centrummaten consumptieprijs van rundsvlees in Denemarken

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 27 Dec 2010 16:26:45 +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/Dec/27/t1293467104hnnb9luz87j68ro.htm/, Retrieved Mon, 27 Dec 2010 17:25:06 +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/2010/Dec/27/t1293467104hnnb9luz87j68ro.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

98,4 96,5 97,4 99,2 100,8 101,8 102,7 100 100,8 101,7 99 101,7 100,2 101,2 99,5 100,8 100,7 99,5 99,4 101,1 97,2 98,1 97,8 95,5 96,3 93,6 96,7 95,1 97,7 96,5 98,1 97,3 97 93,7 95,6 94,6 95,1 94,5 93,6 92,1 95,9 98,1 98,2 96,2 94,1 95 93,4 95,4 93,5 94,5 94,3 95,7 98,4 99,4 99,2 99 99,4 99,3 98,6 98,7 96 98,7 100,1 100 101,5 101,5 103,8 104,1 101 104,9 104,4 105,6 103,4 101,7 103,5 101,2 105,4 105,4 108,6 110,6 110,2 106,2 108,6 107,5 106,9 108,4 109,9 108,6 106,5 105,7 105,6 104,2 105,1 102,7 108,3 104,2 105,4 104,6 106,4 111 111,7 113,8 115,9 117,3 113,6 113,6 114,6 113,2 112,8 109,6 111,1 109,7 113 111 113,3 111,8 107,2 106,4 110 108,2

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 102.416666666667 0.557985488869542 183.547186637701 Geometric Mean 102.238440317527 Harmonic Mean 102.062974660976 Quadratic Mean 102.597387880979 Winsorized Mean ( 1 / 40 ) 102.415833333333 0.553901360219857 184.89904645239 Winsorized Mean ( 2 / 40 ) 102.395833333333 0.549434896642838 186.365725873972 Winsorized Mean ( 3 / 40 ) 102.378333333333 0.545469221253776 187.688561231767 Winsorized Mean ( 4 / 40 ) 102.371666666667 0.544304844523889 188.077816496769 Winsorized Mean ( 5 / 40 ) 102.375833333333 0.543743374129221 188.279688919949 Winsorized Mean ( 6 / 40 ) 102.380833333333 0.538531169473843 190.111249147123 Winsorized Mean ( 7 / 40 ) 102.386666666667 0.536046495189241 191.003331960078 Winsorized Mean ( 8 / 40 ) 102.386666666667 0.53212345260681 192.411490538683 Winsorized Mean ( 9 / 40 ) 102.371666666667 0.529625393924633 193.29070667868 Winsorized Mean ( 10 / 40 ) 102.296666666667 0.515223338662126 198.548200344144 Winsorized Mean ( 11 / 40 ) 102.324166666667 0.509286307673729 200.916783202073 Winsorized Mean ( 12 / 40 ) 102.274166666667 0.498975836008754 204.968175382490 Winsorized Mean ( 13 / 40 ) 102.263333333333 0.497371147021842 205.607691450671 Winsorized Mean ( 14 / 40 ) 102.298333333333 0.493195978872595 207.419236400059 Winsorized Mean ( 15 / 40 ) 102.260833333333 0.484404245600644 211.106393600109 Winsorized Mean ( 16 / 40 ) 102.220833333333 0.475220567738674 215.101871157953 Winsorized Mean ( 17 / 40 ) 102.206666666667 0.46959177296878 217.650036797944 Winsorized Mean ( 18 / 40 ) 102.221666666667 0.464038995713166 220.286802641588 Winsorized Mean ( 19 / 40 ) 102.205833333333 0.457851357225019 223.229289856844 Winsorized Mean ( 20 / 40 ) 102.2225 0.451796077205359 226.258051270188 Winsorized Mean ( 21 / 40 ) 102.065 0.426528639920309 239.292254839134 Winsorized Mean ( 22 / 40 ) 102.101666666667 0.422403061548125 241.716208903553 Winsorized Mean ( 23 / 40 ) 102.101666666667 0.422403061548125 241.716208903553 Winsorized Mean ( 24 / 40 ) 102.101666666667 0.412824837437416 247.324427717228 Winsorized Mean ( 25 / 40 ) 102.143333333333 0.40336770925573 253.226351513864 Winsorized Mean ( 26 / 40 ) 102.165 0.395985898653946 258.001611540421 Winsorized Mean ( 27 / 40 ) 102.03 0.373824207101582 272.935775858610 Winsorized Mean ( 28 / 40 ) 101.983333333333 0.362811410397292 281.091857672441 Winsorized Mean ( 29 / 40 ) 101.983333333333 0.346491687147573 294.331255600652 Winsorized Mean ( 30 / 40 ) 101.908333333333 0.332119463449325 306.842400246388 Winsorized Mean ( 31 / 40 ) 101.96 0.321174751947465 317.459574209238 Winsorized Mean ( 32 / 40 ) 101.96 0.321174751947465 317.459574209238 Winsorized Mean ( 33 / 40 ) 101.905 0.314826994418468 323.68571249182 Winsorized Mean ( 34 / 40 ) 101.791666666667 0.295954476714886 343.94366254081 Winsorized Mean ( 35 / 40 ) 101.820833333333 0.286822874107193 354.995512998312 Winsorized Mean ( 36 / 40 ) 101.820833333333 0.286822874107193 354.995512998312 Winsorized Mean ( 37 / 40 ) 101.820833333333 0.273884025000231 371.766236943712 Winsorized Mean ( 38 / 40 ) 101.8525 0.270770149923576 376.158524227089 Winsorized Mean ( 39 / 40 ) 101.8525 0.270770149923576 376.158524227089 Winsorized Mean ( 40 / 40 ) 101.8525 0.250120314186248 407.214025503571 Trimmed Mean ( 1 / 40 ) 102.377966101695 0.546141477714226 187.456859219298 Trimmed Mean ( 2 / 40 ) 102.338793103448 0.537519947053917 190.390689060667 Trimmed Mean ( 3 / 40 ) 102.308771929825 0.530525369059301 192.844259476663 Trimmed Mean ( 4 / 40 ) 102.283928571429 0.524325505268694 195.077156353499 Trimmed Mean ( 5 / 40 ) 102.26 0.517761590136023 197.504028781152 Trimmed Mean ( 6 / 40 ) 102.234259259259 0.510558578783469 200.240018496717 Trimmed Mean ( 7 / 40 ) 102.206603773585 0.503679665574155 202.919853151263 Trimmed Mean ( 8 / 40 ) 102.176923076923 0.496453499197688 205.813682937173 Trimmed Mean ( 9 / 40 ) 102.146078431373 0.489054475375429 208.864418126342 Trimmed Mean ( 10 / 40 ) 102.116 0.481151228877684 212.232649261215 Trimmed Mean ( 11 / 40 ) 102.093877551020 0.474646083452923 215.094743452458 Trimmed Mean ( 12 / 40 ) 102.067708333333 0.468167608481031 218.015314353959 Trimmed Mean ( 13 / 40 ) 102.045744680851 0.462349705108386 220.711170686113 Trimmed Mean ( 14 / 40 ) 102.023913043478 0.455927593258355 223.772183460863 Trimmed Mean ( 15 / 40 ) 101.997777777778 0.449132824537295 227.099361715229 Trimmed Mean ( 16 / 40 ) 101.973863636364 0.442561575328940 230.417346016925 Trimmed Mean ( 17 / 40 ) 101.952325581395 0.436246666328652 233.703391797585 Trimmed Mean ( 18 / 40 ) 101.930952380952 0.42969246828299 237.218382691832 Trimmed Mean ( 19 / 40 ) 101.907317073171 0.422805831459957 241.02628083743 Trimmed Mean ( 20 / 40 ) 101.88375 0.415614703165494 245.139907765560 Trimmed Mean ( 21 / 40 ) 101.857692307692 0.408001550859463 249.650257684382 Trimmed Mean ( 22 / 40 ) 101.842105263158 0.402497741773745 253.025283606203 Trimmed Mean ( 23 / 40 ) 101.822972972973 0.396483745691014 256.814999554421 Trimmed Mean ( 24 / 40 ) 101.802777777778 0.389338411109798 261.476327207459 Trimmed Mean ( 25 / 40 ) 101.781428571429 0.382133559609037 266.350405537691 Trimmed Mean ( 26 / 40 ) 101.755882352941 0.374771703132152 271.514315255173 Trimmed Mean ( 27 / 40 ) 101.727272727273 0.366922217289993 277.244789041689 Trimmed Mean ( 28 / 40 ) 101.70625 0.360712444007557 281.959360398083 Trimmed Mean ( 29 / 40 ) 101.687096774194 0.354718021877631 286.670229597957 Trimmed Mean ( 30 / 40 ) 101.666666666667 0.349646041088648 290.770249679134 Trimmed Mean ( 31 / 40 ) 101.65 0.345415484929787 294.283274592227 Trimmed Mean ( 32 / 40 ) 101.628571428571 0.341527454028644 297.570723026114 Trimmed Mean ( 33 / 40 ) 101.605555555556 0.336467619373038 301.977217733117 Trimmed Mean ( 34 / 40 ) 101.584615384615 0.331018181245559 306.885304614906 Trimmed Mean ( 35 / 40 ) 101.57 0.327130380298568 310.487824173647 Trimmed Mean ( 36 / 40 ) 101.552083333333 0.323352199996098 314.060282671832 Trimmed Mean ( 37 / 40 ) 101.532608695652 0.31816281718621 319.12154158551 Trimmed Mean ( 38 / 40 ) 101.511363636364 0.313512055213471 323.787752171904 Trimmed Mean ( 39 / 40 ) 101.485714285714 0.307580786033443 329.948159618397 Trimmed Mean ( 40 / 40 ) 101.4575 0.299355879026440 338.919350206044 Median 101.15 Midrange 104.7 Midmean - Weighted Average at Xnp 101.601639344262 Midmean - Weighted Average at X(n+1)p 101.666666666667 Midmean - Empirical Distribution Function 101.601639344262 Midmean - Empirical Distribution Function - Averaging 101.666666666667 Midmean - Empirical Distribution Function - Interpolation 101.666666666667 Midmean - Closest Observation 101.601639344262 Midmean - True Basic - Statistics Graphics Toolkit 101.666666666667 Midmean - MS Excel (old versions) 101.687096774194 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293467104hnnb9luz87j68ro/1wwma1293467203.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293467104hnnb9luz87j68ro/1wwma1293467203.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293467104hnnb9luz87j68ro/27nld1293467203.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293467104hnnb9luz87j68ro/27nld1293467203.ps (open in new window)

Parameters (Session):

par1 = grey ;

Parameters (R input):

par1 = grey ;

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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

• personalize online software applications according to your needs
• enforce strict security rules with respect to the data that you upload (e.g. statistical data)
• manage user sessions of online applications
• alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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