Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationThu, 13 Nov 2008 02:54:23 -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/Nov/13/t1226570128dr5gf0scuxwrxqm.htm/, Retrieved Sun, 19 May 2024 10:41:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24528, Retrieved Sun, 19 May 2024 10:41:22 +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     [Box-Cox Normality Plot] [box-cox normal] [2008-11-12 20:29:20] [7a664918911e34206ce9d0436dd7c1c8]
F RM D    [Percentiles] [] [2008-11-13 09:54:23] [8767719db498704e1fee27044c098ad0] [Current]
Feedback Forum
2008-11-20 16:40:52 [Gert-Jan Geudens] [reply
Het is zeer goed om deze grafiek weer te geven. Ook uit deze normal q-q plot kunnen we afleiden dat de gegevens niet normaal verdeeld zijn.
2008-11-24 20:32:01 [4679c4d03f1d346a85e79d87ba60ec2b] [reply
Inderdaad goed om deze grafiek te maken. Deze bewijst dat de histogram correct is, er is ook hier te zien dat de gegevens niet normaal verdeeld zijn.

Post a new message
Dataseries X:
45
24
18
20
22
39
55
35
38
47
1
57
50
33
19
2
7
15
56
53
24
48
2
49
46
32
37
10
8
16
55
46
46
45
6
45
52
44
35
15
44
51
58
23
44
43
6
51
53
47
19
18
38
43
23
43
18
43
6
31
49




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=24528&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=24528&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24528&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)
0.021.221.2422211.761
0.0422223.6222
0.064.644.8866663.126
0.0866666666
0.16.16.277766.86
0.127.327.44888.477.567
0.149.089.36101012108.6410
0.1613.814.61515151510.415
0.181515.16151515.81515.8415
0.216.416.81818181617.216
0.221818181818181818
0.241818181818.4181818
0.2618.8619191919191919
0.2819.0819.36202019.81919.6419
0.320.621.22222222020.822
0.3222.5222.842323232322.1623
0.342323.08232323.42323.9223
0.3623.9624242424242424
0.3825.2627.92313129.62427.0831
0.431.431.83232323131.232
0.4232.6233.08333333.43334.9233
0.4434.6835353535353535
0.4635.1236.04373736.23535.9637
0.4837.2837.76383837.83737.2438
0.53838383838383838
0.5238.7239.96393939.83942.0439
0.5442.7643434343434343
0.564343434343434343
0.584343434343434343
0.643.644444444444444
0.624444444444444444
0.6444.0444.68454544.44444.3245
0.664545454545454545
0.684545.164545454545.8445
0.745.746464646464646
0.724646464646464646
0.7446.1446.88474746.44646.1247
0.764747.124747474747.8847
0.7847.5848.36484847.84848.6448
0.848.849494949494949
0.8249.0249.84505049.24949.1650
0.8450.2451515150.4505151
0.865151.325151515151.6851
0.8851.6852.56525251.85252.4453
0.952.953535353535353
0.9253.2455555553.4535555
0.945555.285555555555.7255
0.9655.5656.52565655.65656.4857
0.9856.7857.76575756.85757.2458

\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 & 1.22 & 1.24 & 2 & 2 & 2 & 1 & 1.76 & 1 \tabularnewline
0.04 & 2 & 2 & 2 & 2 & 3.6 & 2 & 2 & 2 \tabularnewline
0.06 & 4.64 & 4.88 & 6 & 6 & 6 & 6 & 3.12 & 6 \tabularnewline
0.08 & 6 & 6 & 6 & 6 & 6 & 6 & 6 & 6 \tabularnewline
0.1 & 6.1 & 6.2 & 7 & 7 & 7 & 6 & 6.8 & 6 \tabularnewline
0.12 & 7.32 & 7.44 & 8 & 8 & 8.4 & 7 & 7.56 & 7 \tabularnewline
0.14 & 9.08 & 9.36 & 10 & 10 & 12 & 10 & 8.64 & 10 \tabularnewline
0.16 & 13.8 & 14.6 & 15 & 15 & 15 & 15 & 10.4 & 15 \tabularnewline
0.18 & 15 & 15.16 & 15 & 15 & 15.8 & 15 & 15.84 & 15 \tabularnewline
0.2 & 16.4 & 16.8 & 18 & 18 & 18 & 16 & 17.2 & 16 \tabularnewline
0.22 & 18 & 18 & 18 & 18 & 18 & 18 & 18 & 18 \tabularnewline
0.24 & 18 & 18 & 18 & 18 & 18.4 & 18 & 18 & 18 \tabularnewline
0.26 & 18.86 & 19 & 19 & 19 & 19 & 19 & 19 & 19 \tabularnewline
0.28 & 19.08 & 19.36 & 20 & 20 & 19.8 & 19 & 19.64 & 19 \tabularnewline
0.3 & 20.6 & 21.2 & 22 & 22 & 22 & 20 & 20.8 & 22 \tabularnewline
0.32 & 22.52 & 22.84 & 23 & 23 & 23 & 23 & 22.16 & 23 \tabularnewline
0.34 & 23 & 23.08 & 23 & 23 & 23.4 & 23 & 23.92 & 23 \tabularnewline
0.36 & 23.96 & 24 & 24 & 24 & 24 & 24 & 24 & 24 \tabularnewline
0.38 & 25.26 & 27.92 & 31 & 31 & 29.6 & 24 & 27.08 & 31 \tabularnewline
0.4 & 31.4 & 31.8 & 32 & 32 & 32 & 31 & 31.2 & 32 \tabularnewline
0.42 & 32.62 & 33.08 & 33 & 33 & 33.4 & 33 & 34.92 & 33 \tabularnewline
0.44 & 34.68 & 35 & 35 & 35 & 35 & 35 & 35 & 35 \tabularnewline
0.46 & 35.12 & 36.04 & 37 & 37 & 36.2 & 35 & 35.96 & 37 \tabularnewline
0.48 & 37.28 & 37.76 & 38 & 38 & 37.8 & 37 & 37.24 & 38 \tabularnewline
0.5 & 38 & 38 & 38 & 38 & 38 & 38 & 38 & 38 \tabularnewline
0.52 & 38.72 & 39.96 & 39 & 39 & 39.8 & 39 & 42.04 & 39 \tabularnewline
0.54 & 42.76 & 43 & 43 & 43 & 43 & 43 & 43 & 43 \tabularnewline
0.56 & 43 & 43 & 43 & 43 & 43 & 43 & 43 & 43 \tabularnewline
0.58 & 43 & 43 & 43 & 43 & 43 & 43 & 43 & 43 \tabularnewline
0.6 & 43.6 & 44 & 44 & 44 & 44 & 44 & 44 & 44 \tabularnewline
0.62 & 44 & 44 & 44 & 44 & 44 & 44 & 44 & 44 \tabularnewline
0.64 & 44.04 & 44.68 & 45 & 45 & 44.4 & 44 & 44.32 & 45 \tabularnewline
0.66 & 45 & 45 & 45 & 45 & 45 & 45 & 45 & 45 \tabularnewline
0.68 & 45 & 45.16 & 45 & 45 & 45 & 45 & 45.84 & 45 \tabularnewline
0.7 & 45.7 & 46 & 46 & 46 & 46 & 46 & 46 & 46 \tabularnewline
0.72 & 46 & 46 & 46 & 46 & 46 & 46 & 46 & 46 \tabularnewline
0.74 & 46.14 & 46.88 & 47 & 47 & 46.4 & 46 & 46.12 & 47 \tabularnewline
0.76 & 47 & 47.12 & 47 & 47 & 47 & 47 & 47.88 & 47 \tabularnewline
0.78 & 47.58 & 48.36 & 48 & 48 & 47.8 & 48 & 48.64 & 48 \tabularnewline
0.8 & 48.8 & 49 & 49 & 49 & 49 & 49 & 49 & 49 \tabularnewline
0.82 & 49.02 & 49.84 & 50 & 50 & 49.2 & 49 & 49.16 & 50 \tabularnewline
0.84 & 50.24 & 51 & 51 & 51 & 50.4 & 50 & 51 & 51 \tabularnewline
0.86 & 51 & 51.32 & 51 & 51 & 51 & 51 & 51.68 & 51 \tabularnewline
0.88 & 51.68 & 52.56 & 52 & 52 & 51.8 & 52 & 52.44 & 53 \tabularnewline
0.9 & 52.9 & 53 & 53 & 53 & 53 & 53 & 53 & 53 \tabularnewline
0.92 & 53.24 & 55 & 55 & 55 & 53.4 & 53 & 55 & 55 \tabularnewline
0.94 & 55 & 55.28 & 55 & 55 & 55 & 55 & 55.72 & 55 \tabularnewline
0.96 & 55.56 & 56.52 & 56 & 56 & 55.6 & 56 & 56.48 & 57 \tabularnewline
0.98 & 56.78 & 57.76 & 57 & 57 & 56.8 & 57 & 57.24 & 58 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24528&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]1.22[/C][C]1.24[/C][C]2[/C][C]2[/C][C]2[/C][C]1[/C][C]1.76[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]2[/C][C]2[/C][C]2[/C][C]2[/C][C]3.6[/C][C]2[/C][C]2[/C][C]2[/C][/ROW]
[ROW][C]0.06[/C][C]4.64[/C][C]4.88[/C][C]6[/C][C]6[/C][C]6[/C][C]6[/C][C]3.12[/C][C]6[/C][/ROW]
[ROW][C]0.08[/C][C]6[/C][C]6[/C][C]6[/C][C]6[/C][C]6[/C][C]6[/C][C]6[/C][C]6[/C][/ROW]
[ROW][C]0.1[/C][C]6.1[/C][C]6.2[/C][C]7[/C][C]7[/C][C]7[/C][C]6[/C][C]6.8[/C][C]6[/C][/ROW]
[ROW][C]0.12[/C][C]7.32[/C][C]7.44[/C][C]8[/C][C]8[/C][C]8.4[/C][C]7[/C][C]7.56[/C][C]7[/C][/ROW]
[ROW][C]0.14[/C][C]9.08[/C][C]9.36[/C][C]10[/C][C]10[/C][C]12[/C][C]10[/C][C]8.64[/C][C]10[/C][/ROW]
[ROW][C]0.16[/C][C]13.8[/C][C]14.6[/C][C]15[/C][C]15[/C][C]15[/C][C]15[/C][C]10.4[/C][C]15[/C][/ROW]
[ROW][C]0.18[/C][C]15[/C][C]15.16[/C][C]15[/C][C]15[/C][C]15.8[/C][C]15[/C][C]15.84[/C][C]15[/C][/ROW]
[ROW][C]0.2[/C][C]16.4[/C][C]16.8[/C][C]18[/C][C]18[/C][C]18[/C][C]16[/C][C]17.2[/C][C]16[/C][/ROW]
[ROW][C]0.22[/C][C]18[/C][C]18[/C][C]18[/C][C]18[/C][C]18[/C][C]18[/C][C]18[/C][C]18[/C][/ROW]
[ROW][C]0.24[/C][C]18[/C][C]18[/C][C]18[/C][C]18[/C][C]18.4[/C][C]18[/C][C]18[/C][C]18[/C][/ROW]
[ROW][C]0.26[/C][C]18.86[/C][C]19[/C][C]19[/C][C]19[/C][C]19[/C][C]19[/C][C]19[/C][C]19[/C][/ROW]
[ROW][C]0.28[/C][C]19.08[/C][C]19.36[/C][C]20[/C][C]20[/C][C]19.8[/C][C]19[/C][C]19.64[/C][C]19[/C][/ROW]
[ROW][C]0.3[/C][C]20.6[/C][C]21.2[/C][C]22[/C][C]22[/C][C]22[/C][C]20[/C][C]20.8[/C][C]22[/C][/ROW]
[ROW][C]0.32[/C][C]22.52[/C][C]22.84[/C][C]23[/C][C]23[/C][C]23[/C][C]23[/C][C]22.16[/C][C]23[/C][/ROW]
[ROW][C]0.34[/C][C]23[/C][C]23.08[/C][C]23[/C][C]23[/C][C]23.4[/C][C]23[/C][C]23.92[/C][C]23[/C][/ROW]
[ROW][C]0.36[/C][C]23.96[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][C]24[/C][/ROW]
[ROW][C]0.38[/C][C]25.26[/C][C]27.92[/C][C]31[/C][C]31[/C][C]29.6[/C][C]24[/C][C]27.08[/C][C]31[/C][/ROW]
[ROW][C]0.4[/C][C]31.4[/C][C]31.8[/C][C]32[/C][C]32[/C][C]32[/C][C]31[/C][C]31.2[/C][C]32[/C][/ROW]
[ROW][C]0.42[/C][C]32.62[/C][C]33.08[/C][C]33[/C][C]33[/C][C]33.4[/C][C]33[/C][C]34.92[/C][C]33[/C][/ROW]
[ROW][C]0.44[/C][C]34.68[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][C]35[/C][/ROW]
[ROW][C]0.46[/C][C]35.12[/C][C]36.04[/C][C]37[/C][C]37[/C][C]36.2[/C][C]35[/C][C]35.96[/C][C]37[/C][/ROW]
[ROW][C]0.48[/C][C]37.28[/C][C]37.76[/C][C]38[/C][C]38[/C][C]37.8[/C][C]37[/C][C]37.24[/C][C]38[/C][/ROW]
[ROW][C]0.5[/C][C]38[/C][C]38[/C][C]38[/C][C]38[/C][C]38[/C][C]38[/C][C]38[/C][C]38[/C][/ROW]
[ROW][C]0.52[/C][C]38.72[/C][C]39.96[/C][C]39[/C][C]39[/C][C]39.8[/C][C]39[/C][C]42.04[/C][C]39[/C][/ROW]
[ROW][C]0.54[/C][C]42.76[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][/ROW]
[ROW][C]0.56[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][/ROW]
[ROW][C]0.58[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][C]43[/C][/ROW]
[ROW][C]0.6[/C][C]43.6[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][/ROW]
[ROW][C]0.62[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][C]44[/C][/ROW]
[ROW][C]0.64[/C][C]44.04[/C][C]44.68[/C][C]45[/C][C]45[/C][C]44.4[/C][C]44[/C][C]44.32[/C][C]45[/C][/ROW]
[ROW][C]0.66[/C][C]45[/C][C]45[/C][C]45[/C][C]45[/C][C]45[/C][C]45[/C][C]45[/C][C]45[/C][/ROW]
[ROW][C]0.68[/C][C]45[/C][C]45.16[/C][C]45[/C][C]45[/C][C]45[/C][C]45[/C][C]45.84[/C][C]45[/C][/ROW]
[ROW][C]0.7[/C][C]45.7[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][/ROW]
[ROW][C]0.72[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][C]46[/C][/ROW]
[ROW][C]0.74[/C][C]46.14[/C][C]46.88[/C][C]47[/C][C]47[/C][C]46.4[/C][C]46[/C][C]46.12[/C][C]47[/C][/ROW]
[ROW][C]0.76[/C][C]47[/C][C]47.12[/C][C]47[/C][C]47[/C][C]47[/C][C]47[/C][C]47.88[/C][C]47[/C][/ROW]
[ROW][C]0.78[/C][C]47.58[/C][C]48.36[/C][C]48[/C][C]48[/C][C]47.8[/C][C]48[/C][C]48.64[/C][C]48[/C][/ROW]
[ROW][C]0.8[/C][C]48.8[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][C]49[/C][/ROW]
[ROW][C]0.82[/C][C]49.02[/C][C]49.84[/C][C]50[/C][C]50[/C][C]49.2[/C][C]49[/C][C]49.16[/C][C]50[/C][/ROW]
[ROW][C]0.84[/C][C]50.24[/C][C]51[/C][C]51[/C][C]51[/C][C]50.4[/C][C]50[/C][C]51[/C][C]51[/C][/ROW]
[ROW][C]0.86[/C][C]51[/C][C]51.32[/C][C]51[/C][C]51[/C][C]51[/C][C]51[/C][C]51.68[/C][C]51[/C][/ROW]
[ROW][C]0.88[/C][C]51.68[/C][C]52.56[/C][C]52[/C][C]52[/C][C]51.8[/C][C]52[/C][C]52.44[/C][C]53[/C][/ROW]
[ROW][C]0.9[/C][C]52.9[/C][C]53[/C][C]53[/C][C]53[/C][C]53[/C][C]53[/C][C]53[/C][C]53[/C][/ROW]
[ROW][C]0.92[/C][C]53.24[/C][C]55[/C][C]55[/C][C]55[/C][C]53.4[/C][C]53[/C][C]55[/C][C]55[/C][/ROW]
[ROW][C]0.94[/C][C]55[/C][C]55.28[/C][C]55[/C][C]55[/C][C]55[/C][C]55[/C][C]55.72[/C][C]55[/C][/ROW]
[ROW][C]0.96[/C][C]55.56[/C][C]56.52[/C][C]56[/C][C]56[/C][C]55.6[/C][C]56[/C][C]56.48[/C][C]57[/C][/ROW]
[ROW][C]0.98[/C][C]56.78[/C][C]57.76[/C][C]57[/C][C]57[/C][C]56.8[/C][C]57[/C][C]57.24[/C][C]58[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24528&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24528&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)
0.021.221.2422211.761
0.0422223.6222
0.064.644.8866663.126
0.0866666666
0.16.16.277766.86
0.127.327.44888.477.567
0.149.089.36101012108.6410
0.1613.814.61515151510.415
0.181515.16151515.81515.8415
0.216.416.81818181617.216
0.221818181818181818
0.241818181818.4181818
0.2618.8619191919191919
0.2819.0819.36202019.81919.6419
0.320.621.22222222020.822
0.3222.5222.842323232322.1623
0.342323.08232323.42323.9223
0.3623.9624242424242424
0.3825.2627.92313129.62427.0831
0.431.431.83232323131.232
0.4232.6233.08333333.43334.9233
0.4434.6835353535353535
0.4635.1236.04373736.23535.9637
0.4837.2837.76383837.83737.2438
0.53838383838383838
0.5238.7239.96393939.83942.0439
0.5442.7643434343434343
0.564343434343434343
0.584343434343434343
0.643.644444444444444
0.624444444444444444
0.6444.0444.68454544.44444.3245
0.664545454545454545
0.684545.164545454545.8445
0.745.746464646464646
0.724646464646464646
0.7446.1446.88474746.44646.1247
0.764747.124747474747.8847
0.7847.5848.36484847.84848.6448
0.848.849494949494949
0.8249.0249.84505049.24949.1650
0.8450.2451515150.4505151
0.865151.325151515151.6851
0.8851.6852.56525251.85252.4453
0.952.953535353535353
0.9253.2455555553.4535555
0.945555.285555555555.7255
0.9655.5656.52565655.65656.4857
0.9856.7857.76575756.85757.2458



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')