*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Mon, 22 Nov 2010 12:27:00 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/22/t1290428708616g7q8jdcr5xjw.htm/, Retrieved Mon, 22 Nov 2010 13:25:14 +0100

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/Nov/22/t1290428708616g7q8jdcr5xjw.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:

Dataseries X:

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12.88 12.88 12.88 12.88 12.38 12.38 12.38 12.88 12.88 12.38 12.38 12.38 12.38 12.38 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.38 12.88 12.88 12.38 12.38 12.8 12.38 12.8 12.38 12.38 12.8 12.8 12.8 12.8 12.38 12.38 12.38 12.38 12.38 12.8 12.8 12.38 12.8 12.88 12.38 12.38 12.38 12.88 12.38 12.88 12.88 12.88 12.88 12.38 12.38 12.38 12.88 12.88 12.88 12.88 12.38 12.38 12.88 12.88 12.38 12.38 12.38 12.38 12.38 12.88 12.38 12.38 12.38 12.38 12.88 12.38 12.88 12.38 12.88 12.88 12.88 12.88 12.88 12.38 12.88 12.88 12.88 12.88 12.88 12.88 12.88 12.38 12.38 12.88 12.88 12.38 12.88 12.88 12.88 12.88 12.38 12.38 12.38 12.88 12.88 12.38 12.38 12.88 12.79 12.79 12.29 12.29 12.29 12.29 12.29 12.29 12.29 12.29 12.29 12.79 12.79 12.79 12.79 12.79 12.79 12.79 12.29 12.29 12.79 12.79 12.29 12.29 12.29 12.79 12.29 12.79 12.79 12.7 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 3 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 12.6377611940299 0.0173243082158293 729.481433635697 Geometric Mean 12.6353743985261 Harmonic Mean 12.6329762404567 Quadratic Mean 12.6401358508664 Winsorized Mean ( 1 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 2 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 3 / 67 ) 12.6377611940298 0.0173243082158293 729.481433635697 Winsorized Mean ( 4 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 5 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 6 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 7 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 8 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 9 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 10 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 11 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 12 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 13 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 14 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 15 / 67 ) 12.6377611940298 0.0173243082158293 729.481433635697 Winsorized Mean ( 16 / 67 ) 12.6377611940298 0.0173243082158293 729.481433635697 Winsorized Mean ( 17 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 18 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 19 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 20 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 21 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 22 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 23 / 67 ) 12.6377611940298 0.0173243082158293 729.481433635697 Winsorized Mean ( 24 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 25 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 26 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 27 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 28 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 29 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 30 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 31 / 67 ) 12.6377611940299 0.0173243082158293 729.481433635697 Winsorized Mean ( 32 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 33 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 34 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 35 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 36 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 37 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 38 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 39 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 40 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 41 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 42 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 43 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 44 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 45 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 46 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 47 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 48 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 49 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 50 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 51 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 52 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 53 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 54 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 55 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 56 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 57 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 58 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 59 / 67 ) 12.6520895522388 0.0159913863537194 791.181531881137 Winsorized Mean ( 60 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 61 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 62 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 63 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 64 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 65 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 66 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Winsorized Mean ( 67 / 67 ) 12.6282089552239 0.0144221664865645 875.61109261831 Trimmed Mean ( 1 / 67 ) 12.6382914572864 0.0173680783935894 727.673561281899 Trimmed Mean ( 2 / 67 ) 12.6388324873096 0.0174116522568273 725.8835807701 Trimmed Mean ( 3 / 67 ) 12.6393846153846 0.017454995682486 724.112732268775 Trimmed Mean ( 4 / 67 ) 12.6399481865285 0.0174980719097801 722.362340931043 Trimmed Mean ( 5 / 67 ) 12.6405235602094 0.017540841327206 720.633823909224 Trimmed Mean ( 6 / 67 ) 12.6411111111111 0.017583261240104 718.928698066501 Trimmed Mean ( 7 / 67 ) 12.6417112299465 0.0176252856167388 717.24858846773 Trimmed Mean ( 8 / 67 ) 12.6423243243243 0.0176668648106221 715.595237742648 Trimmed Mean ( 9 / 67 ) 12.6429508196721 0.0177079452565221 713.97051642768 Trimmed Mean ( 10 / 67 ) 12.643591160221 0.0177484691372948 712.37643440769 Trimmed Mean ( 11 / 67 ) 12.6442458100559 0.0177883740183083 710.815153596503 Trimmed Mean ( 12 / 67 ) 12.6449152542373 0.0178275924458241 709.289002015479 Trimmed Mean ( 13 / 67 ) 12.6456 0.0178660515052297 707.800489453331 Trimmed Mean ( 14 / 67 ) 12.6463005780347 0.0179036723344764 706.352324918401 Trimmed Mean ( 15 / 67 ) 12.6463005780347 0.0179403695874579 704.907472300664 Trimmed Mean ( 16 / 67 ) 12.6477514792899 0.0179760508413483 703.588991314919 Trimmed Mean ( 17 / 67 ) 12.648502994012 0.0180106159410931 702.280423689072 Trimmed Mean ( 18 / 67 ) 12.6492727272727 0.0180439562732883 701.025458923236 Trimmed Mean ( 19 / 67 ) 12.6500613496933 0.0180759539605688 699.828146126522 Trimmed Mean ( 20 / 67 ) 12.6508695652174 0.0181064809663299 698.692892823429 Trimmed Mean ( 21 / 67 ) 12.6516981132075 0.0181353980980892 697.624504561637 Trimmed Mean ( 22 / 67 ) 12.6525477707006 0.018162553896019 696.628229880928 Trimmed Mean ( 23 / 67 ) 12.6534193548387 0.0181877833910842 695.709811512352 Trimmed Mean ( 24 / 67 ) 12.6543137254902 0.0182109067147575 694.875544842342 Trimmed Mean ( 25 / 67 ) 12.6552317880795 0.0182317275393527 694.132344878645 Trimmed Mean ( 26 / 67 ) 12.6561744966443 0.0182500313245475 693.487823202853 Trimmed Mean ( 27 / 67 ) 12.6571428571429 0.0182655833415115 692.950376699848 Trimmed Mean ( 28 / 67 ) 12.6581379310345 0.018278126441086 692.52929023301 Trimmed Mean ( 29 / 67 ) 12.6591608391608 0.01828737852647 692.234855905529 Trimmed Mean ( 30 / 67 ) 12.6591608391608 0.0182930296836293 692.021007897325 Trimmed Mean ( 31 / 67 ) 12.6612949640288 0.0182947389138378 692.073006543536 Trimmed Mean ( 32 / 67 ) 12.6624087591241 0.0182921304020092 692.232587502944 Trimmed Mean ( 33 / 67 ) 12.6628888888889 0.0183738784788522 689.178874425642 Trimmed Mean ( 34 / 67 ) 12.6633834586466 0.0184559747281882 686.140051942397 Trimmed Mean ( 35 / 67 ) 12.663893129771 0.0185383614645623 683.118254759416 Trimmed Mean ( 36 / 67 ) 12.6644186046512 0.0186209730366251 680.115833890198 Trimmed Mean ( 37 / 67 ) 12.6649606299213 0.0187037348271619 677.135382155279 Trimmed Mean ( 38 / 67 ) 12.66552 0.0187865621157526 674.179763277706 Trimmed Mean ( 39 / 67 ) 12.6660975609756 0.0188693587827162 671.252145175033 Trimmed Mean ( 40 / 67 ) 12.666694214876 0.0189520158292218 668.356038165896 Trimmed Mean ( 41 / 67 ) 12.6673109243697 0.0190344096839188 665.495338952997 Trimmed Mean ( 42 / 67 ) 12.6679487179487 0.0191164002609823 662.674381421316 Trimmed Mean ( 43 / 67 ) 12.6686086956522 0.0191978287278681 659.897995509362 Trimmed Mean ( 44 / 67 ) 12.6692920353982 0.0192785149330546 657.171575683754 Trimmed Mean ( 45 / 67 ) 12.67 0.019358254434272 654.50116088819 Trimmed Mean ( 46 / 67 ) 12.6707339449541 0.0194368150557393 651.893528266748 Trimmed Mean ( 47 / 67 ) 12.6714953271028 0.019513932888184 649.356303504332 Trimmed Mean ( 48 / 67 ) 12.6722857142857 0.0195893076271827 646.898091319024 Trimmed Mean ( 49 / 67 ) 12.6731067961165 0.0196625971226713 644.528630528885 Trimmed Mean ( 50 / 67 ) 12.6739603960396 0.0197334109841086 642.258979263444 Trimmed Mean ( 51 / 67 ) 12.6748484848485 0.0198013030500826 640.101737385187 Trimmed Mean ( 52 / 67 ) 12.6757731958763 0.0198657624859538 638.071315150311 Trimmed Mean ( 53 / 67 ) 12.6767368421053 0.019926203215514 636.184259740738 Trimmed Mean ( 54 / 67 ) 12.6777419354839 0.0199819513186439 634.459654781317 Trimmed Mean ( 55 / 67 ) 12.6777419354839 0.0200322299311761 632.86723340538 Trimmed Mean ( 56 / 67 ) 12.6798876404494 0.0200761410581333 631.589885911491 Trimmed Mean ( 57 / 67 ) 12.6810344827586 0.020112643546783 630.500632761772 Trimmed Mean ( 58 / 67 ) 12.6822352941176 0.0201405262467361 629.687384468063 Trimmed Mean ( 59 / 67 ) 12.6834939759036 0.0201583750894177 629.19227961791 Trimmed Mean ( 60 / 67 ) 12.6834939759036 0.0201645324177597 629.00015299798 Trimmed Mean ( 61 / 67 ) 12.6872151898734 0.0202555378356323 626.357852989459 Trimmed Mean ( 62 / 67 ) 12.6897402597403 0.0203380302866074 623.941457501736 Trimmed Mean ( 63 / 67 ) 12.6924 0.02041006640878 621.86960815277 Trimmed Mean ( 64 / 67 ) 12.6952054794521 0.0204692939178349 620.207298327508 Trimmed Mean ( 65 / 67 ) 12.6981690140845 0.0205128510136069 619.034818985492 Trimmed Mean ( 66 / 67 ) 12.7013043478261 0.0205372356853138 618.452480287248 Trimmed Mean ( 67 / 67 ) 12.7046268656716 0.0205381338386512 618.587207848577 Median 12.79 Midrange 12.585 Midmean - Weighted Average at Xnp 12.7036094674556 Midmean - Weighted Average at X(n+1)p 12.7036094674556 Midmean - Empirical Distribution Function 12.7036094674556 Midmean - Empirical Distribution Function - Averaging 12.7036094674556 Midmean - Empirical Distribution Function - Interpolation 12.7036094674556 Midmean - Closest Observation 12.7036094674556 Midmean - True Basic - Statistics Graphics Toolkit 12.7036094674556 Midmean - MS Excel (old versions) 12.7036094674556 Number of observations 201

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/22/t1290428708616g7q8jdcr5xjw/19yre1290428815.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290428708616g7q8jdcr5xjw/19yre1290428815.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290428708616g7q8jdcr5xjw/2j78h1290428815.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290428708616g7q8jdcr5xjw/2j78h1290428815.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')

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