Werkloosheidsgraad Central Tendency

*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, 31 Dec 2009 06:38:57 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/31/t1262266811n7sr53ztxwevokg.htm/, Retrieved Thu, 31 Dec 2009 14:40:13 +0100

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/Dec/31/t1262266811n7sr53ztxwevokg.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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7.3 7.2 7.1 7 6.8 6.6 6.3 6.1 6 6.4 6.8 6.8 6.7 6.6 6.5 6.5 6.4 6.3 6.1 5.9 5.9 6.3 6.7 6.8 6.8 6.8 6.8 6.9 6.8 6.7 6.6 6.5 6.5 7 7.5 7.6 7.6 7.6 7.8 8 8 8 7.9 7.9 8 8.5 9.2 9.4 9.5 9.5 9.6 9.7 9.7 9.6 9.5 9.4 9.3 9.6 10.2 10.2 10.1 9.9 9.8 9.8 9.7 9.5 9.3 9.1 9 9.5 10 10.2 10.1 10 9.9 10 9.9 9.7 9.5 9.2 9 9.3 9.8 9.8 9.6 9.4 9.3 9.2 9.2 9 8.8 8.7 8.7 9.1 9.7 9.8 9.6 9.4 9.4 9.5 9.4 9.3 9.2 9 8.9 9.2 9.8 9.9 9.6 9.2 9.1 9.1 9 8.9 8.7 8.5 8.3 8.5 8.7 8.4 8.1 7.8 7.7 7.5 7.2 6.8 6.7 6.4 6.3 6.8 7.3 7.1 7 6.8 6.6 6.3 6.1 6.1 6.3 6.3 6 6.2 6.4 6.8 7.5 7.5 7.6 7.6 7.4 7.3 7.1 6.9 6.8 7.5 7.6 7.8 8 8.1 8.2 8.3 8.2 8 7.9 7.6 7.6 8.3 8.4 8.4 8.4 8.4 8.6 8.9 8.8 8.3 7.5 7.2 7.4 8.8 9.3 9.3 8.7 8.2 8.3 8.5 8.6 8.5 8.2 8.1 7.9 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 8.5 8.3 8 8.2 8.1 8.1 8 7.9 7.9 8 8 7.9 8 7.7 7.2 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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 8.055 0.0742223749848797 108.525225737400 Geometric Mean 7.97220744090017 Harmonic Mean 7.88882560096547 Quadratic Mean 8.13631775846216 Winsorized Mean ( 1 / 80 ) 8.055 0.0742223749848797 108.525225737400 Winsorized Mean ( 2 / 80 ) 8.05583333333333 0.0741234026728595 108.681375150671 Winsorized Mean ( 3 / 80 ) 8.05458333333333 0.0739754471232207 108.881847242056 Winsorized Mean ( 4 / 80 ) 8.05625 0.073786158783565 109.183756585448 Winsorized Mean ( 5 / 80 ) 8.05416666666667 0.0735501225378793 109.505822543241 Winsorized Mean ( 6 / 80 ) 8.05416666666667 0.0735501225378793 109.505822543241 Winsorized Mean ( 7 / 80 ) 8.05416666666667 0.0735501225378793 109.505822543241 Winsorized Mean ( 8 / 80 ) 8.05083333333333 0.0731894231091089 109.999956159394 Winsorized Mean ( 9 / 80 ) 8.05458333333333 0.0727803767133839 110.669712044128 Winsorized Mean ( 10 / 80 ) 8.05875 0.0723463148905504 111.391299089549 Winsorized Mean ( 11 / 80 ) 8.05875 0.0723463148905504 111.391299089549 Winsorized Mean ( 12 / 80 ) 8.05375 0.0718257403511265 112.129021721580 Winsorized Mean ( 13 / 80 ) 8.05375 0.0718257403511265 112.129021721580 Winsorized Mean ( 14 / 80 ) 8.05375 0.0718257403511265 112.129021721580 Winsorized Mean ( 15 / 80 ) 8.05375 0.0718257403511265 112.129021721580 Winsorized Mean ( 16 / 80 ) 8.05375 0.0718257403511265 112.129021721580 Winsorized Mean ( 17 / 80 ) 8.06083333333333 0.0711177733070206 113.344849796325 Winsorized Mean ( 18 / 80 ) 8.05333333333333 0.070366808085551 114.447898838074 Winsorized Mean ( 19 / 80 ) 8.05333333333333 0.070366808085551 114.447898838074 Winsorized Mean ( 20 / 80 ) 8.05333333333333 0.070366808085551 114.447898838074 Winsorized Mean ( 21 / 80 ) 8.05333333333333 0.070366808085551 114.447898838074 Winsorized Mean ( 22 / 80 ) 8.0625 0.0694848673611001 116.032458666153 Winsorized Mean ( 23 / 80 ) 8.05291666666667 0.0685598464929656 117.458207370591 Winsorized Mean ( 24 / 80 ) 8.05291666666667 0.0685598464929656 117.458207370591 Winsorized Mean ( 25 / 80 ) 8.05291666666667 0.0685598464929656 117.458207370591 Winsorized Mean ( 26 / 80 ) 8.05291666666667 0.0685598464929656 117.458207370591 Winsorized Mean ( 27 / 80 ) 8.06416666666667 0.0675161834689914 119.440499334065 Winsorized Mean ( 28 / 80 ) 8.06416666666667 0.0675161834689914 119.440499334065 Winsorized Mean ( 29 / 80 ) 8.05208333333333 0.0663896298799899 121.285257168760 Winsorized Mean ( 30 / 80 ) 8.05208333333333 0.0663896298799899 121.285257168760 Winsorized Mean ( 31 / 80 ) 8.05208333333333 0.0663896298799899 121.285257168760 Winsorized Mean ( 32 / 80 ) 8.06541666666667 0.0651950937562312 123.712018834175 Winsorized Mean ( 33 / 80 ) 8.06541666666667 0.0651950937562312 123.712018834175 Winsorized Mean ( 34 / 80 ) 8.06541666666667 0.0651950937562312 123.712018834175 Winsorized Mean ( 35 / 80 ) 8.06541666666667 0.0651950937562312 123.712018834175 Winsorized Mean ( 36 / 80 ) 8.06541666666667 0.0625418908891677 128.960230527082 Winsorized Mean ( 37 / 80 ) 8.06541666666667 0.0625418908891677 128.960230527082 Winsorized Mean ( 38 / 80 ) 8.06541666666667 0.0625418908891677 128.960230527082 Winsorized Mean ( 39 / 80 ) 8.06541666666667 0.0625418908891677 128.960230527082 Winsorized Mean ( 40 / 80 ) 8.06541666666667 0.0625418908891677 128.960230527082 Winsorized Mean ( 41 / 80 ) 8.06541666666667 0.0625418908891677 128.960230527082 Winsorized Mean ( 42 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 43 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 44 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 45 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 46 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 47 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 48 / 80 ) 8.04791666666667 0.0610089160455465 131.913778973855 Winsorized Mean ( 49 / 80 ) 8.0275 0.0592871560784601 135.400321603831 Winsorized Mean ( 50 / 80 ) 8.04833333333333 0.0575140716111009 139.936768652976 Winsorized Mean ( 51 / 80 ) 8.04833333333333 0.0575140716111009 139.936768652976 Winsorized Mean ( 52 / 80 ) 8.04833333333333 0.0575140716111009 139.936768652976 Winsorized Mean ( 53 / 80 ) 8.04833333333333 0.0575140716111009 139.936768652976 Winsorized Mean ( 54 / 80 ) 8.07083333333333 0.0556682231553164 144.980976145321 Winsorized Mean ( 55 / 80 ) 8.07083333333333 0.0556682231553164 144.980976145321 Winsorized Mean ( 56 / 80 ) 8.0475 0.0537211049120428 149.801460956101 Winsorized Mean ( 57 / 80 ) 8.0475 0.0537211049120428 149.801460956101 Winsorized Mean ( 58 / 80 ) 8.0475 0.0537211049120428 149.801460956101 Winsorized Mean ( 59 / 80 ) 8.0475 0.0537211049120428 149.801460956101 Winsorized Mean ( 60 / 80 ) 8.0475 0.0496744106268983 162.004941748465 Winsorized Mean ( 61 / 80 ) 8.0475 0.0496744106268983 162.004941748465 Winsorized Mean ( 62 / 80 ) 8.0475 0.0496744106268983 162.004941748465 Winsorized Mean ( 63 / 80 ) 8.0475 0.0496744106268983 162.004941748465 Winsorized Mean ( 64 / 80 ) 8.07416666666667 0.0475845854327247 169.680298635405 Winsorized Mean ( 65 / 80 ) 8.04708333333333 0.0454172424566523 177.181239944581 Winsorized Mean ( 66 / 80 ) 8.04708333333333 0.0454172424566523 177.181239944581 Winsorized Mean ( 67 / 80 ) 8.04708333333333 0.0454172424566523 177.181239944581 Winsorized Mean ( 68 / 80 ) 8.01875 0.043231889291857 185.482294004449 Winsorized Mean ( 69 / 80 ) 8.0475 0.0409949694161827 196.304573819813 Winsorized Mean ( 70 / 80 ) 8.0475 0.0409949694161827 196.304573819813 Winsorized Mean ( 71 / 80 ) 8.01791666666667 0.0387687414374684 206.813952926459 Winsorized Mean ( 72 / 80 ) 8.01791666666667 0.0387687414374684 206.813952926459 Winsorized Mean ( 73 / 80 ) 8.01791666666667 0.0387687414374684 206.813952926459 Winsorized Mean ( 74 / 80 ) 8.01791666666667 0.0387687414374684 206.813952926459 Winsorized Mean ( 75 / 80 ) 8.04916666666667 0.0363904503517267 221.188981968308 Winsorized Mean ( 76 / 80 ) 8.04916666666667 0.0363904503517267 221.188981968308 Winsorized Mean ( 77 / 80 ) 8.04916666666667 0.0363904503517267 221.188981968308 Winsorized Mean ( 78 / 80 ) 8.08166666666667 0.034013117222466 237.604410492804 Winsorized Mean ( 79 / 80 ) 8.08166666666667 0.034013117222466 237.604410492804 Winsorized Mean ( 80 / 80 ) 8.04833333333333 0.0315232014058094 255.314592884278 Trimmed Mean ( 1 / 80 ) 8.05504201680672 0.0737443735303046 109.229241923068 Trimmed Mean ( 2 / 80 ) 8.05508474576271 0.0732413596263654 109.980000191900 Trimmed Mean ( 3 / 80 ) 8.05470085470085 0.0727649659594512 110.694765653974 Trimmed Mean ( 4 / 80 ) 8.05474137931034 0.0723172713708136 111.380604199084 Trimmed Mean ( 5 / 80 ) 8.05434782608696 0.0718983223178073 112.024141404647 Trimmed Mean ( 6 / 80 ) 8.05438596491228 0.0715102684054776 112.632579131745 Trimmed Mean ( 7 / 80 ) 8.05442477876106 0.0711004351774557 113.282355567283 Trimmed Mean ( 8 / 80 ) 8.05446428571429 0.0706675658485146 113.976817922102 Trimmed Mean ( 9 / 80 ) 8.05495495495495 0.0702653051577677 114.636305028051 Trimmed Mean ( 10 / 80 ) 8.055 0.0698965166414266 115.241794399035 Trimmed Mean ( 11 / 80 ) 8.0545871559633 0.0695608970939569 115.791881537753 Trimmed Mean ( 12 / 80 ) 8.05416666666667 0.0692049487782522 116.381368801731 Trimmed Mean ( 13 / 80 ) 8.05420560747664 0.0688846968815687 116.923002816198 Trimmed Mean ( 14 / 80 ) 8.05424528301887 0.0685444437445392 117.503984904109 Trimmed Mean ( 15 / 80 ) 8.05428571428571 0.0681829964419885 118.127482430879 Trimmed Mean ( 16 / 80 ) 8.05432692307692 0.0677990686979184 118.797014144299 Trimmed Mean ( 17 / 80 ) 8.05436893203884 0.0673912711201271 119.516501145700 Trimmed Mean ( 18 / 80 ) 8.05392156862745 0.0670195305255895 120.172754202632 Trimmed Mean ( 19 / 80 ) 8.0539603960396 0.066686705466349 120.773103720107 Trimmed Mean ( 20 / 80 ) 8.054 0.0663318897513854 121.419727829053 Trimmed Mean ( 21 / 80 ) 8.0540404040404 0.0659536877807171 122.116604469768 Trimmed Mean ( 22 / 80 ) 8.05408163265306 0.0655505873759672 122.868184024937 Trimmed Mean ( 23 / 80 ) 8.05360824742268 0.0651866926933718 123.546814766407 Trimmed Mean ( 24 / 80 ) 8.05364583333333 0.0648652465953664 124.159642582915 Trimmed Mean ( 25 / 80 ) 8.05368421052632 0.0645211181566349 124.822452564674 Trimmed Mean ( 26 / 80 ) 8.05372340425532 0.0641528003746545 125.539701419444 Trimmed Mean ( 27 / 80 ) 8.05376344086022 0.0637586551193411 126.316394625725 Trimmed Mean ( 28 / 80 ) 8.05326086956522 0.0634073583624774 127.008301205794 Trimmed Mean ( 29 / 80 ) 8.05274725274725 0.0630305485523111 127.759434713852 Trimmed Mean ( 30 / 80 ) 8.05277777777778 0.062700605708979 128.43221667035 Trimmed Mean ( 31 / 80 ) 8.05280898876405 0.0623457521493764 129.163715427958 Trimmed Mean ( 32 / 80 ) 8.05284090909091 0.0619642176659749 129.959534912563 Trimmed Mean ( 33 / 80 ) 8.05229885057471 0.0616297173474013 130.656105482110 Trimmed Mean ( 34 / 80 ) 8.05174418604651 0.0612690148293972 131.416250260698 Trimmed Mean ( 35 / 80 ) 8.05117647058823 0.060880179577862 132.246266788541 Trimmed Mean ( 36 / 80 ) 8.05059523809524 0.0604610943429616 133.153316617605 Trimmed Mean ( 37 / 80 ) 8.05 0.0601734744257092 133.779876878119 Trimmed Mean ( 38 / 80 ) 8.04939024390244 0.0598610350878287 134.467942829460 Trimmed Mean ( 39 / 80 ) 8.04876543209877 0.0595218896218986 135.223620809538 Trimmed Mean ( 40 / 80 ) 8.048125 0.059153966271324 136.053852468410 Trimmed Mean ( 41 / 80 ) 8.04746835443038 0.0587549841581037 136.966564960267 Trimmed Mean ( 42 / 80 ) 8.04679487179487 0.0583224251064871 137.970855243121 Trimmed Mean ( 43 / 80 ) 8.04675324675325 0.0579490513150482 138.859102334669 Trimmed Mean ( 44 / 80 ) 8.0467105263158 0.0575429111037774 139.838433126953 Trimmed Mean ( 45 / 80 ) 8.04666666666667 0.0571012419041371 140.919293492348 Trimmed Mean ( 46 / 80 ) 8.04662162162162 0.0566209721934497 142.11380182823 Trimmed Mean ( 47 / 80 ) 8.04657534246575 0.0560986746514494 143.436104194270 Trimmed Mean ( 48 / 80 ) 8.04652777777778 0.0555305098458648 144.902825493812 Trimmed Mean ( 49 / 80 ) 8.04647887323944 0.0549121579636926 146.533648860780 Trimmed Mean ( 50 / 80 ) 8.04714285714286 0.0543526119958714 148.054390794579 Trimmed Mean ( 51 / 80 ) 8.04710144927536 0.0538597214612195 149.408523307524 Trimmed Mean ( 52 / 80 ) 8.04705882352941 0.0533204761511299 150.91873524762 Trimmed Mean ( 53 / 80 ) 8.04701492537313 0.0527303056037261 152.607022342091 Trimmed Mean ( 54 / 80 ) 8.0469696969697 0.0520840194054029 154.499783020489 Trimmed Mean ( 55 / 80 ) 8.04615384615385 0.0515028045291085 156.227489351697 Trimmed Mean ( 56 / 80 ) 8.0453125 0.0508643229500146 158.172015931605 Trimmed Mean ( 57 / 80 ) 8.0452380952381 0.0503020355908237 159.938618800264 Trimmed Mean ( 58 / 80 ) 8.04516129032258 0.0496823748128702 161.931898799622 Trimmed Mean ( 59 / 80 ) 8.04508196721311 0.0489989542677039 164.18885030197 Trimmed Mean ( 60 / 80 ) 8.045 0.0482443883617915 166.755145482816 Trimmed Mean ( 61 / 80 ) 8.04491525423729 0.0477146477577208 168.604728994055 Trimmed Mean ( 62 / 80 ) 8.0448275862069 0.047126497726707 170.707096310444 Trimmed Mean ( 63 / 80 ) 8.04473684210526 0.0464730625693931 173.105373249136 Trimmed Mean ( 64 / 80 ) 8.04464285714286 0.0457463363956082 175.853270250406 Trimmed Mean ( 65 / 80 ) 8.04363636363636 0.0451025570792983 178.341027305707 Trimmed Mean ( 66 / 80 ) 8.04351851851852 0.0445599449652554 180.510064022527 Trimmed Mean ( 67 / 80 ) 8.0433962264151 0.0439516778665589 183.005441813519 Trimmed Mean ( 68 / 80 ) 8.04326923076923 0.0432692307692308 185.888888888889 Trimmed Mean ( 69 / 80 ) 8.04411764705882 0.0426862865932068 188.447351340676 Trimmed Mean ( 70 / 80 ) 8.044 0.0422192449774347 190.529224392794 Trimmed Mean ( 71 / 80 ) 8.0438775510204 0.0416891991498211 192.948718494510 Trimmed Mean ( 72 / 80 ) 8.04479166666667 0.0412754385056102 194.905056322375 Trimmed Mean ( 73 / 80 ) 8.04574468085106 0.0408014228339897 197.192747752623 Trimmed Mean ( 74 / 80 ) 8.04673913043478 0.0402586918783349 199.875821965420 Trimmed Mean ( 75 / 80 ) 8.04777777777778 0.0396371739972886 203.03611398553 Trimmed Mean ( 76 / 80 ) 8.04772727272727 0.0391583765674779 205.517388057684 Trimmed Mean ( 77 / 80 ) 8.04767441860465 0.0386051868174398 208.460962944211 Trimmed Mean ( 78 / 80 ) 8.04761904761905 0.0379659308608114 211.969491203120 Trimmed Mean ( 79 / 80 ) 8.04634146341463 0.0374670435108858 214.757843411819 Trimmed Mean ( 80 / 80 ) 8.045 0.0368841841169719 218.115167587458 Median 8 Midrange 8.05 Midmean - Weighted Average at Xnp 7.9952380952381 Midmean - Weighted Average at X(n+1)p 8.045 Midmean - Empirical Distribution Function 7.9952380952381 Midmean - Empirical Distribution Function - Averaging 8.045 Midmean - Empirical Distribution Function - Interpolation 8.045 Midmean - Closest Observation 7.9952380952381 Midmean - True Basic - Statistics Graphics Toolkit 8.045 Midmean - MS Excel (old versions) 8.02923076923077 Number of observations 240

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/31/t1262266811n7sr53ztxwevokg/1zjg31262266733.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/31/t1262266811n7sr53ztxwevokg/1zjg31262266733.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/31/t1262266811n7sr53ztxwevokg/29qno1262266733.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/31/t1262266811n7sr53ztxwevokg/29qno1262266733.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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