centrummaten Gemiddelde consumptieprijs cola-limonade

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 08 Dec 2009 11:31:35 -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/08/t1260297173nrk38x3y1siyn1n.htm/, Retrieved Tue, 08 Dec 2009 19:32:55 +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/08/t1260297173nrk38x3y1siyn1n.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

1,14 1,15 1,15 1,14 1,14 1,14 1,15 1,14 1,14 1,15 1,15 1,14 1,15 1,17 1,17 1,17 1,17 1,17 1,17 1,17 1,17 1,17 1,17 1,17 1,17 1,18 1,19 1,19 1,19 1,19 1,18 1,19 1,19 1,2 1,21 1,21 1,2 1,21 1,21 1,21 1,21 1,21 1,21 1,2 1,21 1,22 1,22 1,23 1,22 1,23 1,23 1,23 1,23 1,23 1,22 1,22 1,23 1,24 1,24 1,25 1,25 1,25 1,26 1,26 1,26 1,26 1,27 1,27 1,29 1,31 1,32 1,32 1,33 1,33 1,32 1,32 1,31 1,3 1,31 1,29 1,3 1,3 1,32 1,31 1,35 1,35 1,36 1,37 1,37 1,37 1,32 1,32 1,31 1,31 1,34 1,31 1,26 1,27 1,24 1,25 1,27 1,25 1,26 1,27 1,26 1,26 1,28 1,27 1,28 1,27 1,26 1,27 1,27 1,28 1,27 1,26 1,3 1,31 1,28 1,29 1,31 1,29 1,29 1,32 1,3 1,29 1,31 1,29 1,33 1,35 1,32 1,33

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 1.24772727272727 0.00544736013743645 229.051731709895 Geometric Mean 1.24616294826203 Harmonic Mean 1.24459306845471 Quadratic Mean 1.24928403738325 Winsorized Mean ( 1 / 44 ) 1.24772727272727 0.00544736013743645 229.051731709895 Winsorized Mean ( 2 / 44 ) 1.24772727272727 0.00544736013743645 229.051731709895 Winsorized Mean ( 3 / 44 ) 1.2475 0.00540984507909262 230.598100640849 Winsorized Mean ( 4 / 44 ) 1.24719696969697 0.00536361659677658 232.529105537951 Winsorized Mean ( 5 / 44 ) 1.24719696969697 0.00536361659677658 232.529105537951 Winsorized Mean ( 6 / 44 ) 1.24719696969697 0.00536361659677658 232.529105537951 Winsorized Mean ( 7 / 44 ) 1.24719696969697 0.00521048338478899 239.363006767841 Winsorized Mean ( 8 / 44 ) 1.24659090909091 0.00513165727403405 242.921700051678 Winsorized Mean ( 9 / 44 ) 1.24659090909091 0.00513165727403405 242.921700051678 Winsorized Mean ( 10 / 44 ) 1.24659090909091 0.00513165727403405 242.921700051678 Winsorized Mean ( 11 / 44 ) 1.24659090909091 0.00513165727403405 242.921700051678 Winsorized Mean ( 12 / 44 ) 1.24568181818182 0.00502387681099967 247.952301587974 Winsorized Mean ( 13 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 14 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 15 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 16 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 17 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 18 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 19 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 20 / 44 ) 1.24765151515152 0.00475742823299994 262.253354973843 Winsorized Mean ( 21 / 44 ) 1.24606060606061 0.00458017428501573 272.055281856229 Winsorized Mean ( 22 / 44 ) 1.24606060606061 0.00458017428501573 272.055281856229 Winsorized Mean ( 23 / 44 ) 1.24606060606061 0.00458017428501573 272.055281856229 Winsorized Mean ( 24 / 44 ) 1.24606060606061 0.00458017428501573 272.055281856229 Winsorized Mean ( 25 / 44 ) 1.24795454545455 0.00434694028590466 287.088035117747 Winsorized Mean ( 26 / 44 ) 1.24795454545455 0.00434694028590466 287.088035117747 Winsorized Mean ( 27 / 44 ) 1.25 0.00411071617953302 304.083265642047 Winsorized Mean ( 28 / 44 ) 1.25 0.00411071617953302 304.083265642047 Winsorized Mean ( 29 / 44 ) 1.25 0.00411071617953302 304.083265642047 Winsorized Mean ( 30 / 44 ) 1.25 0.00411071617953302 304.083265642047 Winsorized Mean ( 31 / 44 ) 1.24765151515152 0.0038579625691395 323.396480082957 Winsorized Mean ( 32 / 44 ) 1.24765151515152 0.0038579625691395 323.396480082957 Winsorized Mean ( 33 / 44 ) 1.25015151515152 0.00358141947365483 349.065928844057 Winsorized Mean ( 34 / 44 ) 1.25015151515152 0.00358141947365483 349.065928844057 Winsorized Mean ( 35 / 44 ) 1.25015151515152 0.00358141947365483 349.065928844057 Winsorized Mean ( 36 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 37 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 38 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 39 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 40 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 41 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 42 / 44 ) 1.25015151515152 0.00301316574481833 414.896365160586 Winsorized Mean ( 43 / 44 ) 1.24689393939394 0.00269536784425439 462.606223507449 Winsorized Mean ( 44 / 44 ) 1.24689393939394 0.00269536784425439 462.606223507449 Trimmed Mean ( 1 / 44 ) 1.24761538461538 0.00538644231721263 231.621413753670 Trimmed Mean ( 2 / 44 ) 1.2475 0.00531951540034318 234.513843106746 Trimmed Mean ( 3 / 44 ) 1.24738095238095 0.00524592488424649 237.780940426127 Trimmed Mean ( 4 / 44 ) 1.24733870967742 0.00517983551103926 240.806625426443 Trimmed Mean ( 5 / 44 ) 1.24737704918033 0.0051212149884025 243.570530041238 Trimmed Mean ( 6 / 44 ) 1.24741666666667 0.00505639877126798 246.700611066294 Trimmed Mean ( 7 / 44 ) 1.24745762711864 0.00498467365747294 250.258635336834 Trimmed Mean ( 8 / 44 ) 1.2475 0.00493568075626212 252.751355204090 Trimmed Mean ( 9 / 44 ) 1.24763157894737 0.00489495719964141 254.880998558837 Trimmed Mean ( 10 / 44 ) 1.24776785714286 0.00484925564056098 257.311214262672 Trimmed Mean ( 11 / 44 ) 1.24790909090909 0.00479799696625211 260.089595655555 Trimmed Mean ( 12 / 44 ) 1.24805555555556 0.00474051189035294 263.274427830332 Trimmed Mean ( 13 / 44 ) 1.24830188679245 0.00469074464461583 266.120196550305 Trimmed Mean ( 14 / 44 ) 1.24836538461538 0.00467005175963795 267.312965437489 Trimmed Mean ( 15 / 44 ) 1.24843137254902 0.00464576070900256 268.724854926301 Trimmed Mean ( 16 / 44 ) 1.2485 0.00461743511819139 270.388206448481 Trimmed Mean ( 17 / 44 ) 1.24857142857143 0.00458457241505771 272.341958100734 Trimmed Mean ( 18 / 44 ) 1.24864583333333 0.00454659066327251 274.633439825566 Trimmed Mean ( 19 / 44 ) 1.24872340425532 0.00450281195997109 277.320797616283 Trimmed Mean ( 20 / 44 ) 1.24880434782609 0.00445244123491983 280.476323422733 Trimmed Mean ( 21 / 44 ) 1.24888888888889 0.00439453878662792 284.191117550064 Trimmed Mean ( 22 / 44 ) 1.24909090909091 0.00434784673773909 287.289544557508 Trimmed Mean ( 23 / 44 ) 1.24930232558140 0.00429357263945121 290.970348120412 Trimmed Mean ( 24 / 44 ) 1.24952380952381 0.0042305366208719 295.358230291430 Trimmed Mean ( 25 / 44 ) 1.24975609756098 0.00415730876801273 300.616616975116 Trimmed Mean ( 26 / 44 ) 1.249875 0.00410114892052879 304.762159146087 Trimmed Mean ( 27 / 44 ) 1.25 0.00403530869745009 309.765644643215 Trimmed Mean ( 28 / 44 ) 1.25 0.00398682039250645 313.533060668967 Trimmed Mean ( 29 / 44 ) 1.25 0.00392921447590107 318.129745186114 Trimmed Mean ( 30 / 44 ) 1.25 0.0038608423027087 323.763547431871 Trimmed Mean ( 31 / 44 ) 1.25 0.00377964473009228 330.718913883074 Trimmed Mean ( 32 / 44 ) 1.25014705882353 0.00371559515672697 336.459438149546 Trimmed Mean ( 33 / 44 ) 1.25030303030303 0.00363849976108393 343.631472420534 Trimmed Mean ( 34 / 44 ) 1.2503125 0.00358408595363112 348.851148152091 Trimmed Mean ( 35 / 44 ) 1.25032258064516 0.00351748478367102 355.459272048439 Trimmed Mean ( 36 / 44 ) 1.25033333333333 0.00343598986688675 363.893195781227 Trimmed Mean ( 37 / 44 ) 1.25034482758621 0.00341667309023385 365.953895665397 Trimmed Mean ( 38 / 44 ) 1.25035714285714 0.00338986539320436 368.851561293179 Trimmed Mean ( 39 / 44 ) 1.25037037037037 0.00335384634745831 372.816832028682 Trimmed Mean ( 40 / 44 ) 1.25038461538462 0.00330639421720597 378.171667757525 Trimmed Mean ( 41 / 44 ) 1.2504 0.00324458732950364 385.380288158645 Trimmed Mean ( 42 / 44 ) 1.25041666666667 0.00316449627002877 395.139244912207 Trimmed Mean ( 43 / 44 ) 1.25043478260870 0.00306068291042651 408.547640903594 Trimmed Mean ( 44 / 44 ) 1.25068181818182 0.00298689398079480 418.723204179152 Median 1.26 Midrange 1.255 Midmean - Weighted Average at Xnp 1.24675675675676 Midmean - Weighted Average at X(n+1)p 1.25176470588235 Midmean - Empirical Distribution Function 1.24675675675676 Midmean - Empirical Distribution Function - Averaging 1.25176470588235 Midmean - Empirical Distribution Function - Interpolation 1.25176470588235 Midmean - Closest Observation 1.24675675675676 Midmean - True Basic - Statistics Graphics Toolkit 1.25176470588235 Midmean - MS Excel (old versions) 1.24675675675676 Number of observations 132

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297173nrk38x3y1siyn1n/1hvsj1260297093.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297173nrk38x3y1siyn1n/1hvsj1260297093.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297173nrk38x3y1siyn1n/2j14h1260297093.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/08/t1260297173nrk38x3y1siyn1n/2j14h1260297093.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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