Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 15 Aug 2016 21:48:41 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/15/t14712941637scg1qktvhlj4kv.htm/, Retrieved Sun, 28 Apr 2024 04:49:13 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 28 Apr 2024 04:49:13 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
700
700
620
680
700
670
660
730
680
680
650
800
660
710
660
590
660
710
620
700
690
680
640
810
620
700
720
620
630
680
670
720
660
630
620
810
540
690
720
620
650
690
660
700
630
590
570
760
500
660
750
680
710
620
640
720
680
580
530
740
480
640
690
600
640
580
690
690
720
550
510
680
450
560
730
650
680
580
750
670
670
590
480
810
350
570
710
650
710
510
800
680
660
620
580
830
480
550
720
620
730
520
870
660
650
620
560
820





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean654.3518518518528.2506522898389979.3091053731246
Geometric Mean648.354029385139
Harmonic Mean641.763288743838
Quadratic Mean659.894071185054
Winsorized Mean ( 1 / 36 )654.9074074074077.8939134362088682.9635912148961
Winsorized Mean ( 2 / 36 )655.2777777777787.7299280975151584.771523035049
Winsorized Mean ( 3 / 36 )6557.6760518653490985.3303249495712
Winsorized Mean ( 4 / 36 )6557.6760518653490985.3303249495712
Winsorized Mean ( 5 / 36 )655.9259259259267.4871957587253387.6063545101692
Winsorized Mean ( 6 / 36 )655.9259259259267.2761827582851990.146983344947
Winsorized Mean ( 7 / 36 )655.9259259259267.2761827582851990.146983344947
Winsorized Mean ( 8 / 36 )653.7037037037046.638821120792298.4668349711007
Winsorized Mean ( 9 / 36 )653.7037037037046.36328463584199102.730545797313
Winsorized Mean ( 10 / 36 )654.629629629636.19911047494839105.600574836518
Winsorized Mean ( 11 / 36 )654.629629629635.88399735018586111.255935492383
Winsorized Mean ( 12 / 36 )653.5185185185185.73940068549924113.865289135441
Winsorized Mean ( 13 / 36 )654.7222222222225.54171432584903118.144347349033
Winsorized Mean ( 14 / 36 )654.7222222222225.54171432584903118.144347349033
Winsorized Mean ( 15 / 36 )654.7222222222225.15333981730716127.048136826409
Winsorized Mean ( 16 / 36 )654.7222222222225.15333981730716127.048136826409
Winsorized Mean ( 17 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 18 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 19 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 20 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 21 / 36 )656.2962962962964.4117291364685148.761693203506
Winsorized Mean ( 22 / 36 )656.2962962962964.4117291364685148.761693203506
Winsorized Mean ( 23 / 36 )656.2962962962964.4117291364685148.761693203506
Winsorized Mean ( 24 / 36 )658.5185185185184.10745005831657160.322951994311
Winsorized Mean ( 25 / 36 )663.1481481481483.53161106399135187.774966193098
Winsorized Mean ( 26 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 27 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 28 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 29 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 30 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 31 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 32 / 36 )657.7777777777782.92496840587687224.883720609141
Winsorized Mean ( 33 / 36 )657.7777777777782.92496840587687224.883720609141
Winsorized Mean ( 34 / 36 )657.7777777777782.92496840587687224.883720609141
Winsorized Mean ( 35 / 36 )661.0185185185182.54397058582661259.837327601701
Winsorized Mean ( 36 / 36 )661.0185185185182.54397058582661259.837327601701
Trimmed Mean ( 1 / 36 )655.1886792452837.627009192316885.9037484713272
Trimmed Mean ( 2 / 36 )655.4807692307697.3251077316507589.4841131685382
Trimmed Mean ( 3 / 36 )655.5882352941187.083512605556492.5512908355476
Trimmed Mean ( 4 / 36 )655.86.833045078916595.9747802664853
Trimmed Mean ( 5 / 36 )656.0204081632656.54772538196608100.190580681666
Trimmed Mean ( 6 / 36 )656.0416666666676.27840766259868104.491728145465
Trimmed Mean ( 7 / 36 )656.0638297872346.02598294801242108.872500212372
Trimmed Mean ( 8 / 36 )656.0869565217395.73535760394917114.393382562577
Trimmed Mean ( 9 / 36 )656.4444444444445.54250652273721118.438190690708
Trimmed Mean ( 10 / 36 )656.8181818181825.37648780056558122.164916239387
Trimmed Mean ( 11 / 36 )657.0930232558145.21721416473962125.947105583044
Trimmed Mean ( 12 / 36 )657.3809523809525.08989483962666129.154132471069
Trimmed Mean ( 13 / 36 )657.804878048784.96608306788706132.459499580755
Trimmed Mean ( 14 / 36 )658.1254.85581261368687135.533442568391
Trimmed Mean ( 15 / 36 )658.4615384615384.72724908221953139.290637537631
Trimmed Mean ( 16 / 36 )658.8157894736844.63763061579206142.058702827751
Trimmed Mean ( 17 / 36 )659.1891891891894.53199068091552145.452459107004
Trimmed Mean ( 18 / 36 )659.4444444444444.44444444444444148.375
Trimmed Mean ( 19 / 36 )659.7142857142864.34043737752505151.992582390501
Trimmed Mean ( 20 / 36 )6604.21648589377004156.528449668281
Trimmed Mean ( 21 / 36 )660.303030303034.06800981088186162.315987669629
Trimmed Mean ( 22 / 36 )660.6253.97084488830578166.368875789018
Trimmed Mean ( 23 / 36 )660.9677419354843.8528573353699171.552612620168
Trimmed Mean ( 24 / 36 )661.3333333333333.70879750157936178.314759177796
Trimmed Mean ( 25 / 36 )661.5517241379313.58798934250868184.379512029258
Trimmed Mean ( 26 / 36 )661.4285714285713.53487790186253187.114969679735
Trimmed Mean ( 27 / 36 )661.4814814814823.51106275416579188.399219209811
Trimmed Mean ( 28 / 36 )661.5384615384623.47783994638278190.215326678996
Trimmed Mean ( 29 / 36 )661.63.43285446762871192.725909658795
Trimmed Mean ( 30 / 36 )661.6666666666673.37299104029637196.166150091086
Trimmed Mean ( 31 / 36 )661.7391304347833.29403424780449200.890179231087
Trimmed Mean ( 32 / 36 )661.8181818181823.19011301755444207.459164667945
Trimmed Mean ( 33 / 36 )662.1428571428573.11483122373392212.577443072215
Trimmed Mean ( 34 / 36 )662.53.01172920769993219.973295841546
Trimmed Mean ( 35 / 36 )662.8947368421052.87006164992548230.968814505889
Trimmed Mean ( 36 / 36 )663.0555555555562.78372379480882238.190138257266
Median660
Midrange610
Midmean - Weighted Average at Xnp660.701754385965
Midmean - Weighted Average at X(n+1)p660.701754385965
Midmean - Empirical Distribution Function660.701754385965
Midmean - Empirical Distribution Function - Averaging660.701754385965
Midmean - Empirical Distribution Function - Interpolation660.701754385965
Midmean - Closest Observation660.701754385965
Midmean - True Basic - Statistics Graphics Toolkit660.701754385965
Midmean - MS Excel (old versions)660.701754385965
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 654.351851851852 & 8.25065228983899 & 79.3091053731246 \tabularnewline
Geometric Mean & 648.354029385139 &  &  \tabularnewline
Harmonic Mean & 641.763288743838 &  &  \tabularnewline
Quadratic Mean & 659.894071185054 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 654.907407407407 & 7.89391343620886 & 82.9635912148961 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 655.277777777778 & 7.72992809751515 & 84.771523035049 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 655 & 7.67605186534909 & 85.3303249495712 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 655 & 7.67605186534909 & 85.3303249495712 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 655.925925925926 & 7.48719575872533 & 87.6063545101692 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 655.925925925926 & 7.27618275828519 & 90.146983344947 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 655.925925925926 & 7.27618275828519 & 90.146983344947 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 653.703703703704 & 6.6388211207922 & 98.4668349711007 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 653.703703703704 & 6.36328463584199 & 102.730545797313 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 654.62962962963 & 6.19911047494839 & 105.600574836518 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 654.62962962963 & 5.88399735018586 & 111.255935492383 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 653.518518518518 & 5.73940068549924 & 113.865289135441 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 654.722222222222 & 5.54171432584903 & 118.144347349033 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 654.722222222222 & 5.54171432584903 & 118.144347349033 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 654.722222222222 & 5.15333981730716 & 127.048136826409 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 654.722222222222 & 5.15333981730716 & 127.048136826409 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 656.296296296296 & 4.91814723750573 & 133.44380812583 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 656.296296296296 & 4.91814723750573 & 133.44380812583 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 656.296296296296 & 4.91814723750573 & 133.44380812583 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 656.296296296296 & 4.91814723750573 & 133.44380812583 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 656.296296296296 & 4.4117291364685 & 148.761693203506 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 656.296296296296 & 4.4117291364685 & 148.761693203506 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 656.296296296296 & 4.4117291364685 & 148.761693203506 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 658.518518518518 & 4.10745005831657 & 160.322951994311 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 663.148148148148 & 3.53161106399135 & 187.774966193098 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 660.740740740741 & 3.24574355482236 & 203.571455840695 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 660.740740740741 & 3.24574355482236 & 203.571455840695 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 660.740740740741 & 3.24574355482236 & 203.571455840695 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 660.740740740741 & 3.24574355482236 & 203.571455840695 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 660.740740740741 & 3.24574355482236 & 203.571455840695 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 660.740740740741 & 3.24574355482236 & 203.571455840695 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 657.777777777778 & 2.92496840587687 & 224.883720609141 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 657.777777777778 & 2.92496840587687 & 224.883720609141 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 657.777777777778 & 2.92496840587687 & 224.883720609141 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 661.018518518518 & 2.54397058582661 & 259.837327601701 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 661.018518518518 & 2.54397058582661 & 259.837327601701 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 655.188679245283 & 7.6270091923168 & 85.9037484713272 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 655.480769230769 & 7.32510773165075 & 89.4841131685382 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 655.588235294118 & 7.0835126055564 & 92.5512908355476 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 655.8 & 6.8330450789165 & 95.9747802664853 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 656.020408163265 & 6.54772538196608 & 100.190580681666 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 656.041666666667 & 6.27840766259868 & 104.491728145465 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 656.063829787234 & 6.02598294801242 & 108.872500212372 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 656.086956521739 & 5.73535760394917 & 114.393382562577 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 656.444444444444 & 5.54250652273721 & 118.438190690708 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 656.818181818182 & 5.37648780056558 & 122.164916239387 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 657.093023255814 & 5.21721416473962 & 125.947105583044 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 657.380952380952 & 5.08989483962666 & 129.154132471069 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 657.80487804878 & 4.96608306788706 & 132.459499580755 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 658.125 & 4.85581261368687 & 135.533442568391 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 658.461538461538 & 4.72724908221953 & 139.290637537631 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 658.815789473684 & 4.63763061579206 & 142.058702827751 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 659.189189189189 & 4.53199068091552 & 145.452459107004 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 659.444444444444 & 4.44444444444444 & 148.375 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 659.714285714286 & 4.34043737752505 & 151.992582390501 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 660 & 4.21648589377004 & 156.528449668281 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 660.30303030303 & 4.06800981088186 & 162.315987669629 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 660.625 & 3.97084488830578 & 166.368875789018 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 660.967741935484 & 3.8528573353699 & 171.552612620168 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 661.333333333333 & 3.70879750157936 & 178.314759177796 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 661.551724137931 & 3.58798934250868 & 184.379512029258 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 661.428571428571 & 3.53487790186253 & 187.114969679735 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 661.481481481482 & 3.51106275416579 & 188.399219209811 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 661.538461538462 & 3.47783994638278 & 190.215326678996 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 661.6 & 3.43285446762871 & 192.725909658795 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 661.666666666667 & 3.37299104029637 & 196.166150091086 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 661.739130434783 & 3.29403424780449 & 200.890179231087 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 661.818181818182 & 3.19011301755444 & 207.459164667945 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 662.142857142857 & 3.11483122373392 & 212.577443072215 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 662.5 & 3.01172920769993 & 219.973295841546 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 662.894736842105 & 2.87006164992548 & 230.968814505889 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 663.055555555556 & 2.78372379480882 & 238.190138257266 \tabularnewline
Median & 660 &  &  \tabularnewline
Midrange & 610 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 660.701754385965 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 660.701754385965 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 660.701754385965 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 660.701754385965 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 660.701754385965 &  &  \tabularnewline
Midmean - Closest Observation & 660.701754385965 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 660.701754385965 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 660.701754385965 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]654.351851851852[/C][C]8.25065228983899[/C][C]79.3091053731246[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]648.354029385139[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]641.763288743838[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]659.894071185054[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]654.907407407407[/C][C]7.89391343620886[/C][C]82.9635912148961[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]655.277777777778[/C][C]7.72992809751515[/C][C]84.771523035049[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]655[/C][C]7.67605186534909[/C][C]85.3303249495712[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]655[/C][C]7.67605186534909[/C][C]85.3303249495712[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]655.925925925926[/C][C]7.48719575872533[/C][C]87.6063545101692[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]655.925925925926[/C][C]7.27618275828519[/C][C]90.146983344947[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]655.925925925926[/C][C]7.27618275828519[/C][C]90.146983344947[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]653.703703703704[/C][C]6.6388211207922[/C][C]98.4668349711007[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]653.703703703704[/C][C]6.36328463584199[/C][C]102.730545797313[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]654.62962962963[/C][C]6.19911047494839[/C][C]105.600574836518[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]654.62962962963[/C][C]5.88399735018586[/C][C]111.255935492383[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]653.518518518518[/C][C]5.73940068549924[/C][C]113.865289135441[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]654.722222222222[/C][C]5.54171432584903[/C][C]118.144347349033[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]654.722222222222[/C][C]5.54171432584903[/C][C]118.144347349033[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]654.722222222222[/C][C]5.15333981730716[/C][C]127.048136826409[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]654.722222222222[/C][C]5.15333981730716[/C][C]127.048136826409[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]656.296296296296[/C][C]4.91814723750573[/C][C]133.44380812583[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]656.296296296296[/C][C]4.91814723750573[/C][C]133.44380812583[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]656.296296296296[/C][C]4.91814723750573[/C][C]133.44380812583[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]656.296296296296[/C][C]4.91814723750573[/C][C]133.44380812583[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]656.296296296296[/C][C]4.4117291364685[/C][C]148.761693203506[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]656.296296296296[/C][C]4.4117291364685[/C][C]148.761693203506[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]656.296296296296[/C][C]4.4117291364685[/C][C]148.761693203506[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]658.518518518518[/C][C]4.10745005831657[/C][C]160.322951994311[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]663.148148148148[/C][C]3.53161106399135[/C][C]187.774966193098[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]660.740740740741[/C][C]3.24574355482236[/C][C]203.571455840695[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]660.740740740741[/C][C]3.24574355482236[/C][C]203.571455840695[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]660.740740740741[/C][C]3.24574355482236[/C][C]203.571455840695[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]660.740740740741[/C][C]3.24574355482236[/C][C]203.571455840695[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]660.740740740741[/C][C]3.24574355482236[/C][C]203.571455840695[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]660.740740740741[/C][C]3.24574355482236[/C][C]203.571455840695[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]657.777777777778[/C][C]2.92496840587687[/C][C]224.883720609141[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]657.777777777778[/C][C]2.92496840587687[/C][C]224.883720609141[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]657.777777777778[/C][C]2.92496840587687[/C][C]224.883720609141[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]661.018518518518[/C][C]2.54397058582661[/C][C]259.837327601701[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]661.018518518518[/C][C]2.54397058582661[/C][C]259.837327601701[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]655.188679245283[/C][C]7.6270091923168[/C][C]85.9037484713272[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]655.480769230769[/C][C]7.32510773165075[/C][C]89.4841131685382[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]655.588235294118[/C][C]7.0835126055564[/C][C]92.5512908355476[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]655.8[/C][C]6.8330450789165[/C][C]95.9747802664853[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]656.020408163265[/C][C]6.54772538196608[/C][C]100.190580681666[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]656.041666666667[/C][C]6.27840766259868[/C][C]104.491728145465[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]656.063829787234[/C][C]6.02598294801242[/C][C]108.872500212372[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]656.086956521739[/C][C]5.73535760394917[/C][C]114.393382562577[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]656.444444444444[/C][C]5.54250652273721[/C][C]118.438190690708[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]656.818181818182[/C][C]5.37648780056558[/C][C]122.164916239387[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]657.093023255814[/C][C]5.21721416473962[/C][C]125.947105583044[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]657.380952380952[/C][C]5.08989483962666[/C][C]129.154132471069[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]657.80487804878[/C][C]4.96608306788706[/C][C]132.459499580755[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]658.125[/C][C]4.85581261368687[/C][C]135.533442568391[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]658.461538461538[/C][C]4.72724908221953[/C][C]139.290637537631[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]658.815789473684[/C][C]4.63763061579206[/C][C]142.058702827751[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]659.189189189189[/C][C]4.53199068091552[/C][C]145.452459107004[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]659.444444444444[/C][C]4.44444444444444[/C][C]148.375[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]659.714285714286[/C][C]4.34043737752505[/C][C]151.992582390501[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]660[/C][C]4.21648589377004[/C][C]156.528449668281[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]660.30303030303[/C][C]4.06800981088186[/C][C]162.315987669629[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]660.625[/C][C]3.97084488830578[/C][C]166.368875789018[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]660.967741935484[/C][C]3.8528573353699[/C][C]171.552612620168[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]661.333333333333[/C][C]3.70879750157936[/C][C]178.314759177796[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]661.551724137931[/C][C]3.58798934250868[/C][C]184.379512029258[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]661.428571428571[/C][C]3.53487790186253[/C][C]187.114969679735[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]661.481481481482[/C][C]3.51106275416579[/C][C]188.399219209811[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]661.538461538462[/C][C]3.47783994638278[/C][C]190.215326678996[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]661.6[/C][C]3.43285446762871[/C][C]192.725909658795[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]661.666666666667[/C][C]3.37299104029637[/C][C]196.166150091086[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]661.739130434783[/C][C]3.29403424780449[/C][C]200.890179231087[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]661.818181818182[/C][C]3.19011301755444[/C][C]207.459164667945[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]662.142857142857[/C][C]3.11483122373392[/C][C]212.577443072215[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]662.5[/C][C]3.01172920769993[/C][C]219.973295841546[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]662.894736842105[/C][C]2.87006164992548[/C][C]230.968814505889[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]663.055555555556[/C][C]2.78372379480882[/C][C]238.190138257266[/C][/ROW]
[ROW][C]Median[/C][C]660[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]610[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]660.701754385965[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Mean654.3518518518528.2506522898389979.3091053731246
Geometric Mean648.354029385139
Harmonic Mean641.763288743838
Quadratic Mean659.894071185054
Winsorized Mean ( 1 / 36 )654.9074074074077.8939134362088682.9635912148961
Winsorized Mean ( 2 / 36 )655.2777777777787.7299280975151584.771523035049
Winsorized Mean ( 3 / 36 )6557.6760518653490985.3303249495712
Winsorized Mean ( 4 / 36 )6557.6760518653490985.3303249495712
Winsorized Mean ( 5 / 36 )655.9259259259267.4871957587253387.6063545101692
Winsorized Mean ( 6 / 36 )655.9259259259267.2761827582851990.146983344947
Winsorized Mean ( 7 / 36 )655.9259259259267.2761827582851990.146983344947
Winsorized Mean ( 8 / 36 )653.7037037037046.638821120792298.4668349711007
Winsorized Mean ( 9 / 36 )653.7037037037046.36328463584199102.730545797313
Winsorized Mean ( 10 / 36 )654.629629629636.19911047494839105.600574836518
Winsorized Mean ( 11 / 36 )654.629629629635.88399735018586111.255935492383
Winsorized Mean ( 12 / 36 )653.5185185185185.73940068549924113.865289135441
Winsorized Mean ( 13 / 36 )654.7222222222225.54171432584903118.144347349033
Winsorized Mean ( 14 / 36 )654.7222222222225.54171432584903118.144347349033
Winsorized Mean ( 15 / 36 )654.7222222222225.15333981730716127.048136826409
Winsorized Mean ( 16 / 36 )654.7222222222225.15333981730716127.048136826409
Winsorized Mean ( 17 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 18 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 19 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 20 / 36 )656.2962962962964.91814723750573133.44380812583
Winsorized Mean ( 21 / 36 )656.2962962962964.4117291364685148.761693203506
Winsorized Mean ( 22 / 36 )656.2962962962964.4117291364685148.761693203506
Winsorized Mean ( 23 / 36 )656.2962962962964.4117291364685148.761693203506
Winsorized Mean ( 24 / 36 )658.5185185185184.10745005831657160.322951994311
Winsorized Mean ( 25 / 36 )663.1481481481483.53161106399135187.774966193098
Winsorized Mean ( 26 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 27 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 28 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 29 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 30 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 31 / 36 )660.7407407407413.24574355482236203.571455840695
Winsorized Mean ( 32 / 36 )657.7777777777782.92496840587687224.883720609141
Winsorized Mean ( 33 / 36 )657.7777777777782.92496840587687224.883720609141
Winsorized Mean ( 34 / 36 )657.7777777777782.92496840587687224.883720609141
Winsorized Mean ( 35 / 36 )661.0185185185182.54397058582661259.837327601701
Winsorized Mean ( 36 / 36 )661.0185185185182.54397058582661259.837327601701
Trimmed Mean ( 1 / 36 )655.1886792452837.627009192316885.9037484713272
Trimmed Mean ( 2 / 36 )655.4807692307697.3251077316507589.4841131685382
Trimmed Mean ( 3 / 36 )655.5882352941187.083512605556492.5512908355476
Trimmed Mean ( 4 / 36 )655.86.833045078916595.9747802664853
Trimmed Mean ( 5 / 36 )656.0204081632656.54772538196608100.190580681666
Trimmed Mean ( 6 / 36 )656.0416666666676.27840766259868104.491728145465
Trimmed Mean ( 7 / 36 )656.0638297872346.02598294801242108.872500212372
Trimmed Mean ( 8 / 36 )656.0869565217395.73535760394917114.393382562577
Trimmed Mean ( 9 / 36 )656.4444444444445.54250652273721118.438190690708
Trimmed Mean ( 10 / 36 )656.8181818181825.37648780056558122.164916239387
Trimmed Mean ( 11 / 36 )657.0930232558145.21721416473962125.947105583044
Trimmed Mean ( 12 / 36 )657.3809523809525.08989483962666129.154132471069
Trimmed Mean ( 13 / 36 )657.804878048784.96608306788706132.459499580755
Trimmed Mean ( 14 / 36 )658.1254.85581261368687135.533442568391
Trimmed Mean ( 15 / 36 )658.4615384615384.72724908221953139.290637537631
Trimmed Mean ( 16 / 36 )658.8157894736844.63763061579206142.058702827751
Trimmed Mean ( 17 / 36 )659.1891891891894.53199068091552145.452459107004
Trimmed Mean ( 18 / 36 )659.4444444444444.44444444444444148.375
Trimmed Mean ( 19 / 36 )659.7142857142864.34043737752505151.992582390501
Trimmed Mean ( 20 / 36 )6604.21648589377004156.528449668281
Trimmed Mean ( 21 / 36 )660.303030303034.06800981088186162.315987669629
Trimmed Mean ( 22 / 36 )660.6253.97084488830578166.368875789018
Trimmed Mean ( 23 / 36 )660.9677419354843.8528573353699171.552612620168
Trimmed Mean ( 24 / 36 )661.3333333333333.70879750157936178.314759177796
Trimmed Mean ( 25 / 36 )661.5517241379313.58798934250868184.379512029258
Trimmed Mean ( 26 / 36 )661.4285714285713.53487790186253187.114969679735
Trimmed Mean ( 27 / 36 )661.4814814814823.51106275416579188.399219209811
Trimmed Mean ( 28 / 36 )661.5384615384623.47783994638278190.215326678996
Trimmed Mean ( 29 / 36 )661.63.43285446762871192.725909658795
Trimmed Mean ( 30 / 36 )661.6666666666673.37299104029637196.166150091086
Trimmed Mean ( 31 / 36 )661.7391304347833.29403424780449200.890179231087
Trimmed Mean ( 32 / 36 )661.8181818181823.19011301755444207.459164667945
Trimmed Mean ( 33 / 36 )662.1428571428573.11483122373392212.577443072215
Trimmed Mean ( 34 / 36 )662.53.01172920769993219.973295841546
Trimmed Mean ( 35 / 36 )662.8947368421052.87006164992548230.968814505889
Trimmed Mean ( 36 / 36 )663.0555555555562.78372379480882238.190138257266
Median660
Midrange610
Midmean - Weighted Average at Xnp660.701754385965
Midmean - Weighted Average at X(n+1)p660.701754385965
Midmean - Empirical Distribution Function660.701754385965
Midmean - Empirical Distribution Function - Averaging660.701754385965
Midmean - Empirical Distribution Function - Interpolation660.701754385965
Midmean - Closest Observation660.701754385965
Midmean - True Basic - Statistics Graphics Toolkit660.701754385965
Midmean - MS Excel (old versions)660.701754385965
Number of observations108



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')