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rwasp_percentiles.wasp

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Percentiles

Date of computation

Thu, 03 Dec 2009 10:22:23 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t1259860994n748lsu2pcef2gv.htm/, Retrieved Sat, 20 Apr 2024 10:41:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62941, Retrieved Sat, 20 Apr 2024 10:41:59 +0000

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Estimated Impact

143

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMPD        [Percentiles] [] [2009-12-03 10:35:08] [3b0db66ac8145b1be856a517e2900332]
-    D            [Percentiles] [] [2009-12-03 17:22:23] [791a4a78a0a7ca497fb8791b982a539e] [Current]
- RMPD              [Harrell-Davis Quantiles] [] [2009-12-04 18:29:06] [eba9b8a72d680086d9ebbb043233c887] 
- RMPD              [Harrell-Davis Quantiles] [] [2009-12-04 18:35:49] [eba9b8a72d680086d9ebbb043233c887] 

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=62941&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=62941&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62941&T=0

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Percentiles - Ungrouped Data
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)
0.02	639.048	639.916	672.9	672.9	674.56	629.5	662.484	629.5
0.04	676.552	676.884	681.2	681.2	684.24	672.9	677.216	672.9
0.06	686.216	686.672	688.8	688.8	705	688.8	683.328	688.8
0.08	712.56	714.72	715.8	715.8	740.44	715.8	689.88	715.8
0.1	747.48	748.36	755.4	755.4	755.4	746.6	753.64	746.6
0.12	757.064	757.688	760.6	760.6	761.66	755.4	758.312	755.4
0.14	763.462	764.204	765.9	765.9	773.86	765.9	762.296	765.9
0.16	781.024	784.208	785.8	785.8	789.52	785.8	767.492	785.8
0.18	791.876	796.368	792	792	813.84	792	814.932	792
0.2	822.8	826.3	836.8	836.8	836.8	819.3	829.8	819.3
0.22	842.092	844.864	849.4	849.4	855.6	836.8	841.336	849.4
0.24	869.24	876.68	880.4	880.4	888.28	880.4	853.12	880.4
0.26	897.342	900.676	900.1	900.1	902.98	900.1	904.324	900.1
0.28	907.484	916.528	937.2	937.2	930.74	904.9	925.572	904.9
0.3	940.23	943.26	947.3	947.3	947.3	937.2	941.24	947.3
0.32	948.132	948.644	948.9	948.9	949.64	948.9	947.556	948.9
0.34	951.638	954.328	952.6	952.6	961.24	952.6	972.472	952.6
0.36	973.336	982.712	974.2	974.2	990.16	974.2	992.288	974.2
0.38	1006.56	1018.72	1032.8	1032.8	1026.4	1000.8	1014.88	1032.8
0.4	1035.36	1037.92	1039.2	1039.2	1039.2	1032.8	1034.08	1039.2
0.42	1046.33	1050.964	1050.7	1050.7	1052.02	1050.7	1057.036	1050.7
0.44	1056.244	1062.368	1057.3	1057.3	1064.54	1057.3	1070.332	1057.3
0.46	1075.724	1078.208	1080.8	1080.8	1078.64	1075.4	1077.992	1080.8
0.48	1085.252	1092.884	1096.7	1096.7	1093.52	1080.8	1084.616	1096.7
0.5	1107.55	1118.4	1118.4	1118.4	1118.4	1118.4	1118.4	1118.4
0.52	1155.984	1172.808	1170.6	1170.6	1172.44	1170.6	1177.592	1170.6
0.54	1179.248	1195.784	1179.8	1179.8	1193.12	1179.8	1197.116	1179.8
0.56	1215.324	1223.108	1227	1227	1221.44	1213.1	1216.992	1227
0.58	1230.534	1235.928	1236.3	1236.3	1234.44	1227	1227.372	1236.3
0.6	1244.64	1250.46	1250.2	1250.2	1250.2	1250.2	1251.24	1250.2
0.62	1251.266	1254.272	1251.5	1251.5	1252.76	1251.5	1255.028	1251.5
0.64	1258.064	1262.288	1264.4	1264.4	1260.44	1257.8	1259.912	1264.4
0.66	1264.686	1265.412	1265.5	1265.5	1265.06	1264.4	1264.488	1265.5
0.68	1269.82	1278.708	1274.5	1274.5	1272.7	1265.5	1296.592	1274.5
0.7	1292.91	1307.12	1300.8	1300.8	1300.8	1300.8	1310.28	1300.8
0.72	1315.336	1321.272	1316.6	1316.6	1318.06	1316.6	1319.228	1323.9
0.74	1325.048	1331.116	1332.1	1332.1	1327.18	1323.9	1324.884	1332.1
0.76	1337.968	1351.22	1348.4	1348.4	1341.88	1332.1	1369.08	1348.4
0.78	1362.03	1380.36	1371.9	1371.9	1367.2	1371.9	1386.94	1371.9
0.8	1390.7	1400.14	1395.4	1395.4	1395.4	1395.4	1398.56	1403.3
0.82	1403.308	1403.636	1403.7	1403.7	1403.38	1403.3	1403.364	1403.7
0.84	1407.3	1420.26	1418.7	1418.7	1409.7	1403.7	1436.64	1418.7
0.86	1427.67	1441.496	1438.2	1438.2	1430.4	1418.7	1445.204	1438.2
0.88	1445.204	1450.348	1448.5	1448.5	1446.44	1448.5	1449.952	1451.8
0.9	1451.47	1469.72	1451.8	1451.8	1451.8	1451.8	1456.28	1474.2
0.92	1476.348	1492.96	1492.1	1492.1	1477.78	1474.2	1512.74	1492.1
0.94	1499.41	1517.492	1513.6	1513.6	1500.7	1492.1	1523.608	1513.6
0.96	1521.384	1537.224	1527.5	1527.5	1521.94	1527.5	1536.476	1546.2
0.98	1542.086	1558.36	1546.2	1546.2	1542.46	1546.2	1550.04	1562.2

\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 & 639.048 & 639.916 & 672.9 & 672.9 & 674.56 & 629.5 & 662.484 & 629.5 \tabularnewline
0.04 & 676.552 & 676.884 & 681.2 & 681.2 & 684.24 & 672.9 & 677.216 & 672.9 \tabularnewline
0.06 & 686.216 & 686.672 & 688.8 & 688.8 & 705 & 688.8 & 683.328 & 688.8 \tabularnewline
0.08 & 712.56 & 714.72 & 715.8 & 715.8 & 740.44 & 715.8 & 689.88 & 715.8 \tabularnewline
0.1 & 747.48 & 748.36 & 755.4 & 755.4 & 755.4 & 746.6 & 753.64 & 746.6 \tabularnewline
0.12 & 757.064 & 757.688 & 760.6 & 760.6 & 761.66 & 755.4 & 758.312 & 755.4 \tabularnewline
0.14 & 763.462 & 764.204 & 765.9 & 765.9 & 773.86 & 765.9 & 762.296 & 765.9 \tabularnewline
0.16 & 781.024 & 784.208 & 785.8 & 785.8 & 789.52 & 785.8 & 767.492 & 785.8 \tabularnewline
0.18 & 791.876 & 796.368 & 792 & 792 & 813.84 & 792 & 814.932 & 792 \tabularnewline
0.2 & 822.8 & 826.3 & 836.8 & 836.8 & 836.8 & 819.3 & 829.8 & 819.3 \tabularnewline
0.22 & 842.092 & 844.864 & 849.4 & 849.4 & 855.6 & 836.8 & 841.336 & 849.4 \tabularnewline
0.24 & 869.24 & 876.68 & 880.4 & 880.4 & 888.28 & 880.4 & 853.12 & 880.4 \tabularnewline
0.26 & 897.342 & 900.676 & 900.1 & 900.1 & 902.98 & 900.1 & 904.324 & 900.1 \tabularnewline
0.28 & 907.484 & 916.528 & 937.2 & 937.2 & 930.74 & 904.9 & 925.572 & 904.9 \tabularnewline
0.3 & 940.23 & 943.26 & 947.3 & 947.3 & 947.3 & 937.2 & 941.24 & 947.3 \tabularnewline
0.32 & 948.132 & 948.644 & 948.9 & 948.9 & 949.64 & 948.9 & 947.556 & 948.9 \tabularnewline
0.34 & 951.638 & 954.328 & 952.6 & 952.6 & 961.24 & 952.6 & 972.472 & 952.6 \tabularnewline
0.36 & 973.336 & 982.712 & 974.2 & 974.2 & 990.16 & 974.2 & 992.288 & 974.2 \tabularnewline
0.38 & 1006.56 & 1018.72 & 1032.8 & 1032.8 & 1026.4 & 1000.8 & 1014.88 & 1032.8 \tabularnewline
0.4 & 1035.36 & 1037.92 & 1039.2 & 1039.2 & 1039.2 & 1032.8 & 1034.08 & 1039.2 \tabularnewline
0.42 & 1046.33 & 1050.964 & 1050.7 & 1050.7 & 1052.02 & 1050.7 & 1057.036 & 1050.7 \tabularnewline
0.44 & 1056.244 & 1062.368 & 1057.3 & 1057.3 & 1064.54 & 1057.3 & 1070.332 & 1057.3 \tabularnewline
0.46 & 1075.724 & 1078.208 & 1080.8 & 1080.8 & 1078.64 & 1075.4 & 1077.992 & 1080.8 \tabularnewline
0.48 & 1085.252 & 1092.884 & 1096.7 & 1096.7 & 1093.52 & 1080.8 & 1084.616 & 1096.7 \tabularnewline
0.5 & 1107.55 & 1118.4 & 1118.4 & 1118.4 & 1118.4 & 1118.4 & 1118.4 & 1118.4 \tabularnewline
0.52 & 1155.984 & 1172.808 & 1170.6 & 1170.6 & 1172.44 & 1170.6 & 1177.592 & 1170.6 \tabularnewline
0.54 & 1179.248 & 1195.784 & 1179.8 & 1179.8 & 1193.12 & 1179.8 & 1197.116 & 1179.8 \tabularnewline
0.56 & 1215.324 & 1223.108 & 1227 & 1227 & 1221.44 & 1213.1 & 1216.992 & 1227 \tabularnewline
0.58 & 1230.534 & 1235.928 & 1236.3 & 1236.3 & 1234.44 & 1227 & 1227.372 & 1236.3 \tabularnewline
0.6 & 1244.64 & 1250.46 & 1250.2 & 1250.2 & 1250.2 & 1250.2 & 1251.24 & 1250.2 \tabularnewline
0.62 & 1251.266 & 1254.272 & 1251.5 & 1251.5 & 1252.76 & 1251.5 & 1255.028 & 1251.5 \tabularnewline
0.64 & 1258.064 & 1262.288 & 1264.4 & 1264.4 & 1260.44 & 1257.8 & 1259.912 & 1264.4 \tabularnewline
0.66 & 1264.686 & 1265.412 & 1265.5 & 1265.5 & 1265.06 & 1264.4 & 1264.488 & 1265.5 \tabularnewline
0.68 & 1269.82 & 1278.708 & 1274.5 & 1274.5 & 1272.7 & 1265.5 & 1296.592 & 1274.5 \tabularnewline
0.7 & 1292.91 & 1307.12 & 1300.8 & 1300.8 & 1300.8 & 1300.8 & 1310.28 & 1300.8 \tabularnewline
0.72 & 1315.336 & 1321.272 & 1316.6 & 1316.6 & 1318.06 & 1316.6 & 1319.228 & 1323.9 \tabularnewline
0.74 & 1325.048 & 1331.116 & 1332.1 & 1332.1 & 1327.18 & 1323.9 & 1324.884 & 1332.1 \tabularnewline
0.76 & 1337.968 & 1351.22 & 1348.4 & 1348.4 & 1341.88 & 1332.1 & 1369.08 & 1348.4 \tabularnewline
0.78 & 1362.03 & 1380.36 & 1371.9 & 1371.9 & 1367.2 & 1371.9 & 1386.94 & 1371.9 \tabularnewline
0.8 & 1390.7 & 1400.14 & 1395.4 & 1395.4 & 1395.4 & 1395.4 & 1398.56 & 1403.3 \tabularnewline
0.82 & 1403.308 & 1403.636 & 1403.7 & 1403.7 & 1403.38 & 1403.3 & 1403.364 & 1403.7 \tabularnewline
0.84 & 1407.3 & 1420.26 & 1418.7 & 1418.7 & 1409.7 & 1403.7 & 1436.64 & 1418.7 \tabularnewline
0.86 & 1427.67 & 1441.496 & 1438.2 & 1438.2 & 1430.4 & 1418.7 & 1445.204 & 1438.2 \tabularnewline
0.88 & 1445.204 & 1450.348 & 1448.5 & 1448.5 & 1446.44 & 1448.5 & 1449.952 & 1451.8 \tabularnewline
0.9 & 1451.47 & 1469.72 & 1451.8 & 1451.8 & 1451.8 & 1451.8 & 1456.28 & 1474.2 \tabularnewline
0.92 & 1476.348 & 1492.96 & 1492.1 & 1492.1 & 1477.78 & 1474.2 & 1512.74 & 1492.1 \tabularnewline
0.94 & 1499.41 & 1517.492 & 1513.6 & 1513.6 & 1500.7 & 1492.1 & 1523.608 & 1513.6 \tabularnewline
0.96 & 1521.384 & 1537.224 & 1527.5 & 1527.5 & 1521.94 & 1527.5 & 1536.476 & 1546.2 \tabularnewline
0.98 & 1542.086 & 1558.36 & 1546.2 & 1546.2 & 1542.46 & 1546.2 & 1550.04 & 1562.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62941&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]639.048[/C][C]639.916[/C][C]672.9[/C][C]672.9[/C][C]674.56[/C][C]629.5[/C][C]662.484[/C][C]629.5[/C][/ROW]
[ROW][C]0.04[/C][C]676.552[/C][C]676.884[/C][C]681.2[/C][C]681.2[/C][C]684.24[/C][C]672.9[/C][C]677.216[/C][C]672.9[/C][/ROW]
[ROW][C]0.06[/C][C]686.216[/C][C]686.672[/C][C]688.8[/C][C]688.8[/C][C]705[/C][C]688.8[/C][C]683.328[/C][C]688.8[/C][/ROW]
[ROW][C]0.08[/C][C]712.56[/C][C]714.72[/C][C]715.8[/C][C]715.8[/C][C]740.44[/C][C]715.8[/C][C]689.88[/C][C]715.8[/C][/ROW]
[ROW][C]0.1[/C][C]747.48[/C][C]748.36[/C][C]755.4[/C][C]755.4[/C][C]755.4[/C][C]746.6[/C][C]753.64[/C][C]746.6[/C][/ROW]
[ROW][C]0.12[/C][C]757.064[/C][C]757.688[/C][C]760.6[/C][C]760.6[/C][C]761.66[/C][C]755.4[/C][C]758.312[/C][C]755.4[/C][/ROW]
[ROW][C]0.14[/C][C]763.462[/C][C]764.204[/C][C]765.9[/C][C]765.9[/C][C]773.86[/C][C]765.9[/C][C]762.296[/C][C]765.9[/C][/ROW]
[ROW][C]0.16[/C][C]781.024[/C][C]784.208[/C][C]785.8[/C][C]785.8[/C][C]789.52[/C][C]785.8[/C][C]767.492[/C][C]785.8[/C][/ROW]
[ROW][C]0.18[/C][C]791.876[/C][C]796.368[/C][C]792[/C][C]792[/C][C]813.84[/C][C]792[/C][C]814.932[/C][C]792[/C][/ROW]
[ROW][C]0.2[/C][C]822.8[/C][C]826.3[/C][C]836.8[/C][C]836.8[/C][C]836.8[/C][C]819.3[/C][C]829.8[/C][C]819.3[/C][/ROW]
[ROW][C]0.22[/C][C]842.092[/C][C]844.864[/C][C]849.4[/C][C]849.4[/C][C]855.6[/C][C]836.8[/C][C]841.336[/C][C]849.4[/C][/ROW]
[ROW][C]0.24[/C][C]869.24[/C][C]876.68[/C][C]880.4[/C][C]880.4[/C][C]888.28[/C][C]880.4[/C][C]853.12[/C][C]880.4[/C][/ROW]
[ROW][C]0.26[/C][C]897.342[/C][C]900.676[/C][C]900.1[/C][C]900.1[/C][C]902.98[/C][C]900.1[/C][C]904.324[/C][C]900.1[/C][/ROW]
[ROW][C]0.28[/C][C]907.484[/C][C]916.528[/C][C]937.2[/C][C]937.2[/C][C]930.74[/C][C]904.9[/C][C]925.572[/C][C]904.9[/C][/ROW]
[ROW][C]0.3[/C][C]940.23[/C][C]943.26[/C][C]947.3[/C][C]947.3[/C][C]947.3[/C][C]937.2[/C][C]941.24[/C][C]947.3[/C][/ROW]
[ROW][C]0.32[/C][C]948.132[/C][C]948.644[/C][C]948.9[/C][C]948.9[/C][C]949.64[/C][C]948.9[/C][C]947.556[/C][C]948.9[/C][/ROW]
[ROW][C]0.34[/C][C]951.638[/C][C]954.328[/C][C]952.6[/C][C]952.6[/C][C]961.24[/C][C]952.6[/C][C]972.472[/C][C]952.6[/C][/ROW]
[ROW][C]0.36[/C][C]973.336[/C][C]982.712[/C][C]974.2[/C][C]974.2[/C][C]990.16[/C][C]974.2[/C][C]992.288[/C][C]974.2[/C][/ROW]
[ROW][C]0.38[/C][C]1006.56[/C][C]1018.72[/C][C]1032.8[/C][C]1032.8[/C][C]1026.4[/C][C]1000.8[/C][C]1014.88[/C][C]1032.8[/C][/ROW]
[ROW][C]0.4[/C][C]1035.36[/C][C]1037.92[/C][C]1039.2[/C][C]1039.2[/C][C]1039.2[/C][C]1032.8[/C][C]1034.08[/C][C]1039.2[/C][/ROW]
[ROW][C]0.42[/C][C]1046.33[/C][C]1050.964[/C][C]1050.7[/C][C]1050.7[/C][C]1052.02[/C][C]1050.7[/C][C]1057.036[/C][C]1050.7[/C][/ROW]
[ROW][C]0.44[/C][C]1056.244[/C][C]1062.368[/C][C]1057.3[/C][C]1057.3[/C][C]1064.54[/C][C]1057.3[/C][C]1070.332[/C][C]1057.3[/C][/ROW]
[ROW][C]0.46[/C][C]1075.724[/C][C]1078.208[/C][C]1080.8[/C][C]1080.8[/C][C]1078.64[/C][C]1075.4[/C][C]1077.992[/C][C]1080.8[/C][/ROW]
[ROW][C]0.48[/C][C]1085.252[/C][C]1092.884[/C][C]1096.7[/C][C]1096.7[/C][C]1093.52[/C][C]1080.8[/C][C]1084.616[/C][C]1096.7[/C][/ROW]
[ROW][C]0.5[/C][C]1107.55[/C][C]1118.4[/C][C]1118.4[/C][C]1118.4[/C][C]1118.4[/C][C]1118.4[/C][C]1118.4[/C][C]1118.4[/C][/ROW]
[ROW][C]0.52[/C][C]1155.984[/C][C]1172.808[/C][C]1170.6[/C][C]1170.6[/C][C]1172.44[/C][C]1170.6[/C][C]1177.592[/C][C]1170.6[/C][/ROW]
[ROW][C]0.54[/C][C]1179.248[/C][C]1195.784[/C][C]1179.8[/C][C]1179.8[/C][C]1193.12[/C][C]1179.8[/C][C]1197.116[/C][C]1179.8[/C][/ROW]
[ROW][C]0.56[/C][C]1215.324[/C][C]1223.108[/C][C]1227[/C][C]1227[/C][C]1221.44[/C][C]1213.1[/C][C]1216.992[/C][C]1227[/C][/ROW]
[ROW][C]0.58[/C][C]1230.534[/C][C]1235.928[/C][C]1236.3[/C][C]1236.3[/C][C]1234.44[/C][C]1227[/C][C]1227.372[/C][C]1236.3[/C][/ROW]
[ROW][C]0.6[/C][C]1244.64[/C][C]1250.46[/C][C]1250.2[/C][C]1250.2[/C][C]1250.2[/C][C]1250.2[/C][C]1251.24[/C][C]1250.2[/C][/ROW]
[ROW][C]0.62[/C][C]1251.266[/C][C]1254.272[/C][C]1251.5[/C][C]1251.5[/C][C]1252.76[/C][C]1251.5[/C][C]1255.028[/C][C]1251.5[/C][/ROW]
[ROW][C]0.64[/C][C]1258.064[/C][C]1262.288[/C][C]1264.4[/C][C]1264.4[/C][C]1260.44[/C][C]1257.8[/C][C]1259.912[/C][C]1264.4[/C][/ROW]
[ROW][C]0.66[/C][C]1264.686[/C][C]1265.412[/C][C]1265.5[/C][C]1265.5[/C][C]1265.06[/C][C]1264.4[/C][C]1264.488[/C][C]1265.5[/C][/ROW]
[ROW][C]0.68[/C][C]1269.82[/C][C]1278.708[/C][C]1274.5[/C][C]1274.5[/C][C]1272.7[/C][C]1265.5[/C][C]1296.592[/C][C]1274.5[/C][/ROW]
[ROW][C]0.7[/C][C]1292.91[/C][C]1307.12[/C][C]1300.8[/C][C]1300.8[/C][C]1300.8[/C][C]1300.8[/C][C]1310.28[/C][C]1300.8[/C][/ROW]
[ROW][C]0.72[/C][C]1315.336[/C][C]1321.272[/C][C]1316.6[/C][C]1316.6[/C][C]1318.06[/C][C]1316.6[/C][C]1319.228[/C][C]1323.9[/C][/ROW]
[ROW][C]0.74[/C][C]1325.048[/C][C]1331.116[/C][C]1332.1[/C][C]1332.1[/C][C]1327.18[/C][C]1323.9[/C][C]1324.884[/C][C]1332.1[/C][/ROW]
[ROW][C]0.76[/C][C]1337.968[/C][C]1351.22[/C][C]1348.4[/C][C]1348.4[/C][C]1341.88[/C][C]1332.1[/C][C]1369.08[/C][C]1348.4[/C][/ROW]
[ROW][C]0.78[/C][C]1362.03[/C][C]1380.36[/C][C]1371.9[/C][C]1371.9[/C][C]1367.2[/C][C]1371.9[/C][C]1386.94[/C][C]1371.9[/C][/ROW]
[ROW][C]0.8[/C][C]1390.7[/C][C]1400.14[/C][C]1395.4[/C][C]1395.4[/C][C]1395.4[/C][C]1395.4[/C][C]1398.56[/C][C]1403.3[/C][/ROW]
[ROW][C]0.82[/C][C]1403.308[/C][C]1403.636[/C][C]1403.7[/C][C]1403.7[/C][C]1403.38[/C][C]1403.3[/C][C]1403.364[/C][C]1403.7[/C][/ROW]
[ROW][C]0.84[/C][C]1407.3[/C][C]1420.26[/C][C]1418.7[/C][C]1418.7[/C][C]1409.7[/C][C]1403.7[/C][C]1436.64[/C][C]1418.7[/C][/ROW]
[ROW][C]0.86[/C][C]1427.67[/C][C]1441.496[/C][C]1438.2[/C][C]1438.2[/C][C]1430.4[/C][C]1418.7[/C][C]1445.204[/C][C]1438.2[/C][/ROW]
[ROW][C]0.88[/C][C]1445.204[/C][C]1450.348[/C][C]1448.5[/C][C]1448.5[/C][C]1446.44[/C][C]1448.5[/C][C]1449.952[/C][C]1451.8[/C][/ROW]
[ROW][C]0.9[/C][C]1451.47[/C][C]1469.72[/C][C]1451.8[/C][C]1451.8[/C][C]1451.8[/C][C]1451.8[/C][C]1456.28[/C][C]1474.2[/C][/ROW]
[ROW][C]0.92[/C][C]1476.348[/C][C]1492.96[/C][C]1492.1[/C][C]1492.1[/C][C]1477.78[/C][C]1474.2[/C][C]1512.74[/C][C]1492.1[/C][/ROW]
[ROW][C]0.94[/C][C]1499.41[/C][C]1517.492[/C][C]1513.6[/C][C]1513.6[/C][C]1500.7[/C][C]1492.1[/C][C]1523.608[/C][C]1513.6[/C][/ROW]
[ROW][C]0.96[/C][C]1521.384[/C][C]1537.224[/C][C]1527.5[/C][C]1527.5[/C][C]1521.94[/C][C]1527.5[/C][C]1536.476[/C][C]1546.2[/C][/ROW]
[ROW][C]0.98[/C][C]1542.086[/C][C]1558.36[/C][C]1546.2[/C][C]1546.2[/C][C]1542.46[/C][C]1546.2[/C][C]1550.04[/C][C]1562.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62941&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62941&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
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)
0.02	639.048	639.916	672.9	672.9	674.56	629.5	662.484	629.5
0.04	676.552	676.884	681.2	681.2	684.24	672.9	677.216	672.9
0.06	686.216	686.672	688.8	688.8	705	688.8	683.328	688.8
0.08	712.56	714.72	715.8	715.8	740.44	715.8	689.88	715.8
0.1	747.48	748.36	755.4	755.4	755.4	746.6	753.64	746.6
0.12	757.064	757.688	760.6	760.6	761.66	755.4	758.312	755.4
0.14	763.462	764.204	765.9	765.9	773.86	765.9	762.296	765.9
0.16	781.024	784.208	785.8	785.8	789.52	785.8	767.492	785.8
0.18	791.876	796.368	792	792	813.84	792	814.932	792
0.2	822.8	826.3	836.8	836.8	836.8	819.3	829.8	819.3
0.22	842.092	844.864	849.4	849.4	855.6	836.8	841.336	849.4
0.24	869.24	876.68	880.4	880.4	888.28	880.4	853.12	880.4
0.26	897.342	900.676	900.1	900.1	902.98	900.1	904.324	900.1
0.28	907.484	916.528	937.2	937.2	930.74	904.9	925.572	904.9
0.3	940.23	943.26	947.3	947.3	947.3	937.2	941.24	947.3
0.32	948.132	948.644	948.9	948.9	949.64	948.9	947.556	948.9
0.34	951.638	954.328	952.6	952.6	961.24	952.6	972.472	952.6
0.36	973.336	982.712	974.2	974.2	990.16	974.2	992.288	974.2
0.38	1006.56	1018.72	1032.8	1032.8	1026.4	1000.8	1014.88	1032.8
0.4	1035.36	1037.92	1039.2	1039.2	1039.2	1032.8	1034.08	1039.2
0.42	1046.33	1050.964	1050.7	1050.7	1052.02	1050.7	1057.036	1050.7
0.44	1056.244	1062.368	1057.3	1057.3	1064.54	1057.3	1070.332	1057.3
0.46	1075.724	1078.208	1080.8	1080.8	1078.64	1075.4	1077.992	1080.8
0.48	1085.252	1092.884	1096.7	1096.7	1093.52	1080.8	1084.616	1096.7
0.5	1107.55	1118.4	1118.4	1118.4	1118.4	1118.4	1118.4	1118.4
0.52	1155.984	1172.808	1170.6	1170.6	1172.44	1170.6	1177.592	1170.6
0.54	1179.248	1195.784	1179.8	1179.8	1193.12	1179.8	1197.116	1179.8
0.56	1215.324	1223.108	1227	1227	1221.44	1213.1	1216.992	1227
0.58	1230.534	1235.928	1236.3	1236.3	1234.44	1227	1227.372	1236.3
0.6	1244.64	1250.46	1250.2	1250.2	1250.2	1250.2	1251.24	1250.2
0.62	1251.266	1254.272	1251.5	1251.5	1252.76	1251.5	1255.028	1251.5
0.64	1258.064	1262.288	1264.4	1264.4	1260.44	1257.8	1259.912	1264.4
0.66	1264.686	1265.412	1265.5	1265.5	1265.06	1264.4	1264.488	1265.5
0.68	1269.82	1278.708	1274.5	1274.5	1272.7	1265.5	1296.592	1274.5
0.7	1292.91	1307.12	1300.8	1300.8	1300.8	1300.8	1310.28	1300.8
0.72	1315.336	1321.272	1316.6	1316.6	1318.06	1316.6	1319.228	1323.9
0.74	1325.048	1331.116	1332.1	1332.1	1327.18	1323.9	1324.884	1332.1
0.76	1337.968	1351.22	1348.4	1348.4	1341.88	1332.1	1369.08	1348.4
0.78	1362.03	1380.36	1371.9	1371.9	1367.2	1371.9	1386.94	1371.9
0.8	1390.7	1400.14	1395.4	1395.4	1395.4	1395.4	1398.56	1403.3
0.82	1403.308	1403.636	1403.7	1403.7	1403.38	1403.3	1403.364	1403.7
0.84	1407.3	1420.26	1418.7	1418.7	1409.7	1403.7	1436.64	1418.7
0.86	1427.67	1441.496	1438.2	1438.2	1430.4	1418.7	1445.204	1438.2
0.88	1445.204	1450.348	1448.5	1448.5	1446.44	1448.5	1449.952	1451.8
0.9	1451.47	1469.72	1451.8	1451.8	1451.8	1451.8	1456.28	1474.2
0.92	1476.348	1492.96	1492.1	1492.1	1477.78	1474.2	1512.74	1492.1
0.94	1499.41	1517.492	1513.6	1513.6	1500.7	1492.1	1523.608	1513.6
0.96	1521.384	1537.224	1527.5	1527.5	1521.94	1527.5	1536.476	1546.2
0.98	1542.086	1558.36	1546.2	1546.2	1542.46	1546.2	1550.04	1562.2

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code