Task 4

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sat, 02 Oct 2010 18:10:17 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Oct/02/t1286043068zf7otbctvttt8xj.htm/, Retrieved Sat, 02 Oct 2010 20:11:08 +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/2010/Oct/02/t1286043068zf7otbctvttt8xj.htm/}, year = {2010}, } @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 = {2010}, 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:

» Textbox « » Textfile « » CSV «

426,11 383,7 232,44 70,94 226,73 947,29 611,28 158,05 34 37,03 388,3 506,65 392,25 180,82 198,3 217,47 275,56 1030,94 57,47 136,45 556,28 213,36 274,48 220,55 236,71 260,64 2763,54 213,92 169,86 403,06 449,59 406,17 206,89 156,19 257,1 62,16 662,88 251,42 171,33 350,09 221,59 4,81 183,19 190,38 223,17 232,67 356,73 109,22 475,83 315,96 694,87 8,95 278,74 308,16 207,53 192,8 601,16 289,71 293,67 386,69 699,65 85,09 131,81 645,29 197,55 308,17 86,58 242,21 238,5 187,88 140,32 440,31 421,4 218,76 1305,92 137,55 262,52 348,82 150,03 64,02 261,6 259,7 171,26 203,08 249,15 211,66 252,64 438,56 239,89 401,92 216,89 184,64 380,16 653,64 313,91 366,94 236,3 229,64 235,58 103,9 263,91 241,17 216,55 295,28 193,3 204,39 257,57 136,81 240,76 59,61 213,51 380,53 242,34 250,41 183,61 191,84 266,79 246,54 330,56 403,56 208,11 324,04 308,53 199,3 200,16 262,88 287,07 190,16 199,75 265,78 435,96 72 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 2 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 333.341294964029 36.8855674811175 9.037174096201 Geometric Mean 240.574910318827 Harmonic Mean 137.565736453516 Quadratic Mean 546.691541116247 Winsorized Mean ( 1 / 46 ) 323.019856115108 29.7848126686619 10.8451196154399 Winsorized Mean ( 2 / 46 ) 302.407338129496 19.0314707432886 15.8898564492784 Winsorized Mean ( 3 / 46 ) 296.537913669065 16.9471545256809 17.4977995993195 Winsorized Mean ( 4 / 46 ) 294.188848920863 16.2106890068926 18.1478312732899 Winsorized Mean ( 5 / 46 ) 287.987050359712 14.3061295773171 20.1303258720882 Winsorized Mean ( 6 / 46 ) 285.627194244604 13.7360107238629 20.7940427527767 Winsorized Mean ( 7 / 46 ) 285.514892086331 13.6683418497857 20.8887731389896 Winsorized Mean ( 8 / 46 ) 283.780791366906 13.2650115407313 21.3931808875955 Winsorized Mean ( 9 / 46 ) 283.630575539568 13.0884998879456 21.6702126269481 Winsorized Mean ( 10 / 46 ) 283.16654676259 12.9500124560539 21.866121575058 Winsorized Mean ( 11 / 46 ) 281.444532374101 12.3024616993624 22.8770907198749 Winsorized Mean ( 12 / 46 ) 280.699496402878 12.1189773501990 23.1619787950399 Winsorized Mean ( 13 / 46 ) 278.121942446043 11.1507128348291 24.9420773869571 Winsorized Mean ( 14 / 46 ) 273.659064748201 10.2229324040959 26.7691356971662 Winsorized Mean ( 15 / 46 ) 272.770935251799 9.412987714393 28.9781463152997 Winsorized Mean ( 16 / 46 ) 270.284604316547 8.89786018441472 30.3763600140594 Winsorized Mean ( 17 / 46 ) 269.331870503597 8.74921163469227 30.7835587649572 Winsorized Mean ( 18 / 46 ) 269.281366906475 8.71787559542545 30.8884158713822 Winsorized Mean ( 19 / 46 ) 269.420791366906 8.64268820751069 31.1732628666129 Winsorized Mean ( 20 / 46 ) 270.44381294964 8.4417264880724 32.0365523962141 Winsorized Mean ( 21 / 46 ) 269.886330935252 8.13722630864865 33.1668704664639 Winsorized Mean ( 22 / 46 ) 269.435251798561 8.00434142205224 33.6611393232499 Winsorized Mean ( 23 / 46 ) 268.869352517986 7.47045944174523 35.9910062579997 Winsorized Mean ( 24 / 46 ) 268.660431654676 7.38747846535027 36.3670003120528 Winsorized Mean ( 25 / 46 ) 268.58309352518 7.37438402118356 36.4210885619262 Winsorized Mean ( 26 / 46 ) 270.144964028777 7.1812363274756 37.6181693109298 Winsorized Mean ( 27 / 46 ) 270.508201438849 7.1271319055246 37.9547067494520 Winsorized Mean ( 28 / 46 ) 268.745611510791 6.87639462323402 39.0823427443724 Winsorized Mean ( 29 / 46 ) 268.136402877698 6.75033985636949 39.7219115752653 Winsorized Mean ( 30 / 46 ) 268.488201438849 6.64344251076394 40.414017432052 Winsorized Mean ( 31 / 46 ) 268.329856115108 6.51318871153057 41.1979243960907 Winsorized Mean ( 32 / 46 ) 267.650719424460 6.41541342628 41.7199487609107 Winsorized Mean ( 33 / 46 ) 267.909496402878 6.37409424390083 42.0309907810403 Winsorized Mean ( 34 / 46 ) 264.910647482014 5.94607827201236 44.5521628480615 Winsorized Mean ( 35 / 46 ) 262.465683453237 5.61872908462713 46.7126425745183 Winsorized Mean ( 36 / 46 ) 261.846690647482 5.31330764137003 49.2812967592377 Winsorized Mean ( 37 / 46 ) 261.708273381295 5.25518081596511 49.8000511392932 Winsorized Mean ( 38 / 46 ) 256.989712230216 4.64376971921666 55.3407528299156 Winsorized Mean ( 39 / 46 ) 255.286618705036 4.42428935539014 57.7011579032503 Winsorized Mean ( 40 / 46 ) 253.079424460432 4.15495995903452 60.9101957553496 Winsorized Mean ( 41 / 46 ) 253.336043165468 4.00983844100952 63.1786160196737 Winsorized Mean ( 42 / 46 ) 252.106258992806 3.79731224230991 66.3907108253624 Winsorized Mean ( 43 / 46 ) 252.731151079137 3.71880595851073 67.960295293371 Winsorized Mean ( 44 / 46 ) 252.765971223022 3.71506346458879 68.0381300702758 Winsorized Mean ( 45 / 46 ) 248.803381294964 3.25464958992923 76.4455202995828 Winsorized Mean ( 46 / 46 ) 248.462517985612 3.18201623967117 78.0833595026804 Trimmed Mean ( 1 / 46 ) 307.498321167883 24.2195046140988 12.6963092791287 Trimmed Mean ( 2 / 46 ) 291.516888888889 16.2442130674572 17.9458917263834 Trimmed Mean ( 3 / 46 ) 285.826015037594 14.4659880019919 19.7584855592468 Trimmed Mean ( 4 / 46 ) 282.037328244275 13.3933627517314 21.0579921915290 Trimmed Mean ( 5 / 46 ) 278.763953488372 12.4317226655392 22.4235981599805 Trimmed Mean ( 6 / 46 ) 276.745039370079 11.9214241773633 23.2140921464374 Trimmed Mean ( 7 / 46 ) 275.09888 11.4943883931168 23.9333203813381 Trimmed Mean ( 8 / 46 ) 273.417317073171 11.0310056673555 24.7862547911027 Trimmed Mean ( 9 / 46 ) 271.929173553719 10.5958175909793 25.6638217125619 Trimmed Mean ( 10 / 46 ) 270.410504201681 10.1400453891243 26.6675832133561 Trimmed Mean ( 11 / 46 ) 268.895042735043 9.65041891696794 27.8635616804422 Trimmed Mean ( 12 / 46 ) 267.516086956522 9.21287311125488 29.037205193862 Trimmed Mean ( 13 / 46 ) 266.164690265487 8.74774387933042 30.4266670283287 Trimmed Mean ( 14 / 46 ) 265.012882882883 8.38191276861833 31.6172322712644 Trimmed Mean ( 15 / 46 ) 264.225321100917 8.11437035941454 32.5626400321197 Trimmed Mean ( 16 / 46 ) 263.48523364486 7.92718863802295 33.2381687476247 Trimmed Mean ( 17 / 46 ) 262.922666666667 7.7856396692776 33.7702074376969 Trimmed Mean ( 18 / 46 ) 262.413883495146 7.64559321982903 34.3222397464946 Trimmed Mean ( 19 / 46 ) 261.888811881188 7.49166779312306 34.9573444943178 Trimmed Mean ( 20 / 46 ) 261.332222222222 7.32692851322861 35.6673634457321 Trimmed Mean ( 21 / 46 ) 260.679381443299 7.16398368495368 36.3874895459068 Trimmed Mean ( 22 / 46 ) 260.037894736842 7.01615650581598 37.0627272241271 Trimmed Mean ( 23 / 46 ) 259.399462365591 6.86402914680787 37.7911364910543 Trimmed Mean ( 24 / 46 ) 258.770549450549 6.7532848415043 38.3177306338685 Trimmed Mean ( 25 / 46 ) 258.126966292135 6.63568608250949 38.8998157963669 Trimmed Mean ( 26 / 46 ) 257.458735632184 6.50173275858544 39.5984801578031 Trimmed Mean ( 27 / 46 ) 256.660823529412 6.36744160420515 40.3083121107714 Trimmed Mean ( 28 / 46 ) 255.801927710843 6.21714971326023 41.1445661611232 Trimmed Mean ( 29 / 46 ) 255.008641975309 6.07554368281242 41.9729748132208 Trimmed Mean ( 30 / 46 ) 254.212151898734 5.92639598869576 42.8948980769474 Trimmed Mean ( 31 / 46 ) 253.353116883117 5.76386040624073 43.9554567644981 Trimmed Mean ( 32 / 46 ) 252.457733333333 5.58911173646069 45.1695627565325 Trimmed Mean ( 33 / 46 ) 251.553698630137 5.39631814876268 46.6158020515924 Trimmed Mean ( 34 / 46 ) 250.58338028169 5.17080251699531 48.4612165051898 Trimmed Mean ( 35 / 46 ) 249.734492753623 4.97128097674146 50.235441111059 Trimmed Mean ( 36 / 46 ) 248.979850746269 4.78590307326727 52.0235882203719 Trimmed Mean ( 37 / 46 ) 248.215538461538 4.60922632957512 53.8518876517004 Trimmed Mean ( 38 / 46 ) 247.410952380952 4.40306245955572 56.1906524500942 Trimmed Mean ( 39 / 46 ) 246.836557377049 4.26181765453489 57.9181413626172 Trimmed Mean ( 40 / 46 ) 246.326101694915 4.12700262576996 59.6864417184515 Trimmed Mean ( 41 / 46 ) 245.914385964912 4.00869077823237 61.3453118659725 Trimmed Mean ( 42 / 46 ) 245.456909090909 3.88489563989093 63.1823688056136 Trimmed Mean ( 43 / 46 ) 245.041698113208 3.76903138565545 65.0145018812556 Trimmed Mean ( 44 / 46 ) 244.55431372549 3.63472397479279 67.2827745439547 Trimmed Mean ( 45 / 46 ) 244.024897959184 3.46327852470228 70.460662120775 Trimmed Mean ( 46 / 46 ) 243.71085106383 3.34889151210252 72.773587971747 Median 241.17 Midrange 2103.585 Midmean - Weighted Average at Xnp 248.921142857143 Midmean - Weighted Average at X(n+1)p 250.58338028169 Midmean - Empirical Distribution Function 250.58338028169 Midmean - Empirical Distribution Function - Averaging 250.58338028169 Midmean - Empirical Distribution Function - Interpolation 249.734492753623 Midmean - Closest Observation 248.921142857143 Midmean - True Basic - Statistics Graphics Toolkit 250.58338028169 Midmean - MS Excel (old versions) 250.58338028169 Number of observations 139

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/02/t1286043068zf7otbctvttt8xj/1qw731286043013.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/02/t1286043068zf7otbctvttt8xj/1qw731286043013.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/02/t1286043068zf7otbctvttt8xj/2j57o1286043013.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/02/t1286043068zf7otbctvttt8xj/2j57o1286043013.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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