mean of the error

*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: Thu, 23 Oct 2008 08:45:08 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/23/t1224773302bczag8lj95cny6u.htm/, Retrieved Thu, 23 Oct 2008 14:48:25 +0000

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/2008/Oct/23/t1224773302bczag8lj95cny6u.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

distribution Q6

Dataseries X:

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0.025749385 0.02374787 0.021734644 0.019846432 0.018140909 0.016621471 0.015270188 0.014070406 0.013016966 0.012114996 0.011375257 0.010806475 0.01041044 0.010179372 0.01009575 0.010135252 0.010270244 0.010473029 0.010718977 0.010986893 0.011260233 0.011526183 0.011775741 0.012002907 0.012204698 0.012380026 0.012529858 0.012656553 0.012763782 0.012855895 0.012937608 0.013013837 0.013089429 0.013168544 0.013254564 0.013349985 0.013456339 0.013573675 0.013700963 0.013836316 0.013976347 0.014117471 0.014255109 0.014384556 0.014500777 0.014598919 0.01467451 0.014723505 0.014742413 0.014728713 0.014680949 0.01459833 0.014481446 0.014331633 0.014151607 0.01394507 0.013716369 0.013470887 0.013214505 0.012953678 0.012695236 0.012445944 0.012212696 0.012001897 0.011819503 0.011670936 0.011560378 0.011491247 0.011465717 0.01148472 0.011547978 0.011654156 0.011800748 0.011984507 0.012201422 0.012446842 0.012715908 0.013003495 0.01330457 0.013613992 0.013926996 0.014239117 0.014546304 0.014844989 0.015132148 0.015405269 0.015662525 0.015902616 0.01612482 0.016328967 0.016515394 0.016684831 0.016838382 0.016977485 0.017103717 0.017218825 0.017324554 0.017422675 0.017514828 0.017602504 0.017687027 0.017769428 0.017850499 0.01793075 0.018010355 0.018089198 0.018166812 0.018242448 0.018314982 0.018383012 0.018444798 0.018498321 0.018541308 0.018571245 0.018585367 0.018580929 0.018555004 0.018504726 0.018427342 0.018320256 0.018181244 0.018008336 0.017800172 0.017555895 0.017275153 0.01695839 0.016606633 0.016221732 0.015806088 0.01536282 0.014895774 0.014409298 0.013908231 0.013398015 0.012884423 0.012373828 0.011872755 0.011388287 0.01092791 0.010499544 0.010111815 0.009773851 0.009495565 0.009287581 0.009160983 0.009127086 0.009196839 0.009380001 0.009684446 0.010115235 0.010674166 0.01135928 0.012164855 0.013081277 0.014095168 0.015189115 0.016342299 0.017530232 0.018725319 0.019897617 0.021015315 0.022046049 0.022957976 0.023721479 0.024310322 0.024703403 0.024886415 0.024852666 0.024604672 0.024154591 0.023524617 0.022746938 0.02186292 0.020922174 0.019980527 0.019097146 0.018329924 0.017729391 0.017330373 0.017144205 0.017153293 0.01731132 0.017549121 0.017785239 0.017938518 0.017941391 0.017753954 0.017378803 0.016876717 0.016383702 0.016120959 0.016377277 0.017432385 0.019434723 0.022319625 0.025817482 0.029505023

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 4 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.0155075605279188 0.000280893817086035 55.2079098386454 Geometric Mean 0.0150358592477163 Harmonic Mean 0.0145889615570400 Quadratic Mean 0.0159984091545562 Winsorized Mean ( 1 / 65 ) 0.0154890141116751 0.000276707415216876 55.9761439697424 Winsorized Mean ( 2 / 65 ) 0.0154886867918782 0.000276533781605351 56.0101073437114 Winsorized Mean ( 3 / 65 ) 0.0154769269746193 0.000273978215946016 56.4896260864361 Winsorized Mean ( 4 / 65 ) 0.0154781182639594 0.000273643466519270 56.5630835657807 Winsorized Mean ( 5 / 65 ) 0.0154772629593909 0.000272654452007430 56.7651210000015 Winsorized Mean ( 6 / 65 ) 0.0154800086446701 0.000271501826853688 57.0162227785386 Winsorized Mean ( 7 / 65 ) 0.0154727263350254 0.000269385258737017 57.4371678968906 Winsorized Mean ( 8 / 65 ) 0.0154794742741117 0.000266953575907653 57.9856412167577 Winsorized Mean ( 9 / 65 ) 0.0154616270456853 0.000263848538073207 58.6003892937823 Winsorized Mean ( 10 / 65 ) 0.0154604610050761 0.000263616158153158 58.6476227913685 Winsorized Mean ( 11 / 65 ) 0.0154505864111675 0.000261756691778517 59.0265192694323 Winsorized Mean ( 12 / 65 ) 0.0154187577208122 0.000256168499861511 60.1899051957904 Winsorized Mean ( 13 / 65 ) 0.0154108279847716 0.000253471477006403 60.7990617594511 Winsorized Mean ( 14 / 65 ) 0.0153904237309645 0.000248038562084192 62.0485121411907 Winsorized Mean ( 15 / 65 ) 0.0153743587309645 0.000244616803803336 62.8507874026715 Winsorized Mean ( 16 / 65 ) 0.0153616388121827 0.000242343720984653 63.3878144222913 Winsorized Mean ( 17 / 65 ) 0.0153656382131980 0.000239309641120462 64.2081871054385 Winsorized Mean ( 18 / 65 ) 0.0153040071269036 0.000230270228544246 66.4610758570682 Winsorized Mean ( 19 / 65 ) 0.0153034628781726 0.000228285052356319 67.036640026199 Winsorized Mean ( 20 / 65 ) 0.0152201926243655 0.000215635934677596 70.5828212126226 Winsorized Mean ( 21 / 65 ) 0.0152176420304569 0.000214008778620194 71.1075598326922 Winsorized Mean ( 22 / 65 ) 0.0152424512182741 0.000210356613853483 72.4600521897103 Winsorized Mean ( 23 / 65 ) 0.0152059475329949 0.000204014308717487 74.5337306416664 Winsorized Mean ( 24 / 65 ) 0.0151667678375635 0.000199584499790516 75.9917120491947 Winsorized Mean ( 25 / 65 ) 0.0151212352233503 0.000194824543563113 77.614631846689 Winsorized Mean ( 26 / 65 ) 0.0151129835888325 0.000192106557568672 78.669795451569 Winsorized Mean ( 27 / 65 ) 0.0151149798071066 0.000191798573561890 78.806528778637 Winsorized Mean ( 28 / 65 ) 0.0151145310964467 0.000191582218690453 78.8931833014622 Winsorized Mean ( 29 / 65 ) 0.0151172831522843 0.000190867360512702 79.2030817195601 Winsorized Mean ( 30 / 65 ) 0.0151185165025381 0.000190357744059690 79.4215994585299 Winsorized Mean ( 31 / 65 ) 0.0151147112131980 0.000189644525189955 79.7002243964516 Winsorized Mean ( 32 / 65 ) 0.0151289037817259 0.000188103350832995 80.4286777174847 Winsorized Mean ( 33 / 65 ) 0.0151227488629442 0.000187022573082731 80.860553962406 Winsorized Mean ( 34 / 65 ) 0.0151378243248731 0.000185059410331862 81.7998084924556 Winsorized Mean ( 35 / 65 ) 0.0151343913045685 0.000183936092102721 82.2807048445748 Winsorized Mean ( 36 / 65 ) 0.0151281172538071 0.000182748632102356 82.7810149918603 Winsorized Mean ( 37 / 65 ) 0.0151363030812183 0.000181665992739251 83.3194086190018 Winsorized Mean ( 38 / 65 ) 0.0151568419847716 0.000179615677898408 84.3848497086342 Winsorized Mean ( 39 / 65 ) 0.0151459251522843 0.000178024188990571 85.0779056383537 Winsorized Mean ( 40 / 65 ) 0.0151337030203046 0.000176908132925496 85.5455471155647 Winsorized Mean ( 41 / 65 ) 0.0151540275736041 0.000174554504351102 86.8154484465377 Winsorized Mean ( 42 / 65 ) 0.0151591349441624 0.00017312759281287 87.560478938488 Winsorized Mean ( 43 / 65 ) 0.0151558294010152 0.000171435930957758 88.4052095517224 Winsorized Mean ( 44 / 65 ) 0.0151389514923858 0.000169843357097708 89.1347872008715 Winsorized Mean ( 45 / 65 ) 0.0151403172538071 0.000169642628091987 89.2483064197605 Winsorized Mean ( 46 / 65 ) 0.0151623101573604 0.000165018063775758 91.8827297474798 Winsorized Mean ( 47 / 65 ) 0.0151631034314721 0.000164831739350188 91.9914058496816 Winsorized Mean ( 48 / 65 ) 0.0151772719593909 0.000163291864583457 92.94567122561 Winsorized Mean ( 49 / 65 ) 0.0151575344111675 0.000161565337135870 93.816747328795 Winsorized Mean ( 50 / 65 ) 0.0151658311116751 0.000158686511446805 95.5710159193903 Winsorized Mean ( 51 / 65 ) 0.0151947644213198 0.000155603635867694 97.6504458690124 Winsorized Mean ( 52 / 65 ) 0.0152008017005076 0.000154401681277262 98.4497161867768 Winsorized Mean ( 53 / 65 ) 0.0152022001472081 0.000153588664497071 98.9799618154636 Winsorized Mean ( 54 / 65 ) 0.015208589964467 0.000151937725099640 100.097523208889 Winsorized Mean ( 55 / 65 ) 0.0152224792791878 0.000148838635962896 102.275052312241 Winsorized Mean ( 56 / 65 ) 0.0152065619187817 0.000146161268421001 104.039613798239 Winsorized Mean ( 57 / 65 ) 0.0152084646192893 0.000143791991778744 105.767118398992 Winsorized Mean ( 58 / 65 ) 0.0152112015126904 0.000143245071504514 106.190051447676 Winsorized Mean ( 59 / 65 ) 0.0152204642131980 0.000141578247331127 107.505669127263 Winsorized Mean ( 60 / 65 ) 0.0152189224873096 0.000140936477383471 107.984269011498 Winsorized Mean ( 61 / 65 ) 0.0151943633299492 0.000138747631394654 109.510794362538 Winsorized Mean ( 62 / 65 ) 0.0152115474010152 0.000136882078232701 111.128846065264 Winsorized Mean ( 63 / 65 ) 0.0152001242538071 0.000135521444941089 112.160287697749 Winsorized Mean ( 64 / 65 ) 0.0152100929847716 0.000132198591954180 115.054878875287 Winsorized Mean ( 65 / 65 ) 0.0152233378071066 0.000130850032734131 116.341872363443 Trimmed Mean ( 1 / 65 ) 0.0155075605279188 0.00027252364531572 56.9035413787791 Trimmed Mean ( 2 / 65 ) 0.0154684990512821 0.000268056407385202 57.7061343251292 Trimmed Mean ( 3 / 65 ) 0.0154263488272251 0.000263377054088724 58.5713470013544 Trimmed Mean ( 4 / 65 ) 0.0154263488272251 0.00025935767726317 59.4790522108665 Trimmed Mean ( 5 / 65 ) 0.015390513171123 0.000255158630163372 60.3174314004932 Trimmed Mean ( 6 / 65 ) 0.0153720378108108 0.000250907334600876 61.2657969336109 Trimmed Mean ( 7 / 65 ) 0.0153526659945355 0.000246595259607278 62.2585609268638 Trimmed Mean ( 8 / 65 ) 0.0153526659945355 0.000242372031960866 63.3433893767677 Trimmed Mean ( 9 / 65 ) 0.0153139852681564 0.00023824918362399 64.2771783525827 Trimmed Mean ( 10 / 65 ) 0.0152957269943503 0.000234312662761601 65.2791309444199 Trimmed Mean ( 11 / 65 ) 0.0152771826514286 0.000230115936718340 66.3890683509145 Trimmed Mean ( 12 / 65 ) 0.0152592317630058 0.000225858429073731 67.5610462075092 Trimmed Mean ( 13 / 65 ) 0.0152439166491228 0.000222008703396829 68.6635992908579 Trimmed Mean ( 14 / 65 ) 0.0152289500887574 0.000218195906983321 69.7948476637625 Trimmed Mean ( 15 / 65 ) 0.0152153443113772 0.000214727315633748 70.8589136248016 Trimmed Mean ( 16 / 65 ) 0.0152153443113772 0.000211375189195343 71.9826407692338 Trimmed Mean ( 17 / 65 ) 0.0151906807239264 0.000208008696885886 73.0290653773 Trimmed Mean ( 18 / 65 ) 0.0151780878757764 0.000204688525344493 74.1521189340316 Trimmed Mean ( 19 / 65 ) 0.0151694204779874 0.000202022651101148 75.0877210812983 Trimmed Mean ( 20 / 65 ) 0.0151605681974522 0.000199334003007453 76.0561066788258 Trimmed Mean ( 21 / 65 ) 0.0151567791612903 0.000197599396756917 76.7045821497923 Trimmed Mean ( 22 / 65 ) 0.0151530474509804 0.000195862668896433 77.3656743082213 Trimmed Mean ( 23 / 65 ) 0.0151477456622517 0.000194285339939654 77.966488191835 Trimmed Mean ( 24 / 65 ) 0.0151443999463087 0.000193096028628044 78.42937037033 Trimmed Mean ( 25 / 65 ) 0.0151431509455782 0.000192148766051937 78.8095144024247 Trimmed Mean ( 26 / 65 ) 0.0151443419517241 0.00019146923212154 79.0954336836265 Trimmed Mean ( 27 / 65 ) 0.0151460034895105 0.000190911546175488 79.3351884311289 Trimmed Mean ( 28 / 65 ) 0.0151476088652482 0.000190303594789828 79.5970716264046 Trimmed Mean ( 29 / 65 ) 0.0151492831510791 0.000189633663450287 79.8870985005812 Trimmed Mean ( 30 / 65 ) 0.0151508698613139 0.000188932214931605 80.1920935865736 Trimmed Mean ( 31 / 65 ) 0.0151524435925926 0.000188180329334294 80.5208687124516 Trimmed Mean ( 32 / 65 ) 0.0151524435925926 0.000187386930239445 80.8617952875937 Trimmed Mean ( 33 / 65 ) 0.0151554374351145 0.000186607582818528 81.2155497981711 Trimmed Mean ( 34 / 65 ) 0.0151569501550388 0.000185806851898505 81.5736879462231 Trimmed Mean ( 35 / 65 ) 0.0151578227322835 0.000185045052711877 81.9142285089074 Trimmed Mean ( 36 / 65 ) 0.015158877816 0.000184261961515242 82.268080136258 Trimmed Mean ( 37 / 65 ) 0.0151602463414634 0.000183458289912221 82.6359296639967 Trimmed Mean ( 38 / 65 ) 0.0151612999090909 0.000182623728588156 83.0193317500481 Trimmed Mean ( 39 / 65 ) 0.0151614941176471 0.000181823397684001 83.385825536034 Trimmed Mean ( 40 / 65 ) 0.0151621662820513 0.000181023874567985 83.7578265200428 Trimmed Mean ( 41 / 65 ) 0.0151633852521739 0.000180188408188606 84.1529452677233 Trimmed Mean ( 42 / 65 ) 0.0151637831504425 0.000179403336114982 84.5234178963307 Trimmed Mean ( 43 / 65 ) 0.0151639795675676 0.000178602170212943 84.9036691406822 Trimmed Mean ( 44 / 65 ) 0.0151643221284404 0.000177800845974226 85.2882450887695 Trimmed Mean ( 45 / 65 ) 0.0151653837289720 0.000176989284331480 85.6853214942042 Trimmed Mean ( 46 / 65 ) 0.0151664288285714 0.00017606027263618 86.1433905643899 Trimmed Mean ( 47 / 65 ) 0.0151666000776699 0.000175338078858649 86.4991801917518 Trimmed Mean ( 48 / 65 ) 0.0151667451881188 0.000174498453677931 86.91621540734 Trimmed Mean ( 49 / 65 ) 0.0151663087878788 0.000173632885940389 87.3469832960421 Trimmed Mean ( 50 / 65 ) 0.0151666724639175 0.000172751629403964 87.794670975008 Trimmed Mean ( 51 / 65 ) 0.0151667073578947 0.000171943333545544 88.2075916823922 Trimmed Mean ( 52 / 65 ) 0.0151655420107527 0.000171227918523930 88.5693299403931 Trimmed Mean ( 53 / 65 ) 0.0151655420107527 0.000170458884571164 88.9689149902967 Trimmed Mean ( 54 / 65 ) 0.0151624818089888 0.000169595638252256 89.403725032339 Trimmed Mean ( 55 / 65 ) 0.0151605483678161 0.000168696357318173 89.868854365493 Trimmed Mean ( 56 / 65 ) 0.0151579386588235 0.000167879802553094 90.2904246270464 Trimmed Mean ( 57 / 65 ) 0.0151579386588235 0.000167120247279487 90.7007912301247 Trimmed Mean ( 58 / 65 ) 0.0151536340246914 0.000166390867983418 91.0725102185386 Trimmed Mean ( 59 / 65 ) 0.0151511589493671 0.000165523237445073 91.534936020055 Trimmed Mean ( 60 / 65 ) 0.0151481536363636 0.000164601973867085 92.0289913934791 Trimmed Mean ( 61 / 65 ) 0.0151450555333333 0.000163517528078919 92.6203796697796 Trimmed Mean ( 62 / 65 ) 0.0151428741643836 0.000162408393291136 93.23948016183 Trimmed Mean ( 63 / 65 ) 0.0151398008732394 0.000161224231298034 93.9052445860481 Trimmed Mean ( 64 / 65 ) 0.0151398008732394 0.000159902460672348 94.6814752542304 Trimmed Mean ( 65 / 65 ) 0.0151337121343284 0.000158636751638199 95.3985251087567 Median 0.014728713 Midrange 0.0193160545 Midmean - Weighted Average at Xnp 0.0151389190918367 Midmean - Weighted Average at X(n+1)p 0.0151663087878788 Midmean - Empirical Distribution Function 0.0151663087878788 Midmean - Empirical Distribution Function - Averaging 0.0151663087878788 Midmean - Empirical Distribution Function - Interpolation 0.0151663087878788 Midmean - Closest Observation 0.01513910514 Midmean - True Basic - Statistics Graphics Toolkit 0.0151663087878788 Midmean - MS Excel (old versions) 0.0151663087878788 Number of observations 197

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/23/t1224773302bczag8lj95cny6u/1hf4b1224773103.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/23/t1224773302bczag8lj95cny6u/1hf4b1224773103.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/23/t1224773302bczag8lj95cny6u/2qstx1224773103.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/23/t1224773302bczag8lj95cny6u/2qstx1224773103.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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Software written by Ed van Stee & Patrick Wessa

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