Robuustheid - geboortes 1830-2007 - Nathalie Sysmans

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 06 Apr 2011 18:04:00 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Apr/06/t1302112938ll5hpptbszha5ij.htm/, Retrieved Wed, 06 Apr 2011 20:02:21 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

131676 135050 129070 137792 139762 142917 144198 142648 152170 136022 138142 138135 135027 132911 133976 137012 119610 118106 120383 133185 131416 134248 134397 127728 131837 125955 134187 143291 145074 149812 144668 147253 145568 155564 155872 156323 158010 155598 154785 157294 162938 157283 166074 169282 172552 174055 175409 173696 171283 173322 170717 174229 175339 173511 175839 173816 173990 174777 174819 176726 176199 180952 176663 182346 180605 182497 187856 190020 190108 193288 193230 199068 195076 191563 191067 186665 185508 184371 183046 175714 175768 171029 170465 170102 156389 124291 99360 86675 85056 128236 164257 162401 152779 156005 153387 153190 148840 144211 145953 145542 150271 147489 143824 134754 131736 126304 125511 125495 130133 126257 110323 98417 105749 120665 124075 127245 146731 144979 148210 144670 142970 142524 146142 146522 148128 148798 150181 152388 1556 etc...

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' @ 216.218.223.82 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 145214.837078652 1815.37112599316 79.9918182014749 Geometric Mean 143192.289620066 Harmonic Mean 141154.1097096 Quadratic Mean 147209.596186255 Winsorized Mean ( 1 / 59 ) 145201.505617978 1810.06367785371 80.21900411269 Winsorized Mean ( 2 / 59 ) 145313.348314607 1785.11740384461 81.4026842165366 Winsorized Mean ( 3 / 59 ) 145328.264044944 1782.63179180154 81.5245552745777 Winsorized Mean ( 4 / 59 ) 145434.376404494 1757.38374006508 82.756186420109 Winsorized Mean ( 5 / 59 ) 145548.926966292 1739.77182360911 83.6597793981712 Winsorized Mean ( 6 / 59 ) 145547.005617978 1731.59116630122 84.053908596031 Winsorized Mean ( 7 / 59 ) 145579.882022472 1727.06645951836 84.2931557266595 Winsorized Mean ( 8 / 59 ) 145541.949438202 1706.79039382105 85.2723040656284 Winsorized Mean ( 9 / 59 ) 145517.275280899 1694.69832999281 85.866182025161 Winsorized Mean ( 10 / 59 ) 145455.308988764 1685.55942200175 86.2949754782437 Winsorized Mean ( 11 / 59 ) 145388.134831461 1675.90195648902 86.7521720280378 Winsorized Mean ( 12 / 59 ) 145299.280898876 1664.25927313106 87.3056760113567 Winsorized Mean ( 13 / 59 ) 145303.005617978 1654.56122268645 87.8196609624723 Winsorized Mean ( 14 / 59 ) 145317.162921348 1650.36077164306 88.051755360541 Winsorized Mean ( 15 / 59 ) 145212.078651685 1634.38039732163 88.84839715996 Winsorized Mean ( 16 / 59 ) 145203.988764045 1628.16012144677 89.1828677360172 Winsorized Mean ( 17 / 59 ) 144849.949438202 1582.60850605659 91.52607791748 Winsorized Mean ( 18 / 59 ) 144851.061797753 1581.10823810245 91.6136279016507 Winsorized Mean ( 19 / 59 ) 144951.719101124 1560.18433195708 92.9067906478063 Winsorized Mean ( 20 / 59 ) 144925.202247191 1554.22767706304 93.2457994320693 Winsorized Mean ( 21 / 59 ) 144923.078651685 1552.66153201937 93.3384872768767 Winsorized Mean ( 22 / 59 ) 144984.876404494 1545.11137473244 93.834579678504 Winsorized Mean ( 23 / 59 ) 144958.904494382 1539.36997415478 94.1676834862097 Winsorized Mean ( 24 / 59 ) 145038.185393258 1529.63759662547 94.818658820381 Winsorized Mean ( 25 / 59 ) 145036.640449438 1514.58972738793 95.7596884666379 Winsorized Mean ( 26 / 59 ) 145079.730337079 1509.19587168483 96.130484491132 Winsorized Mean ( 27 / 59 ) 145029.674157303 1496.84547116159 96.8902114155826 Winsorized Mean ( 28 / 59 ) 145089.449438202 1485.59049542784 97.664497642345 Winsorized Mean ( 29 / 59 ) 145079.02247191 1484.40927672978 97.7351898470519 Winsorized Mean ( 30 / 59 ) 145064.696629213 1479.7770936185 98.0314516657958 Winsorized Mean ( 31 / 59 ) 145057.382022472 1476.20993198254 98.263383059387 Winsorized Mean ( 32 / 59 ) 145044.438202247 1470.6646802237 98.6250911935854 Winsorized Mean ( 33 / 59 ) 145009.769662921 1466.8034865701 98.8610751137533 Winsorized Mean ( 34 / 59 ) 144999.646067416 1438.04741245258 100.830921714966 Winsorized Mean ( 35 / 59 ) 144777.848314607 1408.69863139426 102.774181140016 Winsorized Mean ( 36 / 59 ) 144819.511235955 1394.59892785351 103.843125319803 Winsorized Mean ( 37 / 59 ) 144998.275280899 1365.42421944194 106.192839716993 Winsorized Mean ( 38 / 59 ) 145029.657303371 1352.03126763416 107.267975804398 Winsorized Mean ( 39 / 59 ) 144972.91011236 1341.55097929369 108.0636609044 Winsorized Mean ( 40 / 59 ) 144882.348314607 1313.73344923893 110.282910432508 Winsorized Mean ( 41 / 59 ) 144168.073033708 1235.67941206825 116.671097394431 Winsorized Mean ( 42 / 59 ) 143765.061797753 1190.99684934678 120.709859036658 Winsorized Mean ( 43 / 59 ) 143567.938202247 1149.11123907188 124.938242113274 Winsorized Mean ( 44 / 59 ) 143443.353932584 1135.77704566141 126.295345094822 Winsorized Mean ( 45 / 59 ) 143151.612359551 1081.21798049405 132.398475554521 Winsorized Mean ( 46 / 59 ) 143097.859550562 1072.36695073238 133.441131743972 Winsorized Mean ( 47 / 59 ) 142545.213483146 1022.42479798097 139.41877560544 Winsorized Mean ( 48 / 59 ) 142647.146067416 1009.65077649555 141.283649147022 Winsorized Mean ( 49 / 59 ) 142679.078651685 997.450990927534 143.043698336504 Winsorized Mean ( 50 / 59 ) 142491.157303371 978.895014863005 145.563267909084 Winsorized Mean ( 51 / 59 ) 142757.617977528 953.638853469114 149.697778627842 Winsorized Mean ( 52 / 59 ) 142637.550561798 918.396321497682 155.311543854172 Winsorized Mean ( 53 / 59 ) 142769.157303371 902.917169663496 158.119883085819 Winsorized Mean ( 54 / 59 ) 142925.696629213 871.873322476858 163.929429820359 Winsorized Mean ( 55 / 59 ) 142994.292134831 858.568891238204 166.549584540163 Winsorized Mean ( 56 / 59 ) 143161.033707865 834.044491381417 171.646758880632 Winsorized Mean ( 57 / 59 ) 143541.140449438 795.596917898739 180.419427501739 Winsorized Mean ( 58 / 59 ) 143614.780898876 787.371547774863 182.397727355956 Winsorized Mean ( 59 / 59 ) 143620.084269663 784.418339006631 183.091186332461 Trimmed Mean ( 1 / 59 ) 145250.664772727 1777.48204843458 81.717092389568 Trimmed Mean ( 2 / 59 ) 145300.954022989 1742.47925360018 83.3874800648436 Trimmed Mean ( 3 / 59 ) 145294.540697674 1718.84703008599 84.5302334381705 Trimmed Mean ( 4 / 59 ) 145282.770588235 1694.44570518693 85.7405876998627 Trimmed Mean ( 5 / 59 ) 145242.613095238 1675.72724794893 86.674375721355 Trimmed Mean ( 6 / 59 ) 145176.921686747 1659.85844159903 87.463435464346 Trimmed Mean ( 7 / 59 ) 145109.975609756 1644.46871413976 88.2412504184763 Trimmed Mean ( 8 / 59 ) 145036.216049383 1628.69706030112 89.0504560882353 Trimmed Mean ( 9 / 59 ) 144965.8875 1615.03001271808 89.7604913583149 Trimmed Mean ( 10 / 59 ) 144896.867088608 1602.07121782376 90.4434618614733 Trimmed Mean ( 11 / 59 ) 144833.147435897 1589.32125016062 91.1289315619862 Trimmed Mean ( 12 / 59 ) 144774.831168831 1576.76789608238 91.8174650362537 Trimmed Mean ( 13 / 59 ) 144723.651315789 1564.58693175375 92.4995910285202 Trimmed Mean ( 14 / 59 ) 144670.766666667 1552.47124255603 93.1874051518513 Trimmed Mean ( 15 / 59 ) 144615.236486486 1539.74808964646 93.9213612011636 Trimmed Mean ( 16 / 59 ) 144566.726027397 1527.62526441099 94.6349405154268 Trimmed Mean ( 17 / 59 ) 144517.493055556 1515.04372761986 95.3883313207026 Trimmed Mean ( 18 / 59 ) 144492.978873239 1505.87799557452 95.9526464281146 Trimmed Mean ( 19 / 59 ) 144467.685714286 1495.94589524112 96.5728013117745 Trimmed Mean ( 20 / 59 ) 144434.826086957 1486.95722705205 97.1344860896265 Trimmed Mean ( 21 / 59 ) 144402.735294118 1477.58196504435 97.72908624381 Trimmed Mean ( 22 / 59 ) 144369.820895522 1467.37151481111 98.386686287901 Trimmed Mean ( 23 / 59 ) 144332.121212121 1456.75681053713 99.0777047810087 Trimmed Mean ( 24 / 59 ) 144294.807692308 1445.53863157379 99.8207896631656 Trimmed Mean ( 25 / 59 ) 144251.734375 1433.96491806999 100.596418055438 Trimmed Mean ( 26 / 59 ) 144207.380952381 1422.44914634939 101.379638999734 Trimmed Mean ( 27 / 59 ) 144159.217741935 1410.13073342888 102.231101219528 Trimmed Mean ( 28 / 59 ) 144112.180327869 1397.53335501972 103.118955844768 Trimmed Mean ( 29 / 59 ) 144060.408333333 1384.478760814 104.053895524286 Trimmed Mean ( 30 / 59 ) 144007.423728814 1370.06413433984 105.109987276766 Trimmed Mean ( 31 / 59 ) 143953.344827586 1354.43358056179 106.283059497002 Trimmed Mean ( 32 / 59 ) 143897.736842105 1337.34665139287 107.599429581129 Trimmed Mean ( 33 / 59 ) 143840.785714286 1318.80288437995 109.069207701888 Trimmed Mean ( 34 / 59 ) 143783.463636364 1298.47617842396 110.732461654308 Trimmed Mean ( 35 / 59 ) 143724.509259259 1278.39147086028 112.426054565696 Trimmed Mean ( 36 / 59 ) 143673.971698113 1258.685777942 114.146019773915 Trimmed Mean ( 37 / 59 ) 143619.509615385 1237.86273815513 116.02216076835 Trimmed Mean ( 38 / 59 ) 143554.480392157 1217.09418519117 117.9485385263 Trimmed Mean ( 39 / 59 ) 143485.38 1194.93323855436 120.078156143342 Trimmed Mean ( 40 / 59 ) 143416.102040816 1170.94659878041 122.478772465107 Trimmed Mean ( 41 / 59 ) 143348.135416667 1146.61313458336 125.018745288274 Trimmed Mean ( 42 / 59 ) 143310.265957447 1127.14480731166 127.144502665327 Trimmed Mean ( 43 / 59 ) 143289.315217391 1109.49635863982 129.148071646721 Trimmed Mean ( 44 / 59 ) 143276.5 1093.48430300181 131.027486729055 Trimmed Mean ( 45 / 59 ) 143268.829545455 1076.45825362272 133.092787447443 Trimmed Mean ( 46 / 59 ) 143274.220930233 1062.35764179022 134.86439527916 Trimmed Mean ( 47 / 59 ) 143274.220930233 1046.92590067644 136.85230333652 Trimmed Mean ( 48 / 59 ) 143316.390243902 1034.00345228747 138.603396271891 Trimmed Mean ( 49 / 59 ) 143347.4125 1020.24475248167 140.502964755583 Trimmed Mean ( 50 / 59 ) 143378.538461538 1005.42440574206 142.604991128813 Trimmed Mean ( 51 / 59 ) 143378.538461538 989.951570422557 144.833891621928 Trimmed Mean ( 52 / 59 ) 143451.351351351 974.701969740384 147.174578286284 Trimmed Mean ( 53 / 59 ) 143490.041666667 960.63186272358 149.370479196728 Trimmed Mean ( 54 / 59 ) 143524.628571429 945.729056392005 151.76083213408 Trimmed Mean ( 55 / 59 ) 143524.628571429 931.736719090078 154.039897355975 Trimmed Mean ( 56 / 59 ) 143581.090909091 916.541230848281 156.655353929035 Trimmed Mean ( 57 / 59 ) 143601.953125 901.415830083455 159.307112580556 Trimmed Mean ( 58 / 59 ) 143605.016129032 888.227314239996 161.675973961583 Trimmed Mean ( 59 / 59 ) 143605.016129032 873.088177571144 164.479396031371 Median 144439.5 Midrange 142062 Midmean - Weighted Average at Xnp 143061.617977528 Midmean - Weighted Average at X(n+1)p 143276.5 Midmean - Empirical Distribution Function 143276.5 Midmean - Empirical Distribution Function - Averaging 143276.5 Midmean - Empirical Distribution Function - Interpolation 143268.829545455 Midmean - Closest Observation 143276.5 Midmean - True Basic - Statistics Graphics Toolkit 143276.5 Midmean - MS Excel (old versions) 143276.5 Number of observations 178

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/06/t1302112938ll5hpptbszha5ij/1rhks1302113036.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/06/t1302112938ll5hpptbszha5ij/1rhks1302113036.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/06/t1302112938ll5hpptbszha5ij/2rgrq1302113037.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/06/t1302112938ll5hpptbszha5ij/2rgrq1302113037.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