centrummaten eigen reeks - Gaelle Wauters

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

Title produced by software: Central Tendency

Date of computation: Mon, 21 Apr 2008 08:46:11 -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/Apr/21/t12087892508ab0xeyd79xsd2e.htm/, Retrieved Mon, 21 Apr 2008 16:47:30 +0200

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

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 9,1 8,9 8,7 8,5 8,4 8,4 8,7 8,5 8,1 7,8 7,7 7,4 7,2 7 6,6 6,4 6,4 6,8 7,3 7 7 6,7 6,7 6,3 6,2 6 6,3 6,2 6,1 6,2 6,6 6,6 7,8 7,4 7,4 7,5 7,4 7,4 7 6,9 6,9 7,6 7,7 7,6 8,2 8 8,1 8,3 8,2 8,1 7,7 7,6 7,7 8,2 8,4 8,4 8,6 8,4 8,5 8,7 8,7 8,6 7,4 7,3 7,4 9 9,2 9,2 8,5 8,3 8,3 8,6 8,6 8,5 8,1 8,1 8 8,6 8,7 8,7 8,6 8,4 8,4 8,7 8,7 8,5 8,3 8,3 8,3 8,1 8,2 8,1 8,1 7,9 7,7 8,1 8 7,7 7,8 7,6 7,4 7,3 7,4 7,1 7,3 7,1 7,1

Text written by user:

Output produced by software:

Summary of compuational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 8.30705128205128 0.0823562847266949 100.86724176083 Geometric Mean 8.24139975538978 Harmonic Mean 8.17340849761853 Quadratic Mean 8.37008945208457 Winsorized Mean ( 1 / 52 ) 8.30705128205128 0.0821501388297642 101.120355977311 Winsorized Mean ( 2 / 52 ) 8.30705128205128 0.0817565237807802 101.607197785532 Winsorized Mean ( 3 / 52 ) 8.30705128205128 0.0817565237807802 101.607197785532 Winsorized Mean ( 4 / 52 ) 8.30705128205128 0.0817565237807802 101.607197785532 Winsorized Mean ( 5 / 52 ) 8.30705128205128 0.08081528417775 102.790596686887 Winsorized Mean ( 6 / 52 ) 8.30705128205128 0.08081528417775 102.790596686887 Winsorized Mean ( 7 / 52 ) 8.31153846153846 0.0801103536773119 103.751114306869 Winsorized Mean ( 8 / 52 ) 8.30641025641026 0.0794713690618327 104.520789744385 Winsorized Mean ( 9 / 52 ) 8.31794871794872 0.0777553541755619 106.975896465828 Winsorized Mean ( 10 / 52 ) 8.31794871794872 0.0777553541755619 106.975896465828 Winsorized Mean ( 11 / 52 ) 8.31794871794872 0.0777553541755619 106.975896465828 Winsorized Mean ( 12 / 52 ) 8.32564102564102 0.076680898065288 108.575163250597 Winsorized Mean ( 13 / 52 ) 8.31730769230769 0.0756726847710712 109.911624220412 Winsorized Mean ( 14 / 52 ) 8.32628205128205 0.0744603534404767 111.821683171811 Winsorized Mean ( 15 / 52 ) 8.33589743589744 0.0732160242144933 113.853456607759 Winsorized Mean ( 16 / 52 ) 8.32564102564102 0.0720138748858344 115.611623993847 Winsorized Mean ( 17 / 52 ) 8.33653846153846 0.070652673551336 117.993248415167 Winsorized Mean ( 18 / 52 ) 8.33653846153846 0.070652673551336 117.993248415167 Winsorized Mean ( 19 / 52 ) 8.32435897435897 0.0692830577895358 120.149993951570 Winsorized Mean ( 20 / 52 ) 8.32435897435897 0.0692830577895358 120.149993951570 Winsorized Mean ( 21 / 52 ) 8.33782051282051 0.067658113371403 123.234599626667 Winsorized Mean ( 22 / 52 ) 8.33782051282051 0.067658113371403 123.234599626667 Winsorized Mean ( 23 / 52 ) 8.32307692307692 0.0660653995465287 125.982389877399 Winsorized Mean ( 24 / 52 ) 8.33846153846154 0.064266952161797 129.747269132490 Winsorized Mean ( 25 / 52 ) 8.35448717948718 0.0624780719098827 133.718710006569 Winsorized Mean ( 26 / 52 ) 8.35448717948718 0.0624780719098827 133.718710006569 Winsorized Mean ( 27 / 52 ) 8.33717948717949 0.0606568535818494 137.448268330131 Winsorized Mean ( 28 / 52 ) 8.33717948717949 0.0606568535818494 137.448268330131 Winsorized Mean ( 29 / 52 ) 8.35576923076923 0.0586534902157365 142.459880904537 Winsorized Mean ( 30 / 52 ) 8.35576923076923 0.0586534902157365 142.459880904537 Winsorized Mean ( 31 / 52 ) 8.33589743589743 0.0566426897988601 147.166341596744 Winsorized Mean ( 32 / 52 ) 8.33589743589744 0.0566426897988601 147.166341596744 Winsorized Mean ( 33 / 52 ) 8.33589743589744 0.0566426897988601 147.166341596744 Winsorized Mean ( 34 / 52 ) 8.33589743589744 0.0566426897988601 147.166341596744 Winsorized Mean ( 35 / 52 ) 8.33589743589744 0.0566426897988601 147.166341596744 Winsorized Mean ( 36 / 52 ) 8.33589743589744 0.0566426897988601 147.166341596744 Winsorized Mean ( 37 / 52 ) 8.33589743589744 0.0566426897988601 147.166341596744 Winsorized Mean ( 38 / 52 ) 8.36025641025641 0.0540936256576531 154.551600278500 Winsorized Mean ( 39 / 52 ) 8.36025641025641 0.0490916622710237 170.298906647352 Winsorized Mean ( 40 / 52 ) 8.36025641025641 0.0490916622710237 170.298906647352 Winsorized Mean ( 41 / 52 ) 8.36025641025641 0.0490916622710237 170.298906647352 Winsorized Mean ( 42 / 52 ) 8.36025641025641 0.0490916622710237 170.298906647352 Winsorized Mean ( 43 / 52 ) 8.38782051282051 0.0463947794180793 180.792335215887 Winsorized Mean ( 44 / 52 ) 8.35961538461538 0.0436617842390745 191.462981421956 Winsorized Mean ( 45 / 52 ) 8.35961538461538 0.0436617842390745 191.462981421956 Winsorized Mean ( 46 / 52 ) 8.35961538461538 0.0436617842390745 191.462981421956 Winsorized Mean ( 47 / 52 ) 8.35961538461538 0.0436617842390745 191.462981421956 Winsorized Mean ( 48 / 52 ) 8.35961538461538 0.0436617842390745 191.462981421956 Winsorized Mean ( 49 / 52 ) 8.35961538461538 0.0376828746995156 221.84123295463 Winsorized Mean ( 50 / 52 ) 8.35961538461538 0.0376828746995156 221.84123295463 Winsorized Mean ( 51 / 52 ) 8.32692307692308 0.0347309897522327 239.754845350694 Winsorized Mean ( 52 / 52 ) 8.32692307692308 0.0286207071012604 290.940508473893 Trimmed Mean ( 1 / 52 ) 8.30974025974026 0.0811322216056393 102.422195464233 Trimmed Mean ( 2 / 52 ) 8.3125 0.0800308873146105 103.866148170051 Trimmed Mean ( 3 / 52 ) 8.31533333333333 0.0790589883509479 105.178848183853 Trimmed Mean ( 4 / 52 ) 8.31824324324324 0.0780050792595862 106.637200066956 Trimmed Mean ( 5 / 52 ) 8.32123287671233 0.0768610012526898 108.263394193308 Trimmed Mean ( 6 / 52 ) 8.32430555555556 0.0758546649457656 109.740192795094 Trimmed Mean ( 7 / 52 ) 8.3274647887324 0.0747595911577912 111.389918801937 Trimmed Mean ( 8 / 52 ) 8.33 0.0737046409713759 113.018663278410 Trimmed Mean ( 9 / 52 ) 8.33333333333333 0.0726646955167412 114.682009937184 Trimmed Mean ( 10 / 52 ) 8.33529411764706 0.0718077302367095 116.077949966811 Trimmed Mean ( 11 / 52 ) 8.33731343283582 0.0708705636213284 117.641415657187 Trimmed Mean ( 12 / 52 ) 8.33939393939394 0.0698446574123352 119.399167357375 Trimmed Mean ( 13 / 52 ) 8.34076923076923 0.0688667631878338 121.114581906802 Trimmed Mean ( 14 / 52 ) 8.34296875 0.0679212177674929 122.833026618568 Trimmed Mean ( 15 / 52 ) 8.34444444444444 0.0670328567201976 124.482900665789 Trimmed Mean ( 16 / 52 ) 8.34516129032258 0.0662030315245792 126.054065775285 Trimmed Mean ( 17 / 52 ) 8.34672131147541 0.0654229144699691 127.581007038547 Trimmed Mean ( 18 / 52 ) 8.3475 0.0647118424171311 128.994936447524 Trimmed Mean ( 19 / 52 ) 8.34830508474576 0.0639237224134381 130.597918418324 Trimmed Mean ( 20 / 52 ) 8.35 0.0631921939270456 132.136573856574 Trimmed Mean ( 21 / 52 ) 8.35175438596491 0.0623783704703097 133.888627147452 Trimmed Mean ( 22 / 52 ) 8.35267857142857 0.0616425718357847 135.501785903418 Trimmed Mean ( 23 / 52 ) 8.35363636363636 0.0608211432324226 137.347572236741 Trimmed Mean ( 24 / 52 ) 8.35555555555556 0.060061312467647 139.117099048683 Trimmed Mean ( 25 / 52 ) 8.3566037735849 0.0593922328155976 140.701963496316 Trimmed Mean ( 26 / 52 ) 8.35673076923077 0.0588152323734496 142.084464041039 Trimmed Mean ( 27 / 52 ) 8.35686274509804 0.0581623358959521 143.681690502387 Trimmed Mean ( 28 / 52 ) 8.358 0.0575980499108724 145.109079438162 Trimmed Mean ( 29 / 52 ) 8.35918367346939 0.0569554499533592 146.767055309276 Trimmed Mean ( 30 / 52 ) 8.359375 0.0564206111438196 148.161723712837 Trimmed Mean ( 31 / 52 ) 8.359375 0.0558071152161938 149.790487603887 Trimmed Mean ( 32 / 52 ) 8.36086956521739 0.0552965449876894 151.200578030305 Trimmed Mean ( 33 / 52 ) 8.36222222222222 0.0547056081676112 152.858591693221 Trimmed Mean ( 34 / 52 ) 8.36363636363636 0.0540226600686503 154.817188805737 Trimmed Mean ( 35 / 52 ) 8.36511627906977 0.0532337961283415 157.139202676854 Trimmed Mean ( 36 / 52 ) 8.36666666666667 0.0523222432165087 159.906497740273 Trimmed Mean ( 37 / 52 ) 8.36829268292683 0.0512675245639836 163.227945060677 Trimmed Mean ( 38 / 52 ) 8.37 0.0500442841865765 167.251867741673 Trimmed Mean ( 39 / 52 ) 8.37051282051282 0.048935010771948 171.053662571404 Trimmed Mean ( 40 / 52 ) 8.37105263157895 0.0482251950410755 173.582556264396 Trimmed Mean ( 41 / 52 ) 8.37162162162162 0.0473871257833254 176.664473382503 Trimmed Mean ( 42 / 52 ) 8.37222222222222 0.0463968652068856 180.448014858119 Trimmed Mean ( 43 / 52 ) 8.37285714285714 0.0452241451739443 185.141302519989 Trimmed Mean ( 44 / 52 ) 8.37205882352941 0.0441903848723691 189.454308843647 Trimmed Mean ( 45 / 52 ) 8.37205882352941 0.0433205353817297 193.258433898772 Trimmed Mean ( 46 / 52 ) 8.3734375 0.0422719246379817 198.085078257269 Trimmed Mean ( 47 / 52 ) 8.3741935483871 0.041003765022404 204.229868740384 Trimmed Mean ( 48 / 52 ) 8.375 0.0394614164701485 212.232624906799 Trimmed Mean ( 49 / 52 ) 8.37586206896552 0.0375690809426729 222.945620675319 Trimmed Mean ( 50 / 52 ) 8.37678571428571 0.03630597527192 230.727467077975 Trimmed Mean ( 51 / 52 ) 8.37777777777778 0.0347363702832046 241.181727091058 Trimmed Mean ( 52 / 52 ) 8.38076923076923 0.0332999600888502 251.675053315615 Median 8.4 Midrange 8.1 Midmean - Weighted Average at Xnp 8.35949367088608 Midmean - Weighted Average at X(n+1)p 8.37051282051282 Midmean - Empirical Distribution Function 8.35949367088608 Midmean - Empirical Distribution Function - Averaging 8.37051282051282 Midmean - Empirical Distribution Function - Interpolation 8.37051282051282 Midmean - Closest Observation 8.35949367088608 Midmean - True Basic - Statistics Graphics Toolkit 8.37051282051282 Midmean - MS Excel (old versions) 8.4367816091954 Number of observations 156

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/21/t12087892508ab0xeyd79xsd2e/1xvzl1208789165.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/21/t12087892508ab0xeyd79xsd2e/1xvzl1208789165.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/21/t12087892508ab0xeyd79xsd2e/2923s1208789165.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/21/t12087892508ab0xeyd79xsd2e/2923s1208789165.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')

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.

FreeStatistics.org is powered by