Tijdsreeks A - stap 14

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Fri, 06 Aug 2010 10:06:02 +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/Aug/06/t1281089166vjsye9swiwki47u.htm/, Retrieved Fri, 06 Aug 2010 12:06:06 +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/Aug/06/t1281089166vjsye9swiwki47u.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:

Gosselin Claudia

Dataseries X:

» Textbox « » Textfile « » CSV «

155 154 153 151 171 170 155 145 146 146 147 149 146 155 149 140 155 152 137 127 134 125 132 141 133 143 141 132 144 140 130 122 124 119 128 131 121 123 116 109 116 109 103 98 95 83 92 94 76 75 77 68 80 66 69 67 68 64 72 70 55 55 54 55 67 54 57 53 49 47 64 58 38 41 38 41 60 49 53 55 56 52 68 68 41 46 41 47 62 48 53 61 59 46 69 69 42 42 42 50 64 47 51 66 64 49 71 68 39 30 22 33 46 24 27 45 38 18 36 31

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 85.0583333333333 3.90351590123867 21.7901849218399 Geometric Mean 74.403696749972 Harmonic Mean 64.5469574728297 Quadratic Mean 95.1218954815346 Winsorized Mean ( 1 / 40 ) 85.0833333333333 3.89730897845887 21.8313030359164 Winsorized Mean ( 2 / 40 ) 84.8666666666667 3.85078720413155 22.0387838038966 Winsorized Mean ( 3 / 40 ) 84.9416666666667 3.84105231542381 22.1141655180228 Winsorized Mean ( 4 / 40 ) 85.0416666666667 3.82867325743939 22.2117848529969 Winsorized Mean ( 5 / 40 ) 85.0833333333333 3.82368014857651 22.2516868637687 Winsorized Mean ( 6 / 40 ) 85.1333333333333 3.80433435052795 22.3779840280124 Winsorized Mean ( 7 / 40 ) 85.25 3.77583073761307 22.5778129169772 Winsorized Mean ( 8 / 40 ) 85.3166666666667 3.75145132201862 22.7423094006078 Winsorized Mean ( 9 / 40 ) 85.2416666666667 3.74030953034903 22.7900033339519 Winsorized Mean ( 10 / 40 ) 85.075 3.71595022362057 22.8945477953977 Winsorized Mean ( 11 / 40 ) 85.1666666666667 3.70627322942699 22.979057774387 Winsorized Mean ( 12 / 40 ) 85.1666666666667 3.6569708832698 23.2888555542769 Winsorized Mean ( 13 / 40 ) 85.0583333333333 3.64165705182406 23.3570410730271 Winsorized Mean ( 14 / 40 ) 85.0583333333333 3.64165705182406 23.3570410730271 Winsorized Mean ( 15 / 40 ) 85.0583333333333 3.64165705182406 23.3570410730271 Winsorized Mean ( 16 / 40 ) 85.0583333333333 3.60951698455782 23.5650181720237 Winsorized Mean ( 17 / 40 ) 84.9166666666667 3.58983515404816 23.6547537763422 Winsorized Mean ( 18 / 40 ) 84.7666666666667 3.56917893667149 23.749626502536 Winsorized Mean ( 19 / 40 ) 84.925 3.47919310528541 24.4093953483025 Winsorized Mean ( 20 / 40 ) 85.0916666666667 3.4632523822979 24.5698716910165 Winsorized Mean ( 21 / 40 ) 84.9166666666667 3.43960666708802 24.6879003576759 Winsorized Mean ( 22 / 40 ) 84.9166666666667 3.43960666708802 24.6879003576759 Winsorized Mean ( 23 / 40 ) 84.5333333333333 3.34485962351592 25.2726101684581 Winsorized Mean ( 24 / 40 ) 83.9333333333333 3.26666666666667 25.6938775510204 Winsorized Mean ( 25 / 40 ) 83.725 3.23993728757996 25.8415495636144 Winsorized Mean ( 26 / 40 ) 83.725 3.19181293592328 26.2311738440841 Winsorized Mean ( 27 / 40 ) 83.95 3.17081071908219 26.4758787065978 Winsorized Mean ( 28 / 40 ) 83.7166666666667 3.14119603203483 26.6512073149526 Winsorized Mean ( 29 / 40 ) 83.475 3.11072425524296 26.8345867877255 Winsorized Mean ( 30 / 40 ) 83.225 3.02502314966719 27.512186149437 Winsorized Mean ( 31 / 40 ) 83.225 2.96925097129431 28.0289543742144 Winsorized Mean ( 32 / 40 ) 82.9583333333333 2.87927968722623 28.8121830266693 Winsorized Mean ( 33 / 40 ) 82.9583333333333 2.82090028324822 29.4084600671557 Winsorized Mean ( 34 / 40 ) 82.675 2.78635034575692 29.671430272901 Winsorized Mean ( 35 / 40 ) 82.3833333333333 2.75096579255057 29.9470584317776 Winsorized Mean ( 36 / 40 ) 82.3833333333333 2.68792776110636 30.6493851975487 Winsorized Mean ( 37 / 40 ) 81.7666666666667 2.61378947599775 31.2828050680915 Winsorized Mean ( 38 / 40 ) 81.1333333333333 2.47242306594027 32.8153116070684 Winsorized Mean ( 39 / 40 ) 81.1333333333333 2.47242306594027 32.8153116070684 Winsorized Mean ( 40 / 40 ) 78.8 2.19933144922029 35.8290697966131 Trimmed Mean ( 1 / 40 ) 84.8983050847458 3.86000846350528 21.994331330468 Trimmed Mean ( 2 / 40 ) 84.7068965517241 3.81842407348953 22.1837320636608 Trimmed Mean ( 3 / 40 ) 84.6228070175439 3.79855647066224 22.2776224787283 Trimmed Mean ( 4 / 40 ) 84.5089285714286 3.77964463508431 22.3589614184836 Trimmed Mean ( 5 / 40 ) 84.3636363636364 3.76163698489452 22.4273731629109 Trimmed Mean ( 6 / 40 ) 84.2037037037037 3.74204496625399 22.502055550657 Trimmed Mean ( 7 / 40 ) 84.0283018867924 3.72361535731483 22.5663216587942 Trimmed Mean ( 8 / 40 ) 83.8269230769231 3.70763201494831 22.6092888234195 Trimmed Mean ( 9 / 40 ) 83.607843137255 3.69298781092038 22.6396206589206 Trimmed Mean ( 10 / 40 ) 83.39 3.67730948527657 22.6769055837921 Trimmed Mean ( 11 / 40 ) 83.1836734693878 3.66238655905801 22.7129692969338 Trimmed Mean ( 12 / 40 ) 82.9583333333333 3.64571115083486 22.7550483022595 Trimmed Mean ( 13 / 40 ) 82.7234042553192 3.6324626324118 22.7733668936312 Trimmed Mean ( 14 / 40 ) 82.4891304347826 3.61816746785195 22.7985938096323 Trimmed Mean ( 15 / 40 ) 82.2444444444444 3.60050319382123 22.8424861795937 Trimmed Mean ( 16 / 40 ) 81.9886363636364 3.57898977292732 22.9083181471559 Trimmed Mean ( 17 / 40 ) 81.7209302325581 3.55706465171327 22.9742605868007 Trimmed Mean ( 18 / 40 ) 81.452380952381 3.53307480037006 23.0542475194268 Trimmed Mean ( 19 / 40 ) 81.1829268292683 3.50674182054499 23.150528605682 Trimmed Mean ( 20 / 40 ) 80.8875 3.48559393945415 23.2062315361574 Trimmed Mean ( 21 / 40 ) 80.5641025641026 3.4610524936065 23.2773419972469 Trimmed Mean ( 22 / 40 ) 80.2368421052632 3.43382904381155 23.3665803048251 Trimmed Mean ( 23 / 40 ) 79.8918918918919 3.40027263142235 23.495731240372 Trimmed Mean ( 24 / 40 ) 79.5555555555556 3.37143069759777 23.596971936051 Trimmed Mean ( 25 / 40 ) 79.2428571428571 3.34598648451688 23.6829579287134 Trimmed Mean ( 26 / 40 ) 78.9264705882353 3.31737359862161 23.7918546831836 Trimmed Mean ( 27 / 40 ) 78.5909090909091 3.28725569595605 23.9077566091348 Trimmed Mean ( 28 / 40 ) 78.21875 3.2512565298385 24.0580062760798 Trimmed Mean ( 29 / 40 ) 77.8387096774194 3.21009393830591 24.2481096109287 Trimmed Mean ( 30 / 40 ) 77.45 3.16276223762575 24.4880880006146 Trimmed Mean ( 31 / 40 ) 77.051724137931 3.11567883065591 24.7303166744276 Trimmed Mean ( 32 / 40 ) 76.625 3.06367092643034 25.0108454334814 Trimmed Mean ( 33 / 40 ) 76.1851851851852 3.0112848636008 25.2998931140926 Trimmed Mean ( 34 / 40 ) 75.7115384615385 2.95240482015382 25.6440234566457 Trimmed Mean ( 35 / 40 ) 75.22 2.88221711711732 26.0979644986746 Trimmed Mean ( 36 / 40 ) 74.7083333333333 2.79769382188977 26.7035415915777 Trimmed Mean ( 37 / 40 ) 74.1521739130435 2.69835652097786 27.4804953817487 Trimmed Mean ( 38 / 40 ) 73.5909090909091 2.58478189481868 28.4708389665007 Trimmed Mean ( 39 / 40 ) 73.0238095238095 2.46732140333628 29.5963912221033 Trimmed Mean ( 40 / 40 ) 72.4 2.30601220892091 31.3961911042437 Median 68 Midrange 94.5 Midmean - Weighted Average at Xnp 76.0952380952381 Midmean - Weighted Average at X(n+1)p 77.45 Midmean - Empirical Distribution Function 76.0952380952381 Midmean - Empirical Distribution Function - Averaging 77.45 Midmean - Empirical Distribution Function - Interpolation 77.45 Midmean - Closest Observation 76.0952380952381 Midmean - True Basic - Statistics Graphics Toolkit 77.45 Midmean - MS Excel (old versions) 76.9375 Number of observations 120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281089166vjsye9swiwki47u/1m6ez1281089158.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/06/t1281089166vjsye9swiwki47u/1m6ez1281089158.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/06/t1281089166vjsye9swiwki47u/2xgd31281089158.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/06/t1281089166vjsye9swiwki47u/2xgd31281089158.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

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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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