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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 29 Nov 2011 07:40:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/29/t1322570530tucr06wug32dq57.htm/, Retrieved Fri, 19 Apr 2024 18:58:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148281, Retrieved Fri, 19 Apr 2024 18:58:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Central Tendency] [Workshop 8, Robus...] [2010-11-28 19:41:12] [d946de7cca328fbcf207448a112523ab]
-         [Central Tendency] [Workshop 8, Centr...] [2010-11-29 20:08:54] [3635fb7041b1998c5a1332cf9de22bce]
-           [Central Tendency] [Workshop 8 centra...] [2010-11-30 10:54:04] [a9e130f95bad0a0597234e75c6380c5a]
- R  D          [Central Tendency] [WS8 - Mini-tutori...] [2011-11-29 12:40:23] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D            [Central Tendency] [Paper Deel 2 - Da...] [2011-12-20 10:03:48] [95a4a8598e82ac3272c4dca488d0ba38]
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Dataseries X:
9 700
9 081
9 084
9 743
8 587
9 731
9 563
9 998
9 437
10 038
9 918
9 252
9 737
9 035
9 133
9 487
8 700
9 627
8 947
9 283
8 829
9 947
9 628
9 318
9 605
8 640
9 214
9 567
8 547
9 185
9 470
9 123
9 278
10 170
9 434
9 655
9 429
8 739
9 552
9 687
9 019
9 672
9 206
9 069
9 788
10 312
10 105
9 863
9 656
9 295
9 946
9 701
9 049
10 190
9 706
9 765
9 893
9 994
10 433
10 073
10 112
9 266
9 820
10 097
9 115
10 411
9 678
10 408
10 153
10 368
10 581
10 597
10 680
9 738
9 556




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148281&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148281&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148281&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' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean9605.5066666666758.0892428469724165.357752931485
Geometric Mean9592.4687602401
Harmonic Mean9579.39088375951
Quadratic Mean9618.49577498131
Winsorized Mean ( 1 / 25 )9604.9333333333357.6930627501218166.483332232402
Winsorized Mean ( 2 / 25 )9605.9257.2648022014498167.745624375121
Winsorized Mean ( 3 / 25 )9602.455.4455499477551173.18612601098
Winsorized Mean ( 4 / 25 )9603.3066666666754.7592337791909175.373284173235
Winsorized Mean ( 5 / 25 )9609.1066666666753.4873886738467179.651818959806
Winsorized Mean ( 6 / 25 )9615.3466666666751.0786762628865188.24580764739
Winsorized Mean ( 7 / 25 )9616.8448.9059072317666196.639640165052
Winsorized Mean ( 8 / 25 )9605.5333333333346.2580982277877207.650848204633
Winsorized Mean ( 9 / 25 )9604.8133333333345.5736160962029210.753812316719
Winsorized Mean ( 10 / 25 )9605.2133333333344.7605975909247214.590819834827
Winsorized Mean ( 11 / 25 )9600.9643.5011460551111220.705909399183
Winsorized Mean ( 12 / 25 )9600.3243.2464430032394221.990973900001
Winsorized Mean ( 13 / 25 )9604.3066666666742.1727890295927227.737052437469
Winsorized Mean ( 14 / 25 )9601.3241.2387387194513232.82283353325
Winsorized Mean ( 15 / 25 )9596.3239.8595650066897240.753254542277
Winsorized Mean ( 16 / 25 )9598.8836.8826088073015260.254909031808
Winsorized Mean ( 17 / 25 )9602.7333333333336.0347146604585266.48562154068
Winsorized Mean ( 18 / 25 )9593.3733333333334.1294291826912281.088010056688
Winsorized Mean ( 19 / 25 )9602.7466666666732.671866252855293.914849930789
Winsorized Mean ( 20 / 25 )9599.0133333333331.082699880027308.821735897576
Winsorized Mean ( 21 / 25 )9595.3733333333329.6357026789188323.777486813531
Winsorized Mean ( 22 / 25 )9588.0428.2461920577937339.445401361791
Winsorized Mean ( 23 / 25 )9578.5333333333326.0106030585888368.254950173885
Winsorized Mean ( 24 / 25 )9575.6533333333323.6627848104357404.671445480513
Winsorized Mean ( 25 / 25 )9604.9866666666717.4507749726809550.404591297705
Trimmed Mean ( 1 / 25 )9605.2876712328855.9488564276353171.679785513694
Trimmed Mean ( 2 / 25 )9605.6619718309953.8877100014464178.253296931214
Trimmed Mean ( 3 / 25 )9605.5217391304351.7150885848444185.73924945273
Trimmed Mean ( 4 / 25 )9606.6865671641849.9745308671686192.231650812262
Trimmed Mean ( 5 / 25 )9607.6615384615448.1481052273321199.54391752487
Trimmed Mean ( 6 / 25 )9607.3174603174646.3656509941688207.207647349235
Trimmed Mean ( 7 / 25 )9605.6721311475444.9109423624806213.882667026206
Trimmed Mean ( 8 / 25 )9603.6440677966143.7130658173422219.697335069703
Trimmed Mean ( 9 / 25 )9603.3333333333342.8894242805979223.909121990188
Trimmed Mean ( 10 / 25 )9603.1090909090942.0168851157863228.553569938508
Trimmed Mean ( 11 / 25 )9602.8113207547241.100765203254233.640694358519
Trimmed Mean ( 12 / 25 )9603.0588235294140.2154629490649238.790209519463
Trimmed Mean ( 13 / 25 )9603.4081632653139.1377073251118245.374826979288
Trimmed Mean ( 14 / 25 )9603.2978723404237.9914532831502252.775217646113
Trimmed Mean ( 15 / 25 )9603.5333333333336.716324500806261.560313127817
Trimmed Mean ( 16 / 25 )9604.3720930232635.3672556491853271.561135200618
Trimmed Mean ( 17 / 25 )960534.2888554745722280.120169281324
Trimmed Mean ( 18 / 25 )9605.2564102564133.0384946613106290.729238989952
Trimmed Mean ( 19 / 25 )9606.594594594631.8089373869495302.009289959367
Trimmed Mean ( 20 / 25 )9607.0285714285730.4971271746432315.014214827956
Trimmed Mean ( 21 / 25 )9607.9393939393929.0922949875055330.257183149896
Trimmed Mean ( 22 / 25 )9609.3870967741927.5050993285587349.367474808451
Trimmed Mean ( 23 / 25 )9611.8965517241425.6093879428397375.32707041566
Trimmed Mean ( 24 / 25 )9615.9259259259323.5210353769146408.82239118452
Trimmed Mean ( 25 / 25 )9620.9621.1884780010269454.065648298747
Median9655
Midrange9613.5
Midmean - Weighted Average at Xnp9596.26315789474
Midmean - Weighted Average at X(n+1)p9605.25641025641
Midmean - Empirical Distribution Function9605.25641025641
Midmean - Empirical Distribution Function - Averaging9605.25641025641
Midmean - Empirical Distribution Function - Interpolation9606.5945945946
Midmean - Closest Observation9596.26315789474
Midmean - True Basic - Statistics Graphics Toolkit9605.25641025641
Midmean - MS Excel (old versions)9605.25641025641
Number of observations75

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 9605.50666666667 & 58.0892428469724 & 165.357752931485 \tabularnewline
Geometric Mean & 9592.4687602401 &  &  \tabularnewline
Harmonic Mean & 9579.39088375951 &  &  \tabularnewline
Quadratic Mean & 9618.49577498131 &  &  \tabularnewline
Winsorized Mean ( 1 / 25 ) & 9604.93333333333 & 57.6930627501218 & 166.483332232402 \tabularnewline
Winsorized Mean ( 2 / 25 ) & 9605.92 & 57.2648022014498 & 167.745624375121 \tabularnewline
Winsorized Mean ( 3 / 25 ) & 9602.4 & 55.4455499477551 & 173.18612601098 \tabularnewline
Winsorized Mean ( 4 / 25 ) & 9603.30666666667 & 54.7592337791909 & 175.373284173235 \tabularnewline
Winsorized Mean ( 5 / 25 ) & 9609.10666666667 & 53.4873886738467 & 179.651818959806 \tabularnewline
Winsorized Mean ( 6 / 25 ) & 9615.34666666667 & 51.0786762628865 & 188.24580764739 \tabularnewline
Winsorized Mean ( 7 / 25 ) & 9616.84 & 48.9059072317666 & 196.639640165052 \tabularnewline
Winsorized Mean ( 8 / 25 ) & 9605.53333333333 & 46.2580982277877 & 207.650848204633 \tabularnewline
Winsorized Mean ( 9 / 25 ) & 9604.81333333333 & 45.5736160962029 & 210.753812316719 \tabularnewline
Winsorized Mean ( 10 / 25 ) & 9605.21333333333 & 44.7605975909247 & 214.590819834827 \tabularnewline
Winsorized Mean ( 11 / 25 ) & 9600.96 & 43.5011460551111 & 220.705909399183 \tabularnewline
Winsorized Mean ( 12 / 25 ) & 9600.32 & 43.2464430032394 & 221.990973900001 \tabularnewline
Winsorized Mean ( 13 / 25 ) & 9604.30666666667 & 42.1727890295927 & 227.737052437469 \tabularnewline
Winsorized Mean ( 14 / 25 ) & 9601.32 & 41.2387387194513 & 232.82283353325 \tabularnewline
Winsorized Mean ( 15 / 25 ) & 9596.32 & 39.8595650066897 & 240.753254542277 \tabularnewline
Winsorized Mean ( 16 / 25 ) & 9598.88 & 36.8826088073015 & 260.254909031808 \tabularnewline
Winsorized Mean ( 17 / 25 ) & 9602.73333333333 & 36.0347146604585 & 266.48562154068 \tabularnewline
Winsorized Mean ( 18 / 25 ) & 9593.37333333333 & 34.1294291826912 & 281.088010056688 \tabularnewline
Winsorized Mean ( 19 / 25 ) & 9602.74666666667 & 32.671866252855 & 293.914849930789 \tabularnewline
Winsorized Mean ( 20 / 25 ) & 9599.01333333333 & 31.082699880027 & 308.821735897576 \tabularnewline
Winsorized Mean ( 21 / 25 ) & 9595.37333333333 & 29.6357026789188 & 323.777486813531 \tabularnewline
Winsorized Mean ( 22 / 25 ) & 9588.04 & 28.2461920577937 & 339.445401361791 \tabularnewline
Winsorized Mean ( 23 / 25 ) & 9578.53333333333 & 26.0106030585888 & 368.254950173885 \tabularnewline
Winsorized Mean ( 24 / 25 ) & 9575.65333333333 & 23.6627848104357 & 404.671445480513 \tabularnewline
Winsorized Mean ( 25 / 25 ) & 9604.98666666667 & 17.4507749726809 & 550.404591297705 \tabularnewline
Trimmed Mean ( 1 / 25 ) & 9605.28767123288 & 55.9488564276353 & 171.679785513694 \tabularnewline
Trimmed Mean ( 2 / 25 ) & 9605.66197183099 & 53.8877100014464 & 178.253296931214 \tabularnewline
Trimmed Mean ( 3 / 25 ) & 9605.52173913043 & 51.7150885848444 & 185.73924945273 \tabularnewline
Trimmed Mean ( 4 / 25 ) & 9606.68656716418 & 49.9745308671686 & 192.231650812262 \tabularnewline
Trimmed Mean ( 5 / 25 ) & 9607.66153846154 & 48.1481052273321 & 199.54391752487 \tabularnewline
Trimmed Mean ( 6 / 25 ) & 9607.31746031746 & 46.3656509941688 & 207.207647349235 \tabularnewline
Trimmed Mean ( 7 / 25 ) & 9605.67213114754 & 44.9109423624806 & 213.882667026206 \tabularnewline
Trimmed Mean ( 8 / 25 ) & 9603.64406779661 & 43.7130658173422 & 219.697335069703 \tabularnewline
Trimmed Mean ( 9 / 25 ) & 9603.33333333333 & 42.8894242805979 & 223.909121990188 \tabularnewline
Trimmed Mean ( 10 / 25 ) & 9603.10909090909 & 42.0168851157863 & 228.553569938508 \tabularnewline
Trimmed Mean ( 11 / 25 ) & 9602.81132075472 & 41.100765203254 & 233.640694358519 \tabularnewline
Trimmed Mean ( 12 / 25 ) & 9603.05882352941 & 40.2154629490649 & 238.790209519463 \tabularnewline
Trimmed Mean ( 13 / 25 ) & 9603.40816326531 & 39.1377073251118 & 245.374826979288 \tabularnewline
Trimmed Mean ( 14 / 25 ) & 9603.29787234042 & 37.9914532831502 & 252.775217646113 \tabularnewline
Trimmed Mean ( 15 / 25 ) & 9603.53333333333 & 36.716324500806 & 261.560313127817 \tabularnewline
Trimmed Mean ( 16 / 25 ) & 9604.37209302326 & 35.3672556491853 & 271.561135200618 \tabularnewline
Trimmed Mean ( 17 / 25 ) & 9605 & 34.2888554745722 & 280.120169281324 \tabularnewline
Trimmed Mean ( 18 / 25 ) & 9605.25641025641 & 33.0384946613106 & 290.729238989952 \tabularnewline
Trimmed Mean ( 19 / 25 ) & 9606.5945945946 & 31.8089373869495 & 302.009289959367 \tabularnewline
Trimmed Mean ( 20 / 25 ) & 9607.02857142857 & 30.4971271746432 & 315.014214827956 \tabularnewline
Trimmed Mean ( 21 / 25 ) & 9607.93939393939 & 29.0922949875055 & 330.257183149896 \tabularnewline
Trimmed Mean ( 22 / 25 ) & 9609.38709677419 & 27.5050993285587 & 349.367474808451 \tabularnewline
Trimmed Mean ( 23 / 25 ) & 9611.89655172414 & 25.6093879428397 & 375.32707041566 \tabularnewline
Trimmed Mean ( 24 / 25 ) & 9615.92592592593 & 23.5210353769146 & 408.82239118452 \tabularnewline
Trimmed Mean ( 25 / 25 ) & 9620.96 & 21.1884780010269 & 454.065648298747 \tabularnewline
Median & 9655 &  &  \tabularnewline
Midrange & 9613.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 9596.26315789474 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 9605.25641025641 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 9605.25641025641 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 9605.25641025641 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 9606.5945945946 &  &  \tabularnewline
Midmean - Closest Observation & 9596.26315789474 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 9605.25641025641 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 9605.25641025641 &  &  \tabularnewline
Number of observations & 75 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148281&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]9605.50666666667[/C][C]58.0892428469724[/C][C]165.357752931485[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]9592.4687602401[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]9579.39088375951[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]9618.49577498131[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 25 )[/C][C]9604.93333333333[/C][C]57.6930627501218[/C][C]166.483332232402[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 25 )[/C][C]9605.92[/C][C]57.2648022014498[/C][C]167.745624375121[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 25 )[/C][C]9602.4[/C][C]55.4455499477551[/C][C]173.18612601098[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 25 )[/C][C]9603.30666666667[/C][C]54.7592337791909[/C][C]175.373284173235[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 25 )[/C][C]9609.10666666667[/C][C]53.4873886738467[/C][C]179.651818959806[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 25 )[/C][C]9615.34666666667[/C][C]51.0786762628865[/C][C]188.24580764739[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 25 )[/C][C]9616.84[/C][C]48.9059072317666[/C][C]196.639640165052[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 25 )[/C][C]9605.53333333333[/C][C]46.2580982277877[/C][C]207.650848204633[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 25 )[/C][C]9604.81333333333[/C][C]45.5736160962029[/C][C]210.753812316719[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 25 )[/C][C]9605.21333333333[/C][C]44.7605975909247[/C][C]214.590819834827[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 25 )[/C][C]9600.96[/C][C]43.5011460551111[/C][C]220.705909399183[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 25 )[/C][C]9600.32[/C][C]43.2464430032394[/C][C]221.990973900001[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 25 )[/C][C]9604.30666666667[/C][C]42.1727890295927[/C][C]227.737052437469[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 25 )[/C][C]9601.32[/C][C]41.2387387194513[/C][C]232.82283353325[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 25 )[/C][C]9596.32[/C][C]39.8595650066897[/C][C]240.753254542277[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 25 )[/C][C]9598.88[/C][C]36.8826088073015[/C][C]260.254909031808[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 25 )[/C][C]9602.73333333333[/C][C]36.0347146604585[/C][C]266.48562154068[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 25 )[/C][C]9593.37333333333[/C][C]34.1294291826912[/C][C]281.088010056688[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 25 )[/C][C]9602.74666666667[/C][C]32.671866252855[/C][C]293.914849930789[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 25 )[/C][C]9599.01333333333[/C][C]31.082699880027[/C][C]308.821735897576[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 25 )[/C][C]9595.37333333333[/C][C]29.6357026789188[/C][C]323.777486813531[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 25 )[/C][C]9588.04[/C][C]28.2461920577937[/C][C]339.445401361791[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 25 )[/C][C]9578.53333333333[/C][C]26.0106030585888[/C][C]368.254950173885[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 25 )[/C][C]9575.65333333333[/C][C]23.6627848104357[/C][C]404.671445480513[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 25 )[/C][C]9604.98666666667[/C][C]17.4507749726809[/C][C]550.404591297705[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 25 )[/C][C]9605.28767123288[/C][C]55.9488564276353[/C][C]171.679785513694[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 25 )[/C][C]9605.66197183099[/C][C]53.8877100014464[/C][C]178.253296931214[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 25 )[/C][C]9605.52173913043[/C][C]51.7150885848444[/C][C]185.73924945273[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 25 )[/C][C]9606.68656716418[/C][C]49.9745308671686[/C][C]192.231650812262[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 25 )[/C][C]9607.66153846154[/C][C]48.1481052273321[/C][C]199.54391752487[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 25 )[/C][C]9607.31746031746[/C][C]46.3656509941688[/C][C]207.207647349235[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 25 )[/C][C]9605.67213114754[/C][C]44.9109423624806[/C][C]213.882667026206[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 25 )[/C][C]9603.64406779661[/C][C]43.7130658173422[/C][C]219.697335069703[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 25 )[/C][C]9603.33333333333[/C][C]42.8894242805979[/C][C]223.909121990188[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 25 )[/C][C]9603.10909090909[/C][C]42.0168851157863[/C][C]228.553569938508[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 25 )[/C][C]9602.81132075472[/C][C]41.100765203254[/C][C]233.640694358519[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 25 )[/C][C]9603.05882352941[/C][C]40.2154629490649[/C][C]238.790209519463[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 25 )[/C][C]9603.40816326531[/C][C]39.1377073251118[/C][C]245.374826979288[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 25 )[/C][C]9603.29787234042[/C][C]37.9914532831502[/C][C]252.775217646113[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 25 )[/C][C]9603.53333333333[/C][C]36.716324500806[/C][C]261.560313127817[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 25 )[/C][C]9604.37209302326[/C][C]35.3672556491853[/C][C]271.561135200618[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 25 )[/C][C]9605[/C][C]34.2888554745722[/C][C]280.120169281324[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 25 )[/C][C]9605.25641025641[/C][C]33.0384946613106[/C][C]290.729238989952[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 25 )[/C][C]9606.5945945946[/C][C]31.8089373869495[/C][C]302.009289959367[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 25 )[/C][C]9607.02857142857[/C][C]30.4971271746432[/C][C]315.014214827956[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 25 )[/C][C]9607.93939393939[/C][C]29.0922949875055[/C][C]330.257183149896[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 25 )[/C][C]9609.38709677419[/C][C]27.5050993285587[/C][C]349.367474808451[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 25 )[/C][C]9611.89655172414[/C][C]25.6093879428397[/C][C]375.32707041566[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 25 )[/C][C]9615.92592592593[/C][C]23.5210353769146[/C][C]408.82239118452[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 25 )[/C][C]9620.96[/C][C]21.1884780010269[/C][C]454.065648298747[/C][/ROW]
[ROW][C]Median[/C][C]9655[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]9613.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]9596.26315789474[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]9605.25641025641[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]9605.25641025641[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]9605.25641025641[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]9606.5945945946[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]9596.26315789474[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]9605.25641025641[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]9605.25641025641[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]75[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148281&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148281&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean9605.5066666666758.0892428469724165.357752931485
Geometric Mean9592.4687602401
Harmonic Mean9579.39088375951
Quadratic Mean9618.49577498131
Winsorized Mean ( 1 / 25 )9604.9333333333357.6930627501218166.483332232402
Winsorized Mean ( 2 / 25 )9605.9257.2648022014498167.745624375121
Winsorized Mean ( 3 / 25 )9602.455.4455499477551173.18612601098
Winsorized Mean ( 4 / 25 )9603.3066666666754.7592337791909175.373284173235
Winsorized Mean ( 5 / 25 )9609.1066666666753.4873886738467179.651818959806
Winsorized Mean ( 6 / 25 )9615.3466666666751.0786762628865188.24580764739
Winsorized Mean ( 7 / 25 )9616.8448.9059072317666196.639640165052
Winsorized Mean ( 8 / 25 )9605.5333333333346.2580982277877207.650848204633
Winsorized Mean ( 9 / 25 )9604.8133333333345.5736160962029210.753812316719
Winsorized Mean ( 10 / 25 )9605.2133333333344.7605975909247214.590819834827
Winsorized Mean ( 11 / 25 )9600.9643.5011460551111220.705909399183
Winsorized Mean ( 12 / 25 )9600.3243.2464430032394221.990973900001
Winsorized Mean ( 13 / 25 )9604.3066666666742.1727890295927227.737052437469
Winsorized Mean ( 14 / 25 )9601.3241.2387387194513232.82283353325
Winsorized Mean ( 15 / 25 )9596.3239.8595650066897240.753254542277
Winsorized Mean ( 16 / 25 )9598.8836.8826088073015260.254909031808
Winsorized Mean ( 17 / 25 )9602.7333333333336.0347146604585266.48562154068
Winsorized Mean ( 18 / 25 )9593.3733333333334.1294291826912281.088010056688
Winsorized Mean ( 19 / 25 )9602.7466666666732.671866252855293.914849930789
Winsorized Mean ( 20 / 25 )9599.0133333333331.082699880027308.821735897576
Winsorized Mean ( 21 / 25 )9595.3733333333329.6357026789188323.777486813531
Winsorized Mean ( 22 / 25 )9588.0428.2461920577937339.445401361791
Winsorized Mean ( 23 / 25 )9578.5333333333326.0106030585888368.254950173885
Winsorized Mean ( 24 / 25 )9575.6533333333323.6627848104357404.671445480513
Winsorized Mean ( 25 / 25 )9604.9866666666717.4507749726809550.404591297705
Trimmed Mean ( 1 / 25 )9605.2876712328855.9488564276353171.679785513694
Trimmed Mean ( 2 / 25 )9605.6619718309953.8877100014464178.253296931214
Trimmed Mean ( 3 / 25 )9605.5217391304351.7150885848444185.73924945273
Trimmed Mean ( 4 / 25 )9606.6865671641849.9745308671686192.231650812262
Trimmed Mean ( 5 / 25 )9607.6615384615448.1481052273321199.54391752487
Trimmed Mean ( 6 / 25 )9607.3174603174646.3656509941688207.207647349235
Trimmed Mean ( 7 / 25 )9605.6721311475444.9109423624806213.882667026206
Trimmed Mean ( 8 / 25 )9603.6440677966143.7130658173422219.697335069703
Trimmed Mean ( 9 / 25 )9603.3333333333342.8894242805979223.909121990188
Trimmed Mean ( 10 / 25 )9603.1090909090942.0168851157863228.553569938508
Trimmed Mean ( 11 / 25 )9602.8113207547241.100765203254233.640694358519
Trimmed Mean ( 12 / 25 )9603.0588235294140.2154629490649238.790209519463
Trimmed Mean ( 13 / 25 )9603.4081632653139.1377073251118245.374826979288
Trimmed Mean ( 14 / 25 )9603.2978723404237.9914532831502252.775217646113
Trimmed Mean ( 15 / 25 )9603.5333333333336.716324500806261.560313127817
Trimmed Mean ( 16 / 25 )9604.3720930232635.3672556491853271.561135200618
Trimmed Mean ( 17 / 25 )960534.2888554745722280.120169281324
Trimmed Mean ( 18 / 25 )9605.2564102564133.0384946613106290.729238989952
Trimmed Mean ( 19 / 25 )9606.594594594631.8089373869495302.009289959367
Trimmed Mean ( 20 / 25 )9607.0285714285730.4971271746432315.014214827956
Trimmed Mean ( 21 / 25 )9607.9393939393929.0922949875055330.257183149896
Trimmed Mean ( 22 / 25 )9609.3870967741927.5050993285587349.367474808451
Trimmed Mean ( 23 / 25 )9611.8965517241425.6093879428397375.32707041566
Trimmed Mean ( 24 / 25 )9615.9259259259323.5210353769146408.82239118452
Trimmed Mean ( 25 / 25 )9620.9621.1884780010269454.065648298747
Median9655
Midrange9613.5
Midmean - Weighted Average at Xnp9596.26315789474
Midmean - Weighted Average at X(n+1)p9605.25641025641
Midmean - Empirical Distribution Function9605.25641025641
Midmean - Empirical Distribution Function - Averaging9605.25641025641
Midmean - Empirical Distribution Function - Interpolation9606.5945945946
Midmean - Closest Observation9596.26315789474
Midmean - True Basic - Statistics Graphics Toolkit9605.25641025641
Midmean - MS Excel (old versions)9605.25641025641
Number of observations75



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
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]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')