & 77.828 & 78.8 & 78.8 & 79.06 & 76.1 & 77.072 & 78.8 \tabularnewline
0.24 & 79.632 & 79.944 & 80.1 & 80.1 & 80.3 & 80.1 & 78.956 & 80.1 \tabularnewline
0.26 & 80.53 & 80.612 & 80.6 & 80.6 & 80.66 & 80.6 & 80.688 & 80.6 \tabularnewline
0.28 & 80.708 & 80.736 & 80.8 & 80.8 & 80.78 & 80.7 & 80.764 & 80.7 \tabularnewline
0.3 & 80.98 & 81.16 & 81.4 & 81.4 & 81.4 & 80.8 & 81.04 & 81.4 \tabularnewline
0.32 & 81.452 & 81.484 & 81.5 & 81.5 & 81.62 & 81.5 & 81.416 & 81.5 \tabularnewline
0.34 & 81.944 & 82.132 & 82.1 & 82.1 & 82.26 & 82.1 & 82.468 & 82.1 \tabularnewline
0.36 & 82.484 & 82.692 & 82.5 & 82.5 & 82.86 & 82.5 & 82.908 & 82.5 \tabularnewline
0.38 & 83.298 & 83.716 & 84.2 & 84.2 & 83.98 & 83.1 & 83.584 & 84.2 \tabularnewline
0.4 & 84.2 & 84.2 & 84.2 & 84.2 & 84.2 & 84.2 & 84.2 & 84.2 \tabularnewline
0.42 & 84.324 & 84.436 & 84.4 & 84.4 & 84.58 & 84.4 & 85.264 & 84.4 \tabularnewline
0.44 & 85.156 & 85.608 & 85.3 & 85.3 & 85.74 & 85.3 & 86.092 & 85.3 \tabularnewline
0.46 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 \tabularnewline
0.48 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 & 86.4 \tabularnewline
0.5 & 86.85 & 87.3 & 87.3 & 87.3 & 87.3 & 87.3 & 87.3 & 87.3 \tabularnewline
0.52 & 87.66 & 87.848 & 87.8 & 87.8 & 87.84 & 87.8 & 87.952 & 87.8 \tabularnewline
0.54 & 87.988 & 88 & 88 & 88 & 88 & 88 & 88 & 88 \tabularnewline
0.56 & 88.096 & 88.432 & 88.6 & 88.6 & 88.36 & 88 & 88.168 & 88.6 \tabularnewline
0.58 & 88.942 & 89.464 & 89.5 & 89.5 & 89.32 & 88.6 & 88.636 & 89.5 \tabularnewline
0.6 & 89.8 & 90 & 90 & 90 & 90 & 90 & 90 & 90 \tabularnewline
0.62 & 90 & 90.308 & 90 & 90 & 90.14 & 90 & 90.392 & 90 \tabularnewline
0.64 & 90.712 & 90.904 & 91 & 91 & 90.82 & 90.7 & 90.796 & 91 \tabularnewline
0.66 & 91.026 & 91.092 & 91.1 & 91.1 & 91.06 & 91 & 91.008 & 91.1 \tabularnewline
0.68 & 91.532 & 92.064 & 92 & 92 & 91.82 & 91.1 & 92.336 & 92 \tabularnewline
0.7 & 92.28 & 92.8 & 92.4 & 92.4 & 92.4 & 92.4 & 93 & 92.4 \tabularnewline
0.72 & 93.32 & 93.848 & 93.4 & 93.4 & 93.54 & 93.4 & 93.652 & 94.1 \tabularnewline
0.74 & 94.1 & 94.1 & 94.1 & 94.1 & 94.1 & 94.1 & 94.1 & 94.1 \tabularnewline
0.76 & 94.172 & 94.3 & 94.3 & 94.3 & 94.22 & 94.1 & 94.3 & 94.3 \tabularnewline
0.78 & 94.3 & 94.516 & 94.3 & 94.3 & 94.3 & 94.3 & 94.684 & 94.3 \tabularnewline
0.8 & 94.78 & 95.8 & 94.9 & 94.9 & 94.9 & 94.9 & 95.5 & 96.4 \tabularnewline
0.82 & 96.4 & 96.4 & 96.4 & 96.4 & 96.4 & 96.4 & 96.4 & 96.4 \tabularnewline
0.84 & 96.592 & 97.288 & 97.2 & 97.2 & 96.72 & 96.4 & 98.212 & 97.2 \tabularnewline
0.86 & 97.706 & 98.716 & 98.3 & 98.3 & 97.86 & 97.2 & 99.184 & 98.3 \tabularnewline
0.88 & 99.184 & 99.712 & 99.6 & 99.6 & 99.34 & 99.6 & 99.688 & 99.8 \tabularnewline
0.9 & 99.78 & 100.2 & 99.8 & 99.8 & 99.8 & 99.8 & 99.9 & 100.3 \tabularnewline
0.92 & 100.624 & 103.044 & 103 & 103 & 100.84 & 100.3 & 104.056 & 103 \tabularnewline
0.94 & 103.374 & 105.248 & 104.1 & 104.1 & 103.44 & 103 & 107.052 & 104.1 \tabularnewline
0.96 & 106.396 & 108.72 & 108.2 & 108.2 & 106.56 & 108.2 & 108.68 & 109.2 \tabularnewline
0.98 & 108.98 & 109.58 & 109.2 & 109.2 & 109 & 109.2 & 109.32 & 109.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18540&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]66.83[/C][C]66.86[/C][C]68[/C][C]68[/C][C]68.38[/C][C]66.5[/C][C]67.64[/C][C]66.5[/C][/ROW]
[ROW][C]0.04[/C][C]68.836[/C][C]68.912[/C][C]69.9[/C][C]69.9[/C][C]70.14[/C][C]68[/C][C]68.988[/C][C]68[/C][/ROW]
[ROW][C]0.06[/C][C]70.296[/C][C]70.332[/C][C]70.5[/C][C]70.5[/C][C]70.92[/C][C]70.5[/C][C]70.068[/C][C]70.5[/C][/ROW]
[ROW][C]0.08[/C][C]71.116[/C][C]71.172[/C][C]71.2[/C][C]71.2[/C][C]71.76[/C][C]71.2[/C][C]70.528[/C][C]71.2[/C][/ROW]
[ROW][C]0.1[/C][C]71.95[/C][C]72[/C][C]72.4[/C][C]72.4[/C][C]72.4[/C][C]71.9[/C][C]72.3[/C][C]71.9[/C][/ROW]
[ROW][C]0.12[/C][C]72.624[/C][C]72.708[/C][C]73.1[/C][C]73.1[/C][C]73.2[/C][C]72.4[/C][C]72.792[/C][C]72.4[/C][/ROW]
[ROW][C]0.14[/C][C]73.37[/C][C]73.44[/C][C]73.6[/C][C]73.6[/C][C]73.96[/C][C]73.6[/C][C]73.26[/C][C]73.6[/C][/ROW]
[ROW][C]0.16[/C][C]74.284[/C][C]74.428[/C][C]74.5[/C][C]74.5[/C][C]74.86[/C][C]74.5[/C][C]73.672[/C][C]74.5[/C][/ROW]
[ROW][C]0.18[/C][C]75.088[/C][C]75.1[/C][C]75.1[/C][C]75.1[/C][C]75.1[/C][C]75.1[/C][C]75.1[/C][C]75.1[/C][/ROW]
[ROW][C]0.2[/C][C]75.3[/C][C]75.5[/C][C]76.1[/C][C]76.1[/C][C]76.1[/C][C]75.1[/C][C]75.7[/C][C]75.1[/C][/ROW]
[ROW][C]0.22[/C][C]77.234[/C][C]77.828[/C][C]78.8[/C][C]78.8[/C][C]79.06[/C][C]76.1[/C][C]77.072[/C][C]78.8[/C][/ROW]
[ROW][C]0.24[/C][C]79.632[/C][C]79.944[/C][C]80.1[/C][C]80.1[/C][C]80.3[/C][C]80.1[/C][C]78.956[/C][C]80.1[/C][/ROW]
[ROW][C]0.26[/C][C]80.53[/C][C]80.612[/C][C]80.6[/C][C]80.6[/C][C]80.66[/C][C]80.6[/C][C]80.688[/C][C]80.6[/C][/ROW]
[ROW][C]0.28[/C][C]80.708[/C][C]80.736[/C][C]80.8[/C][C]80.8[/C][C]80.78[/C][C]80.7[/C][C]80.764[/C][C]80.7[/C][/ROW]
[ROW][C]0.3[/C][C]80.98[/C][C]81.16[/C][C]81.4[/C][C]81.4[/C][C]81.4[/C][C]80.8[/C][C]81.04[/C][C]81.4[/C][/ROW]
[ROW][C]0.32[/C][C]81.452[/C][C]81.484[/C][C]81.5[/C][C]81.5[/C][C]81.62[/C][C]81.5[/C][C]81.416[/C][C]81.5[/C][/ROW]
[ROW][C]0.34[/C][C]81.944[/C][C]82.132[/C][C]82.1[/C][C]82.1[/C][C]82.26[/C][C]82.1[/C][C]82.468[/C][C]82.1[/C][/ROW]
[ROW][C]0.36[/C][C]82.484[/C][C]82.692[/C][C]82.5[/C][C]82.5[/C][C]82.86[/C][C]82.5[/C][C]82.908[/C][C]82.5[/C][/ROW]
[ROW][C]0.38[/C][C]83.298[/C][C]83.716[/C][C]84.2[/C][C]84.2[/C][C]83.98[/C][C]83.1[/C][C]83.584[/C][C]84.2[/C][/ROW]
[ROW][C]0.4[/C][C]84.2[/C][C]84.2[/C][C]84.2[/C][C]84.2[/C][C]84.2[/C][C]84.2[/C][C]84.2[/C][C]84.2[/C][/ROW]
[ROW][C]0.42[/C][C]84.324[/C][C]84.436[/C][C]84.4[/C][C]84.4[/C][C]84.58[/C][C]84.4[/C][C]85.264[/C][C]84.4[/C][/ROW]
[ROW][C]0.44[/C][C]85.156[/C][C]85.608[/C][C]85.3[/C][C]85.3[/C][C]85.74[/C][C]85.3[/C][C]86.092[/C][C]85.3[/C][/ROW]
[ROW][C]0.46[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][/ROW]
[ROW][C]0.48[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][C]86.4[/C][/ROW]
[ROW][C]0.5[/C][C]86.85[/C][C]87.3[/C][C]87.3[/C][C]87.3[/C][C]87.3[/C][C]87.3[/C][C]87.3[/C][C]87.3[/C][/ROW]
[ROW][C]0.52[/C][C]87.66[/C][C]87.848[/C][C]87.8[/C][C]87.8[/C][C]87.84[/C][C]87.8[/C][C]87.952[/C][C]87.8[/C][/ROW]
[ROW][C]0.54[/C][C]87.988[/C][C]88[/C][C]88[/C][C]88[/C][C]88[/C][C]88[/C][C]88[/C][C]88[/C][/ROW]
[ROW][C]0.56[/C][C]88.096[/C][C]88.432[/C][C]88.6[/C][C]88.6[/C][C]88.36[/C][C]88[/C][C]88.168[/C][C]88.6[/C][/ROW]
[ROW][C]0.58[/C][C]88.942[/C][C]89.464[/C][C]89.5[/C][C]89.5[/C][C]89.32[/C][C]88.6[/C][C]88.636[/C][C]89.5[/C][/ROW]
[ROW][C]0.6[/C][C]89.8[/C][C]90[/C][C]90[/C][C]90[/C][C]90[/C][C]90[/C][C]90[/C][C]90[/C][/ROW]
[ROW][C]0.62[/C][C]90[/C][C]90.308[/C][C]90[/C][C]90[/C][C]90.14[/C][C]90[/C][C]90.392[/C][C]90[/C][/ROW]
[ROW][C]0.64[/C][C]90.712[/C][C]90.904[/C][C]91[/C][C]91[/C][C]90.82[/C][C]90.7[/C][C]90.796[/C][C]91[/C][/ROW]
[ROW][C]0.66[/C][C]91.026[/C][C]91.092[/C][C]91.1[/C][C]91.1[/C][C]91.06[/C][C]91[/C][C]91.008[/C][C]91.1[/C][/ROW]
[ROW][C]0.68[/C][C]91.532[/C][C]92.064[/C][C]92[/C][C]92[/C][C]91.82[/C][C]91.1[/C][C]92.336[/C][C]92[/C][/ROW]
[ROW][C]0.7[/C][C]92.28[/C][C]92.8[/C][C]92.4[/C][C]92.4[/C][C]92.4[/C][C]92.4[/C][C]93[/C][C]92.4[/C][/ROW]
[ROW][C]0.72[/C][C]93.32[/C][C]93.848[/C][C]93.4[/C][C]93.4[/C][C]93.54[/C][C]93.4[/C][C]93.652[/C][C]94.1[/C][/ROW]
[ROW][C]0.74[/C][C]94.1[/C][C]94.1[/C][C]94.1[/C][C]94.1[/C][C]94.1[/C][C]94.1[/C][C]94.1[/C][C]94.1[/C][/ROW]
[ROW][C]0.76[/C][C]94.172[/C][C]94.3[/C][C]94.3[/C][C]94.3[/C][C]94.22[/C][C]94.1[/C][C]94.3[/C][C]94.3[/C][/ROW]
[ROW][C]0.78[/C][C]94.3[/C][C]94.516[/C][C]94.3[/C][C]94.3[/C][C]94.3[/C][C]94.3[/C][C]94.684[/C][C]94.3[/C][/ROW]
[ROW][C]0.8[/C][C]94.78[/C][C]95.8[/C][C]94.9[/C][C]94.9[/C][C]94.9[/C][C]94.9[/C][C]95.5[/C][C]96.4[/C][/ROW]
[ROW][C]0.82[/C][C]96.4[/C][C]96.4[/C][C]96.4[/C][C]96.4[/C][C]96.4[/C][C]96.4[/C][C]96.4[/C][C]96.4[/C][/ROW]
[ROW][C]0.84[/C][C]96.592[/C][C]97.288[/C][C]97.2[/C][C]97.2[/C][C]96.72[/C][C]96.4[/C][C]98.212[/C][C]97.2[/C][/ROW]
[ROW][C]0.86[/C][C]97.706[/C][C]98.716[/C][C]98.3[/C][C]98.3[/C][C]97.86[/C][C]97.2[/C][C]99.184[/C][C]98.3[/C][/ROW]
[ROW][C]0.88[/C][C]99.184[/C][C]99.712[/C][C]99.6[/C][C]99.6[/C][C]99.34[/C][C]99.6[/C][C]99.688[/C][C]99.8[/C][/ROW]
[ROW][C]0.9[/C][C]99.78[/C][C]100.2[/C][C]99.8[/C][C]99.8[/C][C]99.8[/C][C]99.8[/C][C]99.9[/C][C]100.3[/C][/ROW]
[ROW][C]0.92[/C][C]100.624[/C][C]103.044[/C][C]103[/C][C]103[/C][C]100.84[/C][C]100.3[/C][C]104.056[/C][C]103[/C][/ROW]
[ROW][C]0.94[/C][C]103.374[/C][C]105.248[/C][C]104.1[/C][C]104.1[/C][C]103.44[/C][C]103[/C][C]107.052[/C][C]104.1[/C][/ROW]
[ROW][C]0.96[/C][C]106.396[/C][C]108.72[/C][C]108.2[/C][C]108.2[/C][C]106.56[/C][C]108.2[/C][C]108.68[/C][C]109.2[/C][/ROW]
[ROW][C]0.98[/C][C]108.98[/C][C]109.58[/C][C]109.2[/C][C]109.2[/C][C]109[/C][C]109.2[/C][C]109.32[/C][C]109.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18540&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18540&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)
0.0266.8366.86686868.3866.567.6466.5
0.0468.83668.91269.969.970.146868.98868
0.0670.29670.33270.570.570.9270.570.06870.5
0.0871.11671.17271.271.271.7671.270.52871.2
0.171.957272.472.472.471.972.371.9
0.1272.62472.70873.173.173.272.472.79272.4
0.1473.3773.4473.673.673.9673.673.2673.6
0.1674.28474.42874.574.574.8674.573.67274.5
0.1875.08875.175.175.175.175.175.175.1
0.275.375.576.176.176.175.175.775.1
0.2277.23477.82878.878.879.0676.177.07278.8
0.2479.63279.94480.180.180.380.178.95680.1
0.2680.5380.61280.680.680.6680.680.68880.6
0.2880.70880.73680.880.880.7880.780.76480.7
0.380.9881.1681.481.481.480.881.0481.4
0.3281.45281.48481.581.581.6281.581.41681.5
0.3481.94482.13282.182.182.2682.182.46882.1
0.3682.48482.69282.582.582.8682.582.90882.5
0.3883.29883.71684.284.283.9883.183.58484.2
0.484.284.284.284.284.284.284.284.2
0.4284.32484.43684.484.484.5884.485.26484.4
0.4485.15685.60885.385.385.7485.386.09285.3
0.4686.486.486.486.486.486.486.486.4
0.4886.486.486.486.486.486.486.486.4
0.586.8587.387.387.387.387.387.387.3
0.5287.6687.84887.887.887.8487.887.95287.8
0.5487.98888888888888888
0.5688.09688.43288.688.688.368888.16888.6
0.5888.94289.46489.589.589.3288.688.63689.5
0.689.890909090909090
0.629090.308909090.149090.39290
0.6490.71290.904919190.8290.790.79691
0.6691.02691.09291.191.191.069191.00891.1
0.6891.53292.064929291.8291.192.33692
0.792.2892.892.492.492.492.49392.4
0.7293.3293.84893.493.493.5493.493.65294.1
0.7494.194.194.194.194.194.194.194.1
0.7694.17294.394.394.394.2294.194.394.3
0.7894.394.51694.394.394.394.394.68494.3
0.894.7895.894.994.994.994.995.596.4
0.8296.496.496.496.496.496.496.496.4
0.8496.59297.28897.297.296.7296.498.21297.2
0.8697.70698.71698.398.397.8697.299.18498.3
0.8899.18499.71299.699.699.3499.699.68899.8
0.999.78100.299.899.899.899.899.9100.3
0.92100.624103.044103103100.84100.3104.056103
0.94103.374105.248104.1104.1103.44103107.052104.1
0.96106.396108.72108.2108.2106.56108.2108.68109.2
0.98108.98109.58109.2109.2109109.2109.32109.7



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')