*The author of this computation has been verified*

R Software Module: rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Tue, 20 Oct 2009 01:38:50 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/20/t1256024401co9qt4fgnm3y6m6.htm/, Retrieved Tue, 20 Oct 2009 09:40:02 +0200

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Oct/20/t1256024401co9qt4fgnm3y6m6.htm/}, year = {2009}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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3.88 3.98 3.29 2.88 3.22 3.62 3.82 3.54 2.53 2.22 2.85 2.78 2.28 2.26 2.71 2.77 2.77 2.64 2.56 2.07 2.32 2.16 2.23 2.4 2.84 2.77 2.93 2.91 2.69 2.38 2.58 3.19 2.82 2.72 2.53 2.7 2.42 2.5 2.31 2.41 2.56 2.76 2.71 2.44 2.46 2.12 1.99 1.86 1.88 1.82 1.74 1.71 1.38 1.27 1.19 1.28 1.19 1.22 1.47 1.46 1.96 1.88 2.03 2.04 1.9 1.8 1.92 1.92 1.97 2.46 2.36 2.53 2.31 1.98 1.46 1.26 1.58 1.74 1.89 1.85 1.62 1.3 1.42 1.15 0.42 0.74 1.02 1.51 1.86 1.59 1.03 0.44 0.82 0.86 0.58 0.59 0.95 0.98 1.23 1.17 0.84 0.74 0.65 0.91 1.19 1.3 1.53 1.94 1.79 1.95 2.26 2.04 2.16 2.75 2.79 2.88 3.36 2.97 3.1 2.49 2.2 2.25 2.09 2.79 3.14 2.93 2.65 2.67 2.26 2.35 2.13 2.18 2.9 2.63 2.67 1.81 1.33 0.88 1.28 1.26 1.26 1.29 1.1 1.37 1.21 1.74 1.76 1.48 1.04 1.62 1.49 1.79 1.8 1.58 1.86 1.74 1.59 1.26 1.13 1.92 2.61 2.26 2.41 2.26 2.03 2.86 2.55 2.27 2.26 2.57 3.07 2.76 2.51 etc...

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 2.10995535714286 0.0682153442484514 30.9308027451721 Geometric Mean NaN Harmonic Mean 1.86850864882622 Quadratic Mean 2.34299059125603 Winsorized Mean ( 1 / 74 ) 2.11205357142857 0.0674947585214853 31.2921124202 Winsorized Mean ( 2 / 74 ) 2.111875 0.0661933119156359 31.9046583239649 Winsorized Mean ( 3 / 74 ) 2.11642857142857 0.0649714036257521 32.5747706424754 Winsorized Mean ( 4 / 74 ) 2.12732142857143 0.0621640221363217 34.2211033884897 Winsorized Mean ( 5 / 74 ) 2.11683035714286 0.0598223750696012 35.3852610278345 Winsorized Mean ( 6 / 74 ) 2.11174107142857 0.0577171589673691 36.5877515319571 Winsorized Mean ( 7 / 74 ) 2.10455357142857 0.0564055443121937 37.3111118258212 Winsorized Mean ( 8 / 74 ) 2.09883928571429 0.0554062543688704 37.8809091071405 Winsorized Mean ( 9 / 74 ) 2.095625 0.0547091547910698 38.3048323082862 Winsorized Mean ( 10 / 74 ) 2.09428571428571 0.0541608139922872 38.6679143076386 Winsorized Mean ( 11 / 74 ) 2.08986607142857 0.0524229736001068 39.8654621801979 Winsorized Mean ( 12 / 74 ) 2.08879464285714 0.052281579165617 39.9527840626291 Winsorized Mean ( 13 / 74 ) 2.08879464285714 0.0511543897607972 40.8331455545564 Winsorized Mean ( 14 / 74 ) 2.08504464285714 0.0503916037872818 41.376826418519 Winsorized Mean ( 15 / 74 ) 2.0796875 0.0494446816956694 42.0608936831754 Winsorized Mean ( 16 / 74 ) 2.07611607142857 0.0487173158274328 42.6155677127743 Winsorized Mean ( 17 / 74 ) 2.07308035714286 0.0478857893109913 43.2921830666582 Winsorized Mean ( 18 / 74 ) 2.07388392857143 0.0472823499356121 43.8616932406192 Winsorized Mean ( 19 / 74 ) 2.07388392857143 0.0467459537978580 44.3649933326734 Winsorized Mean ( 20 / 74 ) 2.07566964285714 0.0461902390958485 44.9374084977122 Winsorized Mean ( 21 / 74 ) 2.07660714285714 0.0460944697410276 45.0511125200949 Winsorized Mean ( 22 / 74 ) 2.07758928571429 0.0459947917085778 45.1700987989652 Winsorized Mean ( 23 / 74 ) 2.08066964285714 0.0450651708741052 46.1702375137938 Winsorized Mean ( 24 / 74 ) 2.08174107142857 0.0447478121439122 46.5216280235901 Winsorized Mean ( 25 / 74 ) 2.08174107142857 0.0445269329899769 46.7524020101986 Winsorized Mean ( 26 / 74 ) 2.08174107142857 0.0440710447612687 47.236027253388 Winsorized Mean ( 27 / 74 ) 2.07209821428571 0.0426671060589722 48.564301769653 Winsorized Mean ( 28 / 74 ) 2.07084821428571 0.0420806217202301 49.2114453073815 Winsorized Mean ( 29 / 74 ) 2.06955357142857 0.0419611417273329 49.32071641131 Winsorized Mean ( 30 / 74 ) 2.06955357142857 0.0419611417273329 49.32071641131 Winsorized Mean ( 31 / 74 ) 2.06955357142857 0.0414492512109902 49.9298180537417 Winsorized Mean ( 32 / 74 ) 2.068125 0.0413198170880853 50.0516494444103 Winsorized Mean ( 33 / 74 ) 2.068125 0.0410503346487673 50.3802226631081 Winsorized Mean ( 34 / 74 ) 2.06660714285714 0.0409145385903442 50.510337255639 Winsorized Mean ( 35 / 74 ) 2.06816964285714 0.0407700220502944 50.7277047901967 Winsorized Mean ( 36 / 74 ) 2.07138392857143 0.0401861138509242 51.5447683310585 Winsorized Mean ( 37 / 74 ) 2.06973214285714 0.0400394144199217 51.6923679539964 Winsorized Mean ( 38 / 74 ) 2.06803571428571 0.0398897763941597 51.8437529920197 Winsorized Mean ( 39 / 74 ) 2.06629464285714 0.0397372416948364 51.9989449374803 Winsorized Mean ( 40 / 74 ) 2.06450892857143 0.0392649842617104 52.5788808372108 Winsorized Mean ( 41 / 74 ) 2.06084821428571 0.0386296691426456 53.3488445545764 Winsorized Mean ( 42 / 74 ) 2.06084821428571 0.0386296691426456 53.3488445545764 Winsorized Mean ( 43 / 74 ) 2.05892857142857 0.0384677453703669 53.5235052536934 Winsorized Mean ( 44 / 74 ) 2.05892857142857 0.038125034224878 54.0046353606955 Winsorized Mean ( 45 / 74 ) 2.05892857142857 0.038125034224878 54.0046353606955 Winsorized Mean ( 46 / 74 ) 2.06098214285714 0.0379398145873318 54.322409460201 Winsorized Mean ( 47 / 74 ) 2.05888392857143 0.0377645539456801 54.5189526541977 Winsorized Mean ( 48 / 74 ) 2.0653125 0.037189882042476 55.5342578833976 Winsorized Mean ( 49 / 74 ) 2.071875 0.0362385009319067 57.1733086833013 Winsorized Mean ( 50 / 74 ) 2.06517857142857 0.0356819580627072 57.8773891219546 Winsorized Mean ( 51 / 74 ) 2.06517857142857 0.0352964568110134 58.5095150622650 Winsorized Mean ( 52 / 74 ) 2.07446428571429 0.034497205237064 60.1342709201692 Winsorized Mean ( 53 / 74 ) 2.0815625 0.0335051750537909 62.1265967617885 Winsorized Mean ( 54 / 74 ) 2.07915178571429 0.0333062713642554 62.4252340640464 Winsorized Mean ( 55 / 74 ) 2.07669642857143 0.0327000554896582 63.5074282741879 Winsorized Mean ( 56 / 74 ) 2.07919642857143 0.0324926861125336 63.9896751339807 Winsorized Mean ( 57 / 74 ) 2.07665178571429 0.0318696536632789 65.160789246576 Winsorized Mean ( 58 / 74 ) 2.0740625 0.0316614341282042 65.5075348640766 Winsorized Mean ( 59 / 74 ) 2.07669642857143 0.0310168126683616 66.953895320448 Winsorized Mean ( 60 / 74 ) 2.07669642857143 0.0310168126683616 66.953895320448 Winsorized Mean ( 61 / 74 ) 2.08214285714286 0.0305731378281298 68.1036689412729 Winsorized Mean ( 62 / 74 ) 2.09044642857143 0.0290219863518504 72.0297502461662 Winsorized Mean ( 63 / 74 ) 2.08200892857143 0.0283509355077616 73.4370450668706 Winsorized Mean ( 64 / 74 ) 2.08200892857143 0.0278999496513126 74.6241106020589 Winsorized Mean ( 65 / 74 ) 2.08200892857143 0.0278999496513126 74.6241106020589 Winsorized Mean ( 66 / 74 ) 2.08200892857143 0.0274367378389409 75.883982301148 Winsorized Mean ( 67 / 74 ) 2.08799107142857 0.026968316932213 77.4238554329105 Winsorized Mean ( 68 / 74 ) 2.08495535714286 0.0267307677341549 77.9983342745082 Winsorized Mean ( 69 / 74 ) 2.081875 0.0260123398823156 80.0341303173328 Winsorized Mean ( 70 / 74 ) 2.085 0.0257696237956658 80.9092137523045 Winsorized Mean ( 71 / 74 ) 2.09133928571429 0.0252816447127698 82.721646849896 Winsorized Mean ( 72 / 74 ) 2.09455357142857 0.0240498308878454 87.0922369972732 Winsorized Mean ( 73 / 74 ) 2.0978125 0.0233084988185101 90.00204244531 Winsorized Mean ( 74 / 74 ) 2.10441964285714 0.0223200526081352 94.2838119516855 Trimmed Mean ( 1 / 74 ) 2.10990990990991 0.0644255396638944 32.7495884538528 Trimmed Mean ( 2 / 74 ) 2.10772727272727 0.061074824240483 34.5105745114888 Trimmed Mean ( 3 / 74 ) 2.10559633027523 0.0581824536531338 36.1895416585240 Trimmed Mean ( 4 / 74 ) 2.10185185185185 0.0555338315263573 37.8481331844405 Trimmed Mean ( 5 / 74 ) 2.09518691588785 0.0535523526240979 39.1240872384203 Trimmed Mean ( 6 / 74 ) 2.09061320754717 0.0520286869731783 40.1819328753177 Trimmed Mean ( 7 / 74 ) 2.08685714285714 0.0508565783682298 41.0341633239095 Trimmed Mean ( 8 / 74 ) 2.08413461538462 0.0498553379769398 41.8036402912084 Trimmed Mean ( 9 / 74 ) 2.08213592233010 0.0489579454365005 42.5290706904903 Trimmed Mean ( 10 / 74 ) 2.08049019607843 0.048109621340404 43.2447842679479 Trimmed Mean ( 11 / 74 ) 2.07896039603960 0.0472839681992404 43.9675533846798 Trimmed Mean ( 12 / 74 ) 2.07785 0.0466320396628281 44.5584198122974 Trimmed Mean ( 13 / 74 ) 2.07681818181818 0.0459559498557384 45.1914972563417 Trimmed Mean ( 14 / 74 ) 2.07576530612245 0.0453655382049161 45.7564351324615 Trimmed Mean ( 15 / 74 ) 2.075 0.0448199842919896 46.2963125217082 Trimmed Mean ( 16 / 74 ) 2.07463541666667 0.0443365303713534 46.7929131867099 Trimmed Mean ( 17 / 74 ) 2.07452631578947 0.0438926398897562 47.2636487802966 Trimmed Mean ( 18 / 74 ) 2.07462765957447 0.0434969700283049 47.6959121112216 Trimmed Mean ( 19 / 74 ) 2.07467741935484 0.0431288057661101 48.1042167178459 Trimmed Mean ( 20 / 74 ) 2.07472826086957 0.0427819100488123 48.4954565727054 Trimmed Mean ( 21 / 74 ) 2.07467032967033 0.0424574235658678 48.8647250686731 Trimmed Mean ( 22 / 74 ) 2.07455555555556 0.0421180630684391 49.2557208099656 Trimmed Mean ( 23 / 74 ) 2.07438202247191 0.0417627909265622 49.6705793949357 Trimmed Mean ( 24 / 74 ) 2.07403409090909 0.0414543387494135 50.0317735966404 Trimmed Mean ( 25 / 74 ) 2.07362068965517 0.0411473459450015 50.3950046359448 Trimmed Mean ( 26 / 74 ) 2.07319767441860 0.0408341311169744 50.7711959997305 Trimmed Mean ( 27 / 74 ) 2.07276470588235 0.0405309353554524 51.1403126452525 Trimmed Mean ( 28 / 74 ) 2.07279761904762 0.040304827028563 51.4280241812893 Trimmed Mean ( 29 / 74 ) 2.07289156626506 0.0401007366274576 51.6921069436345 Trimmed Mean ( 30 / 74 ) 2.07304878048781 0.0398874649633929 51.9724375161561 Trimmed Mean ( 31 / 74 ) 2.07320987654321 0.0396561068658427 52.2797127705176 Trimmed Mean ( 32 / 74 ) 2.073375 0.0394395572403452 52.5709502103389 Trimmed Mean ( 33 / 74 ) 2.07360759493671 0.0392127251831577 52.8809865994048 Trimmed Mean ( 34 / 74 ) 2.07384615384615 0.0389839378111809 53.1974518297985 Trimmed Mean ( 35 / 74 ) 2.07415584415584 0.0387438247951167 53.5351337954964 Trimmed Mean ( 36 / 74 ) 2.07440789473684 0.0384920462232440 53.8918581440387 Trimmed Mean ( 37 / 74 ) 2.07453333333333 0.0382563573014296 54.2271528098628 Trimmed Mean ( 38 / 74 ) 2.07472972972973 0.0380086023330783 54.5857938039496 Trimmed Mean ( 39 / 74 ) 2.075 0.0377477956887231 54.9700972504705 Trimmed Mean ( 40 / 74 ) 2.07534722222222 0.0374728486522633 55.3826916517828 Trimmed Mean ( 41 / 74 ) 2.07577464788732 0.0372035042520879 55.7951378402971 Trimmed Mean ( 42 / 74 ) 2.07635714285714 0.0369501776603219 56.1934278623724 Trimmed Mean ( 43 / 74 ) 2.07695652173913 0.0366720434055837 56.6359637713259 Trimmed Mean ( 44 / 74 ) 2.07764705882353 0.0363773845947961 57.1137007777284 Trimmed Mean ( 45 / 74 ) 2.07835820895522 0.0360770124200749 57.6089334880382 Trimmed Mean ( 46 / 74 ) 2.07909090909091 0.0357467922279106 58.161607783861 Trimmed Mean ( 47 / 74 ) 2.07976923076923 0.0353969677177157 58.7555761090895 Trimmed Mean ( 48 / 74 ) 2.080546875 0.0350241249451166 59.4032507096253 Trimmed Mean ( 49 / 74 ) 2.08111111111111 0.0346557166263426 60.0510193902385 Trimmed Mean ( 50 / 74 ) 2.08145161290323 0.0343182628084098 60.6514270411484 Trimmed Mean ( 51 / 74 ) 2.08204918032787 0.0339841724049513 61.2652606489404 Trimmed Mean ( 52 / 74 ) 2.08266666666667 0.0336418634539963 61.9069948225258 Trimmed Mean ( 53 / 74 ) 2.08296610169492 0.0333214471032823 62.5112737522654 Trimmed Mean ( 54 / 74 ) 2.08301724137931 0.0330374418067323 63.0501978199424 Trimmed Mean ( 55 / 74 ) 2.08315789473684 0.0327344862320389 63.6380201592396 Trimmed Mean ( 56 / 74 ) 2.08339285714286 0.0324405588418297 64.2218547251559 Trimmed Mean ( 57 / 74 ) 2.08354545454545 0.0321266224900957 64.8541705617448 Trimmed Mean ( 58 / 74 ) 2.08379629629630 0.031821835927929 65.483220421843 Trimmed Mean ( 59 / 74 ) 2.08415094339623 0.031494624514461 66.1748147668588 Trimmed Mean ( 60 / 74 ) 2.08442307692308 0.0311773657519835 66.856933761008 Trimmed Mean ( 61 / 74 ) 2.08442307692308 0.0308186704153934 67.6350747396923 Trimmed Mean ( 62 / 74 ) 2.0848 0.030450648929079 68.4648791838755 Trimmed Mean ( 63 / 74 ) 2.08459183673469 0.0301637191859754 69.1092442507529 Trimmed Mean ( 64 / 74 ) 2.0846875 0.0298919667100353 69.740727340638 Trimmed Mean ( 65 / 74 ) 2.08478723404255 0.0296180709040438 70.3890284008305 Trimmed Mean ( 66 / 74 ) 2.08489130434783 0.0293024879396911 71.1506582184708 Trimmed Mean ( 67 / 74 ) 2.085 0.0289811381253601 71.9433443566356 Trimmed Mean ( 68 / 74 ) 2.08488636363636 0.0286536055265366 72.7617458719291 Trimmed Mean ( 69 / 74 ) 2.08488372093023 0.0282972033083927 73.6780839508572 Trimmed Mean ( 70 / 74 ) 2.085 0.0279545057009511 74.5854719201513 Trimmed Mean ( 71 / 74 ) 2.085 0.0275799186379271 75.5984826268767 Trimmed Mean ( 72 / 74 ) 2.08475 0.0271936183643669 76.6632072299633 Trimmed Mean ( 73 / 74 ) 2.08435897435897 0.0268718730377899 77.5665682636913 Trimmed Mean ( 74 / 74 ) 2.08381578947368 0.0265699785110829 78.4274548285569 Median 2.055 Midrange 2.115 Midmean - Weighted Average at Xnp 2.08315789473684 Midmean - Weighted Average at X(n+1)p 2.08858407079646 Midmean - Empirical Distribution Function 2.08315789473684 Midmean - Empirical Distribution Function - Averaging 2.08858407079646 Midmean - Empirical Distribution Function - Interpolation 2.08858407079646 Midmean - Closest Observation 2.08315789473684 Midmean - True Basic - Statistics Graphics Toolkit 2.08858407079646 Midmean - MS Excel (old versions) 2.08315789473684 Number of observations 224

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/20/t1256024401co9qt4fgnm3y6m6/1iy101256024324.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t1256024401co9qt4fgnm3y6m6/1iy101256024324.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t1256024401co9qt4fgnm3y6m6/2ox661256024324.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t1256024401co9qt4fgnm3y6m6/2ox661256024324.ps (open in new window)

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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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')

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