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Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationWed, 08 Aug 2012 03:36:20 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Aug/08/t1344411454vn6a8oyu75m9821.htm/, Retrieved Fri, 03 May 2024 18:04:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169092, Retrieved Fri, 03 May 2024 18:04:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVan der Smissen Britt
Estimated Impact115
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Tijdreeks A-Stap 1] [2012-08-07 06:32:31] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP   [Histogram] [Tijdreeks A-Stap 3] [2012-08-07 06:54:24] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Harrell-Davis Quantiles] [Tijdreeks A-stap 12] [2012-08-08 07:36:20] [b3616d670e39c9c081ac68ec1f5d1a32] [Current]
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Dataseries X:
95870
95523
95208
94541
101097
100781
95870
92581
92928
92928
93244
93910
93559
96190
97172
96190
99799
97488
92261
90964
90964
91599
89004
90964
89319
90964
93559
94541
96852
95870
89981
87670
86692
87670
86057
86692
84728
88021
89635
89981
96190
96190
88021
86057
86057
87039
82764
80799
78524
79186
82133
79821
86057
87039
80799
78524
77221
78524
74910
73613
68390
69688
70004
70355
76559
75893
68390
65097
63799
65444
59208
54964
47115
47777
47777
47115
52684
53004
46448
45151
42524
46133
39577
35653
28146
29764
27800
28462
33373
34355
31093
30742
30742
35017
27484
22573
14058
20929
19946
20293
28146
27164
23555
25204
25204
31093
24222
20293
14058
22258
21595
21911
28782
28146
25835
26186
27800
31409
25835
21275




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169092&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169092&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169092&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'Gertrude Mary Cox' @ cox.wessa.net







Harrell-Davis Quantiles
quantilesvaluestandard error
0.0115163.2673943572318.16523038948
0.0217310.73778823882773.82773187739
0.0319184.5968056661742.0719429425
0.0420319.75117724471035.85586342159
0.0520998.1191917876902.266232581321
0.0621526.25120250691000.50983455658
0.0722045.29637554271170.48574525716
0.0822598.39224564521353.3778435294
0.0923188.51955124641501.17560349843
0.123800.05153332891581.55929255788
0.1124409.89416389261590.67508158425
0.1224996.9591355851548.18275385876
0.1325547.92686285131480.7303547458
0.1426058.03786546431408.17635144175
0.1526528.90772527041341.59533433055
0.1626966.25270589581289.76953289872
0.1727378.96055609751265.5428459699
0.1827779.13325811911285.91382203412
0.1928182.03831078891366.22886154262
0.228605.39473924081515.15622398674
0.2129068.24833852621735.19249522493
0.2229590.05513353012027.56210556818
0.2330190.28733444882395.61911106146
0.2430888.25772035842843.26229879258
0.2531702.45737747893368.80995167395
0.2632648.84017368573958.89707026388
0.2733738.11118805914584.55482342606
0.2834972.83210412945204.10769140025
0.2936345.61192228925771.42665785723
0.337839.52256050336248.04558926697
0.3139431.16378146696614.98113687084
0.3241095.77693010246879.86044109151
0.3342812.90484644717075.99047629535
0.3444570.71733126597252.62711532382
0.3546367.46146768387458.04250269671
0.3648209.45005477127720.96255640666
0.3750106.2063952618038.98256926273
0.3852064.37104398838378.02386863407
0.3954082.37068566588683.75169800484
0.456147.5226662588898.08678501419
0.4158236.35968454048975.5016114508
0.4260317.87102512828893.03730718479
0.4362358.4771452928654.31022482835
0.4464327.17284393368285.16808650017
0.4566199.46323122117824.70914370208
0.4667959.32946210997314.95801141877
0.4769599.21455569546792.32554192824
0.4871118.62000664796282.48773357522
0.4972522.16126185925801.30114976027
0.573817.81641398745357.22300733656
0.5175015.73808255344956.51609275171
0.5276127.58185401474605.15896964707
0.5377166.02116784644308.51468517807
0.5478144.06837812274069.31978895119
0.5579073.99282029493884.10695809172
0.5679965.91570980073740.86266021755
0.5780826.4269297923620.3097749839
0.5881657.69024202183499.61314478108
0.5982457.42725163673358.04247590415
0.683219.92428328523181.74523524587
0.6183937.88414679092967.7743724172
0.6284604.66803162762723.84016214225
0.6385216.3429427242466.15062317684
0.6485773.01047930112215.8696570985
0.6586279.11470292551993.27640711763
0.6686742.72572330021813.5688956522
0.6787174.06854543381683.77980288006
0.6887583.73331683431601.39610159911
0.6987981.03060399511556.35551220693
0.788372.85895052511534.73819647269
0.7188763.27666669751522.88978786239
0.7289153.76810196241510.23287561697
0.7389544.01374162881490.98677469841
0.7489932.85355600591464.22955755574
0.7590319.10804512651432.13892947931
0.7690702.01063986951397.91138611925
0.7791081.1937799911363.46648706691
0.7891456.3936617341328.32801162541
0.7991827.18822315481290.45061821757
0.892193.05820185041248.68757675502
0.8192553.83655800341204.27135228175
0.8292910.28351953631161.95820507658
0.8393264.28680011231127.31123718555
0.8493618.22975479491102.48170557561
0.8593973.45573786731082.48521298321
0.8694328.34410171691055.48397144636
0.8794676.9943822981006.39061590995
0.8895009.562593125924.31556731561
0.8995314.7743864862808.918295170113
0.995584.2780473589673.36787217748
0.9195817.7870095684542.91544851407
0.9296027.7894077628451.533661360274
0.9396243.1412620971436.88897814044
0.9496512.3766052524526.868421590471
0.9596908.4593325731736.582281494543
0.9697527.11708912821077.21546085213
0.9798441.46336415451453.23024166059
0.9899575.44755168511510.88456474511
0.99100598.351397982932.303750992829

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 15163.267394357 & 2318.16523038948 \tabularnewline
0.02 & 17310.7377882388 & 2773.82773187739 \tabularnewline
0.03 & 19184.596805666 & 1742.0719429425 \tabularnewline
0.04 & 20319.7511772447 & 1035.85586342159 \tabularnewline
0.05 & 20998.1191917876 & 902.266232581321 \tabularnewline
0.06 & 21526.2512025069 & 1000.50983455658 \tabularnewline
0.07 & 22045.2963755427 & 1170.48574525716 \tabularnewline
0.08 & 22598.3922456452 & 1353.3778435294 \tabularnewline
0.09 & 23188.5195512464 & 1501.17560349843 \tabularnewline
0.1 & 23800.0515333289 & 1581.55929255788 \tabularnewline
0.11 & 24409.8941638926 & 1590.67508158425 \tabularnewline
0.12 & 24996.959135585 & 1548.18275385876 \tabularnewline
0.13 & 25547.9268628513 & 1480.7303547458 \tabularnewline
0.14 & 26058.0378654643 & 1408.17635144175 \tabularnewline
0.15 & 26528.9077252704 & 1341.59533433055 \tabularnewline
0.16 & 26966.2527058958 & 1289.76953289872 \tabularnewline
0.17 & 27378.9605560975 & 1265.5428459699 \tabularnewline
0.18 & 27779.1332581191 & 1285.91382203412 \tabularnewline
0.19 & 28182.0383107889 & 1366.22886154262 \tabularnewline
0.2 & 28605.3947392408 & 1515.15622398674 \tabularnewline
0.21 & 29068.2483385262 & 1735.19249522493 \tabularnewline
0.22 & 29590.0551335301 & 2027.56210556818 \tabularnewline
0.23 & 30190.2873344488 & 2395.61911106146 \tabularnewline
0.24 & 30888.2577203584 & 2843.26229879258 \tabularnewline
0.25 & 31702.4573774789 & 3368.80995167395 \tabularnewline
0.26 & 32648.8401736857 & 3958.89707026388 \tabularnewline
0.27 & 33738.1111880591 & 4584.55482342606 \tabularnewline
0.28 & 34972.8321041294 & 5204.10769140025 \tabularnewline
0.29 & 36345.6119222892 & 5771.42665785723 \tabularnewline
0.3 & 37839.5225605033 & 6248.04558926697 \tabularnewline
0.31 & 39431.1637814669 & 6614.98113687084 \tabularnewline
0.32 & 41095.7769301024 & 6879.86044109151 \tabularnewline
0.33 & 42812.9048464471 & 7075.99047629535 \tabularnewline
0.34 & 44570.7173312659 & 7252.62711532382 \tabularnewline
0.35 & 46367.4614676838 & 7458.04250269671 \tabularnewline
0.36 & 48209.4500547712 & 7720.96255640666 \tabularnewline
0.37 & 50106.206395261 & 8038.98256926273 \tabularnewline
0.38 & 52064.3710439883 & 8378.02386863407 \tabularnewline
0.39 & 54082.3706856658 & 8683.75169800484 \tabularnewline
0.4 & 56147.522666258 & 8898.08678501419 \tabularnewline
0.41 & 58236.3596845404 & 8975.5016114508 \tabularnewline
0.42 & 60317.8710251282 & 8893.03730718479 \tabularnewline
0.43 & 62358.477145292 & 8654.31022482835 \tabularnewline
0.44 & 64327.1728439336 & 8285.16808650017 \tabularnewline
0.45 & 66199.4632312211 & 7824.70914370208 \tabularnewline
0.46 & 67959.3294621099 & 7314.95801141877 \tabularnewline
0.47 & 69599.2145556954 & 6792.32554192824 \tabularnewline
0.48 & 71118.6200066479 & 6282.48773357522 \tabularnewline
0.49 & 72522.1612618592 & 5801.30114976027 \tabularnewline
0.5 & 73817.8164139874 & 5357.22300733656 \tabularnewline
0.51 & 75015.7380825534 & 4956.51609275171 \tabularnewline
0.52 & 76127.5818540147 & 4605.15896964707 \tabularnewline
0.53 & 77166.0211678464 & 4308.51468517807 \tabularnewline
0.54 & 78144.0683781227 & 4069.31978895119 \tabularnewline
0.55 & 79073.9928202949 & 3884.10695809172 \tabularnewline
0.56 & 79965.9157098007 & 3740.86266021755 \tabularnewline
0.57 & 80826.426929792 & 3620.3097749839 \tabularnewline
0.58 & 81657.6902420218 & 3499.61314478108 \tabularnewline
0.59 & 82457.4272516367 & 3358.04247590415 \tabularnewline
0.6 & 83219.9242832852 & 3181.74523524587 \tabularnewline
0.61 & 83937.8841467909 & 2967.7743724172 \tabularnewline
0.62 & 84604.6680316276 & 2723.84016214225 \tabularnewline
0.63 & 85216.342942724 & 2466.15062317684 \tabularnewline
0.64 & 85773.0104793011 & 2215.8696570985 \tabularnewline
0.65 & 86279.1147029255 & 1993.27640711763 \tabularnewline
0.66 & 86742.7257233002 & 1813.5688956522 \tabularnewline
0.67 & 87174.0685454338 & 1683.77980288006 \tabularnewline
0.68 & 87583.7333168343 & 1601.39610159911 \tabularnewline
0.69 & 87981.0306039951 & 1556.35551220693 \tabularnewline
0.7 & 88372.8589505251 & 1534.73819647269 \tabularnewline
0.71 & 88763.2766666975 & 1522.88978786239 \tabularnewline
0.72 & 89153.7681019624 & 1510.23287561697 \tabularnewline
0.73 & 89544.0137416288 & 1490.98677469841 \tabularnewline
0.74 & 89932.8535560059 & 1464.22955755574 \tabularnewline
0.75 & 90319.1080451265 & 1432.13892947931 \tabularnewline
0.76 & 90702.0106398695 & 1397.91138611925 \tabularnewline
0.77 & 91081.193779991 & 1363.46648706691 \tabularnewline
0.78 & 91456.393661734 & 1328.32801162541 \tabularnewline
0.79 & 91827.1882231548 & 1290.45061821757 \tabularnewline
0.8 & 92193.0582018504 & 1248.68757675502 \tabularnewline
0.81 & 92553.8365580034 & 1204.27135228175 \tabularnewline
0.82 & 92910.2835195363 & 1161.95820507658 \tabularnewline
0.83 & 93264.2868001123 & 1127.31123718555 \tabularnewline
0.84 & 93618.2297547949 & 1102.48170557561 \tabularnewline
0.85 & 93973.4557378673 & 1082.48521298321 \tabularnewline
0.86 & 94328.3441017169 & 1055.48397144636 \tabularnewline
0.87 & 94676.994382298 & 1006.39061590995 \tabularnewline
0.88 & 95009.562593125 & 924.31556731561 \tabularnewline
0.89 & 95314.7743864862 & 808.918295170113 \tabularnewline
0.9 & 95584.2780473589 & 673.36787217748 \tabularnewline
0.91 & 95817.7870095684 & 542.91544851407 \tabularnewline
0.92 & 96027.7894077628 & 451.533661360274 \tabularnewline
0.93 & 96243.1412620971 & 436.88897814044 \tabularnewline
0.94 & 96512.3766052524 & 526.868421590471 \tabularnewline
0.95 & 96908.4593325731 & 736.582281494543 \tabularnewline
0.96 & 97527.1170891282 & 1077.21546085213 \tabularnewline
0.97 & 98441.4633641545 & 1453.23024166059 \tabularnewline
0.98 & 99575.4475516851 & 1510.88456474511 \tabularnewline
0.99 & 100598.351397982 & 932.303750992829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169092&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.01[/C][C]15163.267394357[/C][C]2318.16523038948[/C][/ROW]
[ROW][C]0.02[/C][C]17310.7377882388[/C][C]2773.82773187739[/C][/ROW]
[ROW][C]0.03[/C][C]19184.596805666[/C][C]1742.0719429425[/C][/ROW]
[ROW][C]0.04[/C][C]20319.7511772447[/C][C]1035.85586342159[/C][/ROW]
[ROW][C]0.05[/C][C]20998.1191917876[/C][C]902.266232581321[/C][/ROW]
[ROW][C]0.06[/C][C]21526.2512025069[/C][C]1000.50983455658[/C][/ROW]
[ROW][C]0.07[/C][C]22045.2963755427[/C][C]1170.48574525716[/C][/ROW]
[ROW][C]0.08[/C][C]22598.3922456452[/C][C]1353.3778435294[/C][/ROW]
[ROW][C]0.09[/C][C]23188.5195512464[/C][C]1501.17560349843[/C][/ROW]
[ROW][C]0.1[/C][C]23800.0515333289[/C][C]1581.55929255788[/C][/ROW]
[ROW][C]0.11[/C][C]24409.8941638926[/C][C]1590.67508158425[/C][/ROW]
[ROW][C]0.12[/C][C]24996.959135585[/C][C]1548.18275385876[/C][/ROW]
[ROW][C]0.13[/C][C]25547.9268628513[/C][C]1480.7303547458[/C][/ROW]
[ROW][C]0.14[/C][C]26058.0378654643[/C][C]1408.17635144175[/C][/ROW]
[ROW][C]0.15[/C][C]26528.9077252704[/C][C]1341.59533433055[/C][/ROW]
[ROW][C]0.16[/C][C]26966.2527058958[/C][C]1289.76953289872[/C][/ROW]
[ROW][C]0.17[/C][C]27378.9605560975[/C][C]1265.5428459699[/C][/ROW]
[ROW][C]0.18[/C][C]27779.1332581191[/C][C]1285.91382203412[/C][/ROW]
[ROW][C]0.19[/C][C]28182.0383107889[/C][C]1366.22886154262[/C][/ROW]
[ROW][C]0.2[/C][C]28605.3947392408[/C][C]1515.15622398674[/C][/ROW]
[ROW][C]0.21[/C][C]29068.2483385262[/C][C]1735.19249522493[/C][/ROW]
[ROW][C]0.22[/C][C]29590.0551335301[/C][C]2027.56210556818[/C][/ROW]
[ROW][C]0.23[/C][C]30190.2873344488[/C][C]2395.61911106146[/C][/ROW]
[ROW][C]0.24[/C][C]30888.2577203584[/C][C]2843.26229879258[/C][/ROW]
[ROW][C]0.25[/C][C]31702.4573774789[/C][C]3368.80995167395[/C][/ROW]
[ROW][C]0.26[/C][C]32648.8401736857[/C][C]3958.89707026388[/C][/ROW]
[ROW][C]0.27[/C][C]33738.1111880591[/C][C]4584.55482342606[/C][/ROW]
[ROW][C]0.28[/C][C]34972.8321041294[/C][C]5204.10769140025[/C][/ROW]
[ROW][C]0.29[/C][C]36345.6119222892[/C][C]5771.42665785723[/C][/ROW]
[ROW][C]0.3[/C][C]37839.5225605033[/C][C]6248.04558926697[/C][/ROW]
[ROW][C]0.31[/C][C]39431.1637814669[/C][C]6614.98113687084[/C][/ROW]
[ROW][C]0.32[/C][C]41095.7769301024[/C][C]6879.86044109151[/C][/ROW]
[ROW][C]0.33[/C][C]42812.9048464471[/C][C]7075.99047629535[/C][/ROW]
[ROW][C]0.34[/C][C]44570.7173312659[/C][C]7252.62711532382[/C][/ROW]
[ROW][C]0.35[/C][C]46367.4614676838[/C][C]7458.04250269671[/C][/ROW]
[ROW][C]0.36[/C][C]48209.4500547712[/C][C]7720.96255640666[/C][/ROW]
[ROW][C]0.37[/C][C]50106.206395261[/C][C]8038.98256926273[/C][/ROW]
[ROW][C]0.38[/C][C]52064.3710439883[/C][C]8378.02386863407[/C][/ROW]
[ROW][C]0.39[/C][C]54082.3706856658[/C][C]8683.75169800484[/C][/ROW]
[ROW][C]0.4[/C][C]56147.522666258[/C][C]8898.08678501419[/C][/ROW]
[ROW][C]0.41[/C][C]58236.3596845404[/C][C]8975.5016114508[/C][/ROW]
[ROW][C]0.42[/C][C]60317.8710251282[/C][C]8893.03730718479[/C][/ROW]
[ROW][C]0.43[/C][C]62358.477145292[/C][C]8654.31022482835[/C][/ROW]
[ROW][C]0.44[/C][C]64327.1728439336[/C][C]8285.16808650017[/C][/ROW]
[ROW][C]0.45[/C][C]66199.4632312211[/C][C]7824.70914370208[/C][/ROW]
[ROW][C]0.46[/C][C]67959.3294621099[/C][C]7314.95801141877[/C][/ROW]
[ROW][C]0.47[/C][C]69599.2145556954[/C][C]6792.32554192824[/C][/ROW]
[ROW][C]0.48[/C][C]71118.6200066479[/C][C]6282.48773357522[/C][/ROW]
[ROW][C]0.49[/C][C]72522.1612618592[/C][C]5801.30114976027[/C][/ROW]
[ROW][C]0.5[/C][C]73817.8164139874[/C][C]5357.22300733656[/C][/ROW]
[ROW][C]0.51[/C][C]75015.7380825534[/C][C]4956.51609275171[/C][/ROW]
[ROW][C]0.52[/C][C]76127.5818540147[/C][C]4605.15896964707[/C][/ROW]
[ROW][C]0.53[/C][C]77166.0211678464[/C][C]4308.51468517807[/C][/ROW]
[ROW][C]0.54[/C][C]78144.0683781227[/C][C]4069.31978895119[/C][/ROW]
[ROW][C]0.55[/C][C]79073.9928202949[/C][C]3884.10695809172[/C][/ROW]
[ROW][C]0.56[/C][C]79965.9157098007[/C][C]3740.86266021755[/C][/ROW]
[ROW][C]0.57[/C][C]80826.426929792[/C][C]3620.3097749839[/C][/ROW]
[ROW][C]0.58[/C][C]81657.6902420218[/C][C]3499.61314478108[/C][/ROW]
[ROW][C]0.59[/C][C]82457.4272516367[/C][C]3358.04247590415[/C][/ROW]
[ROW][C]0.6[/C][C]83219.9242832852[/C][C]3181.74523524587[/C][/ROW]
[ROW][C]0.61[/C][C]83937.8841467909[/C][C]2967.7743724172[/C][/ROW]
[ROW][C]0.62[/C][C]84604.6680316276[/C][C]2723.84016214225[/C][/ROW]
[ROW][C]0.63[/C][C]85216.342942724[/C][C]2466.15062317684[/C][/ROW]
[ROW][C]0.64[/C][C]85773.0104793011[/C][C]2215.8696570985[/C][/ROW]
[ROW][C]0.65[/C][C]86279.1147029255[/C][C]1993.27640711763[/C][/ROW]
[ROW][C]0.66[/C][C]86742.7257233002[/C][C]1813.5688956522[/C][/ROW]
[ROW][C]0.67[/C][C]87174.0685454338[/C][C]1683.77980288006[/C][/ROW]
[ROW][C]0.68[/C][C]87583.7333168343[/C][C]1601.39610159911[/C][/ROW]
[ROW][C]0.69[/C][C]87981.0306039951[/C][C]1556.35551220693[/C][/ROW]
[ROW][C]0.7[/C][C]88372.8589505251[/C][C]1534.73819647269[/C][/ROW]
[ROW][C]0.71[/C][C]88763.2766666975[/C][C]1522.88978786239[/C][/ROW]
[ROW][C]0.72[/C][C]89153.7681019624[/C][C]1510.23287561697[/C][/ROW]
[ROW][C]0.73[/C][C]89544.0137416288[/C][C]1490.98677469841[/C][/ROW]
[ROW][C]0.74[/C][C]89932.8535560059[/C][C]1464.22955755574[/C][/ROW]
[ROW][C]0.75[/C][C]90319.1080451265[/C][C]1432.13892947931[/C][/ROW]
[ROW][C]0.76[/C][C]90702.0106398695[/C][C]1397.91138611925[/C][/ROW]
[ROW][C]0.77[/C][C]91081.193779991[/C][C]1363.46648706691[/C][/ROW]
[ROW][C]0.78[/C][C]91456.393661734[/C][C]1328.32801162541[/C][/ROW]
[ROW][C]0.79[/C][C]91827.1882231548[/C][C]1290.45061821757[/C][/ROW]
[ROW][C]0.8[/C][C]92193.0582018504[/C][C]1248.68757675502[/C][/ROW]
[ROW][C]0.81[/C][C]92553.8365580034[/C][C]1204.27135228175[/C][/ROW]
[ROW][C]0.82[/C][C]92910.2835195363[/C][C]1161.95820507658[/C][/ROW]
[ROW][C]0.83[/C][C]93264.2868001123[/C][C]1127.31123718555[/C][/ROW]
[ROW][C]0.84[/C][C]93618.2297547949[/C][C]1102.48170557561[/C][/ROW]
[ROW][C]0.85[/C][C]93973.4557378673[/C][C]1082.48521298321[/C][/ROW]
[ROW][C]0.86[/C][C]94328.3441017169[/C][C]1055.48397144636[/C][/ROW]
[ROW][C]0.87[/C][C]94676.994382298[/C][C]1006.39061590995[/C][/ROW]
[ROW][C]0.88[/C][C]95009.562593125[/C][C]924.31556731561[/C][/ROW]
[ROW][C]0.89[/C][C]95314.7743864862[/C][C]808.918295170113[/C][/ROW]
[ROW][C]0.9[/C][C]95584.2780473589[/C][C]673.36787217748[/C][/ROW]
[ROW][C]0.91[/C][C]95817.7870095684[/C][C]542.91544851407[/C][/ROW]
[ROW][C]0.92[/C][C]96027.7894077628[/C][C]451.533661360274[/C][/ROW]
[ROW][C]0.93[/C][C]96243.1412620971[/C][C]436.88897814044[/C][/ROW]
[ROW][C]0.94[/C][C]96512.3766052524[/C][C]526.868421590471[/C][/ROW]
[ROW][C]0.95[/C][C]96908.4593325731[/C][C]736.582281494543[/C][/ROW]
[ROW][C]0.96[/C][C]97527.1170891282[/C][C]1077.21546085213[/C][/ROW]
[ROW][C]0.97[/C][C]98441.4633641545[/C][C]1453.23024166059[/C][/ROW]
[ROW][C]0.98[/C][C]99575.4475516851[/C][C]1510.88456474511[/C][/ROW]
[ROW][C]0.99[/C][C]100598.351397982[/C][C]932.303750992829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169092&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169092&T=1

As an alternative you can also use a QR Code:  

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

Harrell-Davis Quantiles
quantilesvaluestandard error
0.0115163.2673943572318.16523038948
0.0217310.73778823882773.82773187739
0.0319184.5968056661742.0719429425
0.0420319.75117724471035.85586342159
0.0520998.1191917876902.266232581321
0.0621526.25120250691000.50983455658
0.0722045.29637554271170.48574525716
0.0822598.39224564521353.3778435294
0.0923188.51955124641501.17560349843
0.123800.05153332891581.55929255788
0.1124409.89416389261590.67508158425
0.1224996.9591355851548.18275385876
0.1325547.92686285131480.7303547458
0.1426058.03786546431408.17635144175
0.1526528.90772527041341.59533433055
0.1626966.25270589581289.76953289872
0.1727378.96055609751265.5428459699
0.1827779.13325811911285.91382203412
0.1928182.03831078891366.22886154262
0.228605.39473924081515.15622398674
0.2129068.24833852621735.19249522493
0.2229590.05513353012027.56210556818
0.2330190.28733444882395.61911106146
0.2430888.25772035842843.26229879258
0.2531702.45737747893368.80995167395
0.2632648.84017368573958.89707026388
0.2733738.11118805914584.55482342606
0.2834972.83210412945204.10769140025
0.2936345.61192228925771.42665785723
0.337839.52256050336248.04558926697
0.3139431.16378146696614.98113687084
0.3241095.77693010246879.86044109151
0.3342812.90484644717075.99047629535
0.3444570.71733126597252.62711532382
0.3546367.46146768387458.04250269671
0.3648209.45005477127720.96255640666
0.3750106.2063952618038.98256926273
0.3852064.37104398838378.02386863407
0.3954082.37068566588683.75169800484
0.456147.5226662588898.08678501419
0.4158236.35968454048975.5016114508
0.4260317.87102512828893.03730718479
0.4362358.4771452928654.31022482835
0.4464327.17284393368285.16808650017
0.4566199.46323122117824.70914370208
0.4667959.32946210997314.95801141877
0.4769599.21455569546792.32554192824
0.4871118.62000664796282.48773357522
0.4972522.16126185925801.30114976027
0.573817.81641398745357.22300733656
0.5175015.73808255344956.51609275171
0.5276127.58185401474605.15896964707
0.5377166.02116784644308.51468517807
0.5478144.06837812274069.31978895119
0.5579073.99282029493884.10695809172
0.5679965.91570980073740.86266021755
0.5780826.4269297923620.3097749839
0.5881657.69024202183499.61314478108
0.5982457.42725163673358.04247590415
0.683219.92428328523181.74523524587
0.6183937.88414679092967.7743724172
0.6284604.66803162762723.84016214225
0.6385216.3429427242466.15062317684
0.6485773.01047930112215.8696570985
0.6586279.11470292551993.27640711763
0.6686742.72572330021813.5688956522
0.6787174.06854543381683.77980288006
0.6887583.73331683431601.39610159911
0.6987981.03060399511556.35551220693
0.788372.85895052511534.73819647269
0.7188763.27666669751522.88978786239
0.7289153.76810196241510.23287561697
0.7389544.01374162881490.98677469841
0.7489932.85355600591464.22955755574
0.7590319.10804512651432.13892947931
0.7690702.01063986951397.91138611925
0.7791081.1937799911363.46648706691
0.7891456.3936617341328.32801162541
0.7991827.18822315481290.45061821757
0.892193.05820185041248.68757675502
0.8192553.83655800341204.27135228175
0.8292910.28351953631161.95820507658
0.8393264.28680011231127.31123718555
0.8493618.22975479491102.48170557561
0.8593973.45573786731082.48521298321
0.8694328.34410171691055.48397144636
0.8794676.9943822981006.39061590995
0.8895009.562593125924.31556731561
0.8995314.7743864862808.918295170113
0.995584.2780473589673.36787217748
0.9195817.7870095684542.91544851407
0.9296027.7894077628451.533661360274
0.9396243.1412620971436.88897814044
0.9496512.3766052524526.868421590471
0.9596908.4593325731736.582281494543
0.9697527.11708912821077.21546085213
0.9798441.46336415451453.23024166059
0.9899575.44755168511510.88456474511
0.99100598.351397982932.303750992829



Parameters (Session):
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par3 <- '0.01'
par2 <- '0.99'
par1 <- '0.01'
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
library(Hmisc)
myseq <- seq(par1, par2, par3)
hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE)
bitmap(file='test1.png')
plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'quantiles',header=TRUE)
a<-table.element(a,'value',header=TRUE)
a<-table.element(a,'standard error',header=TRUE)
a<-table.row.end(a)
length(hd)
for (i in 1:length(hd))
{
a<-table.row.start(a)
a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE)
a<-table.element(a,as.matrix(hd[i])[1,1])
a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')