opdracht 5 oefening 2 stap 1

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 19 Oct 2010 09:44:26 +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/19/t1287481458gzt9uipzg1spkh7.htm/, Retrieved Tue, 19 Oct 2010 11:44:18 +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/19/t1287481458gzt9uipzg1spkh7.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 «

132,1 125 127,1 101,5 85,7 79,3 70,9 77,1 83,9 96,2 111,7 127,2 143,6 134,9 135,6 105,3 86,4 74,6 67,6 73,4 78,5 98,2 118,6 136,9 137,9 115,6 119,3 98,5 84,3 73,5 60,7 69,5 77,9 113,9 126,3 135,1 130,5 113,1 110 90,8 85,4 72,5 64,7 67,2 77,9 105,2 107,2 120,7 121,3 107,9 105,6 81,3 71,7 64,8 57,3 61,9 70,1 88,8 106,8 110,7 114,1 108 111,5 86,8 78,4 68 57,3 65,3 73,3 88,6 101,3 122,9 126,6 114,1 124,7 93,3 77,2 66,5 57,9 63,7 65,8 85 101 105,3 121 117,9 106 86,6 79,9 65,2 61,2 67,6 78,9 95,5 113,1 124,4 122 110,3 114 93,3 75,5 65,4 59,2 63,8 74,2 91,7 107 120,7 127,4 119,7 112,7 84,4 75,6 66,5 59,9 64,8 74,3 100,4 105,9 131,1

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 94.7575 2.1759449032521 43.5477478581274 Geometric Mean 91.7366196371463 Harmonic Mean 88.7452797413195 Quadratic Mean 97.6852978531911 Winsorized Mean ( 1 / 40 ) 94.71 2.16748715341616 43.6957607110742 Winsorized Mean ( 2 / 40 ) 94.7033333333333 2.16328574829082 43.7775422910067 Winsorized Mean ( 3 / 40 ) 94.7033333333333 2.1534539819294 43.9774121611289 Winsorized Mean ( 4 / 40 ) 94.71 2.14760155451955 44.1003592126697 Winsorized Mean ( 5 / 40 ) 94.735 2.14179060993523 44.2316814540824 Winsorized Mean ( 6 / 40 ) 94.62 2.11701410942294 44.6950256868112 Winsorized Mean ( 7 / 40 ) 94.6025 2.10304449928345 44.9835940381827 Winsorized Mean ( 8 / 40 ) 94.6825 2.08189059147544 45.4790950051311 Winsorized Mean ( 9 / 40 ) 94.4575 2.04842416118285 46.112275860609 Winsorized Mean ( 10 / 40 ) 94.5158333333333 2.03684478761692 46.4030611993345 Winsorized Mean ( 11 / 40 ) 94.5158333333333 2.03448353236492 46.4569173599878 Winsorized Mean ( 12 / 40 ) 94.4658333333334 2.02778960112563 46.5856187845599 Winsorized Mean ( 13 / 40 ) 94.4766666666667 2.01816739308643 46.8130973626431 Winsorized Mean ( 14 / 40 ) 94.3366666666667 1.99690830129282 47.2413613612563 Winsorized Mean ( 15 / 40 ) 94.3116666666667 1.99055690282394 47.3795381246675 Winsorized Mean ( 16 / 40 ) 94.325 1.97895200811444 47.6641169736469 Winsorized Mean ( 17 / 40 ) 94.2116666666667 1.94021973954544 48.5572148074007 Winsorized Mean ( 18 / 40 ) 94.0766666666667 1.92359801372169 48.9066145814174 Winsorized Mean ( 19 / 40 ) 94.0766666666667 1.89687924945724 49.5954957035799 Winsorized Mean ( 20 / 40 ) 94.0933333333333 1.88295194571678 49.9711814459051 Winsorized Mean ( 21 / 40 ) 94.0408333333333 1.8766662048922 50.1105807139183 Winsorized Mean ( 22 / 40 ) 94.1141666666667 1.86801745437525 50.3818454405944 Winsorized Mean ( 23 / 40 ) 94.21 1.81185653119552 51.9963906512164 Winsorized Mean ( 24 / 40 ) 94.25 1.78873615461094 52.6908341160578 Winsorized Mean ( 25 / 40 ) 94.2708333333333 1.75285696997489 53.7812468148408 Winsorized Mean ( 26 / 40 ) 94.2925 1.71594359244848 54.9508156415877 Winsorized Mean ( 27 / 40 ) 93.955 1.63738957119042 57.3809688623415 Winsorized Mean ( 28 / 40 ) 93.7916666666667 1.57856066027566 59.4159407534506 Winsorized Mean ( 29 / 40 ) 93.8158333333333 1.57592709623628 59.5305668373807 Winsorized Mean ( 30 / 40 ) 93.8158333333333 1.57050545657196 59.7360760134579 Winsorized Mean ( 31 / 40 ) 93.9708333333333 1.54818064174904 60.6975896734964 Winsorized Mean ( 32 / 40 ) 93.7841666666666 1.5224031919167 61.6027128454667 Winsorized Mean ( 33 / 40 ) 93.8666666666666 1.51355422936503 62.0173792557443 Winsorized Mean ( 34 / 40 ) 94.0083333333333 1.47437475868189 63.7614912896216 Winsorized Mean ( 35 / 40 ) 93.7458333333333 1.44047868630707 65.079639306339 Winsorized Mean ( 36 / 40 ) 94.1358333333333 1.3871306235223 67.8637121385852 Winsorized Mean ( 37 / 40 ) 93.92 1.35816423308583 69.1521671032437 Winsorized Mean ( 38 / 40 ) 94.015 1.32221466133312 71.1041881090697 Winsorized Mean ( 39 / 40 ) 93.9175 1.31214786526067 71.5753936629259 Winsorized Mean ( 40 / 40 ) 93.4175 1.22738458384757 76.1110260218176 Trimmed Mean ( 1 / 40 ) 94.6610169491525 2.15006814721355 44.0269844803902 Trimmed Mean ( 2 / 40 ) 94.6103448275862 2.13060316202912 44.4054277744909 Trimmed Mean ( 3 / 40 ) 94.561403508772 2.11125487729919 44.7891936333803 Trimmed Mean ( 4 / 40 ) 94.5107142857143 2.09348185470279 45.1452273509826 Trimmed Mean ( 5 / 40 ) 94.4563636363636 2.0753043838658 45.5144625389427 Trimmed Mean ( 6 / 40 ) 94.3944444444444 2.05632012667454 45.9045472638048 Trimmed Mean ( 7 / 40 ) 94.3518867924528 2.04047597248961 46.2401361567287 Trimmed Mean ( 8 / 40 ) 94.310576923077 2.02524439478443 46.5675042310712 Trimmed Mean ( 9 / 40 ) 94.2558823529412 2.01165096644828 46.8549882285778 Trimmed Mean ( 10 / 40 ) 94.229 2.00159900473536 47.0768619374181 Trimmed Mean ( 11 / 40 ) 94.1938775510204 1.99157113838706 47.2962656143463 Trimmed Mean ( 12 / 40 ) 94.1572916666667 1.98008824054197 47.5520685082675 Trimmed Mean ( 13 / 40 ) 94.1244680851064 1.96755755727272 47.8382285373011 Trimmed Mean ( 14 / 40 ) 94.0891304347826 1.95416754633377 48.1479341990425 Trimmed Mean ( 15 / 40 ) 94.0655555555556 1.94128557036199 48.455290139521 Trimmed Mean ( 16 / 40 ) 94.0431818181818 1.92689592033724 48.8055326837387 Trimmed Mean ( 17 / 40 ) 94.0186046511628 1.91140683581628 49.1881701422352 Trimmed Mean ( 18 / 40 ) 94.002380952381 1.89798181924994 49.5275455217635 Trimmed Mean ( 19 / 40 ) 93.9963414634146 1.88398969713953 49.892173829894 Trimmed Mean ( 20 / 40 ) 93.99 1.87047733026572 50.2492056327931 Trimmed Mean ( 21 / 40 ) 93.9820512820513 1.8558488543868 50.6410050904194 Trimmed Mean ( 22 / 40 ) 93.9776315789474 1.83894763830725 51.1040279893198 Trimmed Mean ( 23 / 40 ) 93.9675675675676 1.81966113190892 51.6401465744289 Trimmed Mean ( 24 / 40 ) 93.95 1.80343091558636 52.0951477475663 Trimmed Mean ( 25 / 40 ) 93.9285714285714 1.7864571539697 52.578127171901 Trimmed Mean ( 26 / 40 ) 93.9044117647059 1.77012873078342 53.0494817307135 Trimmed Mean ( 27 / 40 ) 93.8772727272727 1.75456088378061 53.504710833968 Trimmed Mean ( 28 / 40 ) 93.871875 1.74502050738109 53.7941385805729 Trimmed Mean ( 29 / 40 ) 93.8774193548387 1.73962501255863 53.9641696785932 Trimmed Mean ( 30 / 40 ) 93.8816666666667 1.73182000158526 54.2098293013881 Trimmed Mean ( 31 / 40 ) 93.8862068965517 1.72145362728729 54.5389114224936 Trimmed Mean ( 32 / 40 ) 93.8803571428572 1.71025444230417 54.8926258109145 Trimmed Mean ( 33 / 40 ) 93.887037037037 1.69845172701986 55.2780132301866 Trimmed Mean ( 34 / 40 ) 93.8884615384615 1.68336205158847 55.7743721559277 Trimmed Mean ( 35 / 40 ) 93.88 1.66879890817269 56.2560291358275 Trimmed Mean ( 36 / 40 ) 93.8895833333333 1.65393159248447 56.7675130942365 Trimmed Mean ( 37 / 40 ) 93.8717391304348 1.64173133262907 57.1785025142381 Trimmed Mean ( 38 / 40 ) 93.8681818181818 1.6285792350428 57.6380809716726 Trimmed Mean ( 39 / 40 ) 93.8571428571429 1.61531269687253 58.1046276915071 Trimmed Mean ( 40 / 40 ) 93.8525 1.59684780635684 58.7736036123075 Median 93.3 Midrange 100.45 Midmean - Weighted Average at Xnp 93.5459016393443 Midmean - Weighted Average at X(n+1)p 93.8816666666667 Midmean - Empirical Distribution Function 93.5459016393443 Midmean - Empirical Distribution Function - Averaging 93.8816666666667 Midmean - Empirical Distribution Function - Interpolation 93.8816666666667 Midmean - Closest Observation 93.5459016393443 Midmean - True Basic - Statistics Graphics Toolkit 93.8816666666667 Midmean - MS Excel (old versions) 94.1984126984127 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/19/t1287481458gzt9uipzg1spkh7/1m4dc1287481461.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/19/t1287481458gzt9uipzg1spkh7/1m4dc1287481461.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/19/t1287481458gzt9uipzg1spkh7/2eduf1287481461.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/19/t1287481458gzt9uipzg1spkh7/2eduf1287481461.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.

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