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central tendency totaal G29

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

Title produced by software: Central Tendency

Date of computation: Sat, 08 Dec 2007 05:35:27 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/08/t11971165033qa7bvj0roewtmm.htm/, Retrieved Sat, 08 Dec 2007 13:21:43 +0100

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Dataseries X:

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153,4 159,5 157,4 169,1 172,6 161,7 159,2 157,4 153,9 144,8 142,2 140,1 143,4 153,3 166,9 170,6 182,8 170,3 156,6 155,2 154,7 151,6 152,1 153,2 149,5 149,7 144,3 140 137,8 132,2 128,9 123,1 120,4 122,8 126 124,5 120,6 114,7 111,7 109,1 108 107,7 99,9 103,7 103,4 103,4 104,7 105,8 105,3 103 103,8 103,4 105,8 101,4 97 94,3 96,6 97,1 95,7 96,9 97,4 95,3 93,6 91,5 93,1 91,7 94,3 93,9 90,9 88,3 91,3 91,7 92,4 92 95,6 95,8 96,4 99 107 109,7 116,2 115,9 113,8 112,6 113,7 115,9 110,3 111,3 113,4 108,2 104,8 106 110,9 115 118,4 121,4 128,8 131,7 141,7 142,9 139,4 134,7 125 113,6 111,5 108,5 112,3 116,6 115,5 120,1 132,9 128,1 129,3 132,5 131 124,9 120,8 122 122,1 127,4 135,2 137,3 135 136 138,4 134,7 138,4 133,9 133,6 141,2 151,8 155,4 156,6 161,6 160,7 156 159,5 168,7 169,9 169,9 185,9

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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 4 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 125.928368794326 2.05186655484876 61.3725919440254 Geometric Mean 123.637560644502 Harmonic Mean 121.419074567177 Quadratic Mean 128.247323392915 Winsorized Mean ( 1 / 47 ) 125.924822695035 2.04505189179892 61.5753679405497 Winsorized Mean ( 2 / 47 ) 125.785815602837 2.01798513714519 62.3323796035406 Winsorized Mean ( 3 / 47 ) 125.747517730496 2.01055033410202 62.5438297154892 Winsorized Mean ( 4 / 47 ) 125.744680851064 2.00850936110069 62.6059720140683 Winsorized Mean ( 5 / 47 ) 125.730496453901 2.00627029831252 62.6687722784179 Winsorized Mean ( 6 / 47 ) 125.743262411348 2.00472954083062 62.7233049896836 Winsorized Mean ( 7 / 47 ) 125.723404255319 1.99614512954711 62.9830979693562 Winsorized Mean ( 8 / 47 ) 125.740425531915 1.98793523618499 63.251771608627 Winsorized Mean ( 9 / 47 ) 125.657446808511 1.96673223854141 63.8914867748862 Winsorized Mean ( 10 / 47 ) 125.309929078014 1.91151427768772 65.5553194348078 Winsorized Mean ( 11 / 47 ) 125.333333333333 1.90680875332305 65.7293675178023 Winsorized Mean ( 12 / 47 ) 125.256737588652 1.89649313890171 66.046501840334 Winsorized Mean ( 13 / 47 ) 125.238297872340 1.87122877333654 66.9283733004121 Winsorized Mean ( 14 / 47 ) 125.268085106383 1.8678369610376 67.0658562387563 Winsorized Mean ( 15 / 47 ) 125.246808510638 1.86246384764393 67.2479139227744 Winsorized Mean ( 16 / 47 ) 125.053900709220 1.83501420166012 68.1487372664936 Winsorized Mean ( 17 / 47 ) 125.126241134752 1.8268327171595 68.4935407382607 Winsorized Mean ( 18 / 47 ) 125.049645390071 1.81116866672453 69.0436223238234 Winsorized Mean ( 19 / 47 ) 125.090070921986 1.80664800280605 69.2387619102881 Winsorized Mean ( 20 / 47 ) 125.019148936170 1.79451768824612 69.6672703507083 Winsorized Mean ( 21 / 47 ) 124.944680851064 1.78189118525261 70.1191418898852 Winsorized Mean ( 22 / 47 ) 124.960283687943 1.77287420813918 70.4845742096402 Winsorized Mean ( 23 / 47 ) 125.139716312057 1.73439777524906 72.1516817525247 Winsorized Mean ( 24 / 47 ) 125.156737588652 1.70152512342842 73.5556212866684 Winsorized Mean ( 25 / 47 ) 125.334042553191 1.66305946922032 75.3635362251665 Winsorized Mean ( 26 / 47 ) 125.610638297872 1.63105335837921 77.0119736749094 Winsorized Mean ( 27 / 47 ) 125.668085106383 1.62118113944073 77.5163749744432 Winsorized Mean ( 28 / 47 ) 125.449645390071 1.59489453431762 78.657016304683 Winsorized Mean ( 29 / 47 ) 125.387943262411 1.58754603286371 78.9822409346009 Winsorized Mean ( 30 / 47 ) 125.409219858156 1.57619509690097 79.5645285946702 Winsorized Mean ( 31 / 47 ) 125.013475177305 1.52507153314654 81.9722042279395 Winsorized Mean ( 32 / 47 ) 125.172340425532 1.49971125433731 83.4642935855293 Winsorized Mean ( 33 / 47 ) 124.095744680851 1.37428654137774 90.2983045707802 Winsorized Mean ( 34 / 47 ) 124.095744680851 1.34930687761914 91.9699934382749 Winsorized Mean ( 35 / 47 ) 123.996453900709 1.31325192147889 94.4193965169098 Winsorized Mean ( 36 / 47 ) 123.868794326241 1.29983988365981 95.295425139193 Winsorized Mean ( 37 / 47 ) 123.737588652482 1.27552620963115 97.0090521999259 Winsorized Mean ( 38 / 47 ) 123.872340425532 1.23507589583520 100.295326662306 Winsorized Mean ( 39 / 47 ) 123.927659574468 1.20206598007298 103.095555176550 Winsorized Mean ( 40 / 47 ) 123.700709219858 1.16211014813880 106.444909217920 Winsorized Mean ( 41 / 47 ) 123.729787234043 1.15357764483166 107.257441914192 Winsorized Mean ( 42 / 47 ) 123.640425531915 1.12706502075817 109.701235735932 Winsorized Mean ( 43 / 47 ) 123.518439716312 1.07930359683488 114.442720360181 Winsorized Mean ( 44 / 47 ) 123.705673758865 1.06154709843616 116.533382212721 Winsorized Mean ( 45 / 47 ) 123.705673758865 1.02470139127766 120.723632086243 Winsorized Mean ( 46 / 47 ) 123.738297872340 0.990502855299827 124.924726072480 Winsorized Mean ( 47 / 47 ) 123.438297872340 0.936189359203676 131.851848836797 Trimmed Mean ( 1 / 47 ) 125.767625899281 2.01770399430658 62.3320498220566 Trimmed Mean ( 2 / 47 ) 125.605839416058 1.98778439030371 63.188864963804 Trimmed Mean ( 3 / 47 ) 125.511851851852 1.97039785805255 63.6987354299613 Trimmed Mean ( 4 / 47 ) 125.428571428571 1.95417966146137 64.1847696515139 Trimmed Mean ( 5 / 47 ) 125.343511450382 1.93692618058889 64.7125908599537 Trimmed Mean ( 6 / 47 ) 125.258914728682 1.91847328459515 65.2909351068264 Trimmed Mean ( 7 / 47 ) 125.169291338583 1.89845104630509 65.932324977353 Trimmed Mean ( 8 / 47 ) 125.08 1.8780281354174 66.6017711029662 Trimmed Mean ( 9 / 47 ) 124.985365853659 1.85689930095762 67.3086396172387 Trimmed Mean ( 10 / 47 ) 124.898347107438 1.83700520726068 67.9901976400409 Trimmed Mean ( 11 / 47 ) 124.849579831933 1.82333771539152 68.473096770844 Trimmed Mean ( 12 / 47 ) 124.796581196581 1.80869788834877 68.9980244907083 Trimmed Mean ( 13 / 47 ) 124.749565217391 1.79370727058791 69.5484526728281 Trimmed Mean ( 14 / 47 ) 124.702654867257 1.78012292904303 70.052833336794 Trimmed Mean ( 15 / 47 ) 124.651351351351 1.76522735778604 70.6148988692823 Trimmed Mean ( 16 / 47 ) 124.6 1.74909859800372 71.2366930842027 Trimmed Mean ( 17 / 47 ) 124.56261682243 1.73416686810717 71.8285068831865 Trimmed Mean ( 18 / 47 ) 124.518095238095 1.71818424738775 72.4707466195242 Trimmed Mean ( 19 / 47 ) 124.477669902913 1.70185726925971 73.1422500296158 Trimmed Mean ( 20 / 47 ) 124.432673267327 1.68382350672621 73.8988811893096 Trimmed Mean ( 21 / 47 ) 124.390909090909 1.66471505458578 74.7220425190789 Trimmed Mean ( 22 / 47 ) 124.352577319588 1.64440965183781 75.6214105047423 Trimmed Mean ( 23 / 47 ) 124.311578947368 1.62229211931712 76.6271237264567 Trimmed Mean ( 24 / 47 ) 124.256989247312 1.60125914533314 77.5995500849806 Trimmed Mean ( 25 / 47 ) 124.198901098901 1.58077467794465 78.5683771582089 Trimmed Mean ( 26 / 47 ) 124.126966292135 1.56133599261364 79.5004834829623 Trimmed Mean ( 27 / 47 ) 124.034482758621 1.54217448170218 80.4283070627114 Trimmed Mean ( 28 / 47 ) 123.934117647059 1.52096419453836 81.4839153295618 Trimmed Mean ( 29 / 47 ) 123.842168674699 1.49941326607050 82.5937528212293 Trimmed Mean ( 30 / 47 ) 123.749382716049 1.47517013400128 83.8882104943307 Trimmed Mean ( 31 / 47 ) 123.650632911392 1.44816851889870 85.3841464565368 Trimmed Mean ( 32 / 47 ) 123.570129870130 1.42299380301336 86.8381363351372 Trimmed Mean ( 33 / 47 ) 123.476 1.39630637594172 88.4304491675213 Trimmed Mean ( 34 / 47 ) 123.439726027397 1.38052024545834 89.4153681798523 Trimmed Mean ( 35 / 47 ) 123.401408450704 1.36445018880772 90.4403909083225 Trimmed Mean ( 36 / 47 ) 123.366666666667 1.3493496691725 91.426758745435 Trimmed Mean ( 37 / 47 ) 123.337313432836 1.33260411281353 92.5536040650762 Trimmed Mean ( 38 / 47 ) 123.313846153846 1.31525055547171 93.7569238354134 Trimmed Mean ( 39 / 47 ) 123.280952380952 1.29910532280811 94.896811071847 Trimmed Mean ( 40 / 47 ) 123.242622950820 1.28336447130572 96.0308826575436 Trimmed Mean ( 41 / 47 ) 123.215254237288 1.26910372926106 97.0884029385295 Trimmed Mean ( 42 / 47 ) 123.184210526316 1.25210546858949 98.3816568304618 Trimmed Mean ( 43 / 47 ) 123.156363636364 1.23442420671761 99.7682668293116 Trimmed Mean ( 44 / 47 ) 123.133962264151 1.21906107066954 101.007213852316 Trimmed Mean ( 45 / 47 ) 123.098039215686 1.20165405675931 102.440497348850 Trimmed Mean ( 46 / 47 ) 123.059183673469 1.18488897829240 103.857142675777 Trimmed Mean ( 47 / 47 ) 123.014893617021 1.16838154592122 105.286577014557 Median 122.1 Midrange 137.1 Midmean - Weighted Average at Xnp 123.115714285714 Midmean - Weighted Average at X(n+1)p 123.401408450704 Midmean - Empirical Distribution Function 123.401408450704 Midmean - Empirical Distribution Function - Averaging 123.401408450704 Midmean - Empirical Distribution Function - Interpolation 123.401408450704 Midmean - Closest Observation 123.15 Midmean - True Basic - Statistics Graphics Toolkit 123.401408450704 Midmean - MS Excel (old versions) 123.401408450704 Number of observations 141

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/08/t11971165033qa7bvj0roewtmm/14mpt1197117321.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/08/t11971165033qa7bvj0roewtmm/14mpt1197117321.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/08/t11971165033qa7bvj0roewtmm/2nw5p1197117321.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/08/t11971165033qa7bvj0roewtmm/2nw5p1197117321.ps (open in new window)

Parameters:

R code (references can be found in the software module):

geomean <- function(x) { return(exp(mean(log(x)))) } harmean <- function(x) { return(1/mean(1/x)) } quamean <- function(x) { return(sqrt(mean(x*x))) } winmean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) win <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn } return(win) } trimean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) tri <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { tri[j,1] <- mean(x,trim=j/n) tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2) } return(tri) } midrange <- function(x) { return((max(x)+min(x))/2) } q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } midmean <- function(x,def) { x <-sort(x[!is.na(x)]) n<-length(x) if (def==1) { qvalue1 <- q1(x,n,0.25,i,f) qvalue3 <- q1(x,n,0.75,i,f) } if (def==2) { qvalue1 <- q2(x,n,0.25,i,f) qvalue3 <- q2(x,n,0.75,i,f) } if (def==3) { qvalue1 <- q3(x,n,0.25,i,f) qvalue3 <- q3(x,n,0.75,i,f) } if (def==4) { qvalue1 <- q4(x,n,0.25,i,f) qvalue3 <- q4(x,n,0.75,i,f) } if (def==5) { qvalue1 <- q5(x,n,0.25,i,f) qvalue3 <- q5(x,n,0.75,i,f) } if (def==6) { qvalue1 <- q6(x,n,0.25,i,f) qvalue3 <- q6(x,n,0.75,i,f) } if (def==7) { qvalue1 <- q7(x,n,0.25,i,f) qvalue3 <- q7(x,n,0.75,i,f) } if (def==8) { qvalue1 <- q8(x,n,0.25,i,f) qvalue3 <- q8(x,n,0.75,i,f) } midm <- 0 myn <- 0 roundno4 <- round(n/4) round3no4 <- round(3*n/4) for (i in 1:n) { if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){ midm = midm + x[i] myn = myn + 1 } } midm = midm / myn return(midm) } (arm <- mean(x)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') lb <- win[,1] - 2*win[,2] ub <- win[,1] + 2*win[,2] if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() bitmap(file='test2.png') lb <- tri[,1] - 2*tri[,2] ub <- tri[,1] + 2*tri[,2] if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Measure',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.element(a,'S.E.',header=TRUE) a<-table.element(a,'Value/S.E.',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE) a<-table.element(a,arm) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean')) a<-table.element(a,armose) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE) a<-table.element(a,geo) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE) a<-table.element(a,har) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE) a<-table.element(a,qua) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) for (j in 1:length(win[,1])) { a<-table.row.start(a) mylabel <- paste('Winsorized Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(win[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE) a<-table.element(a,win[j,1]) a<-table.element(a,win[j,2]) a<-table.element(a,win[j,1]/win[j,2]) a<-table.row.end(a) } for (j in 1:length(tri[,1])) { a<-table.row.start(a) mylabel <- paste('Trimmed Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(tri[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE) a<-table.element(a,tri[j,1]) a<-table.element(a,tri[j,2]) a<-table.element(a,tri[j,1]/tri[j,2]) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE) a<-table.element(a,median(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE) a<-table.element(a,midr) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[1]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[2]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[3]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[4]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[5]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[6]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[7]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[8]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of observations',header=TRUE) a<-table.element(a,length(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

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