*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 14:55:34 +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/t1290437615pmhuyhhi1wrcirp.htm/, Retrieved Mon, 22 Nov 2010 15:53:35 +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/t1290437615pmhuyhhi1wrcirp.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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29.75 29.75 29.75 29.75 29.75 29.75 29.75 29.04 29.75 29.75 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.04 29.75 29.75 29.75 29.43 29.43 29.43 29.43 29.43 29.43 30.15 30.15 30.15 29.43 29.43 30.15 29.43 29.43 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 29.43 30.15 29.43 30.15 30.15 29.43 29.43 29.43 29.43 29.43 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 29.43 29.43 29.43 30.15 30.15 30.15 30.15 29.43 30.15 30.15 30.15 30.15 30.15 30.15 30.15 30.15 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 30.15 30.15 29.43 30.15 30.15 30.15 30.15 30.15 29.43 29.43 30.15 30.15 30.15 30.15 30.15 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 30.15 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 30.15 30.15 30.15 30.15 29.43 29.43 29.43 29.43 29.43 29.43 29.43 29.43 30.15 30.15 30.15 30 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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 29.892039800995 0.0358303297416147 834.266388742644 Geometric Mean 29.887756976167 Harmonic Mean 29.8834862713582 Quadratic Mean 29.8963343232937 Winsorized Mean ( 1 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 2 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 3 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 4 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 5 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 6 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 7 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 8 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 9 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 10 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 11 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 12 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 13 / 67 ) 29.892039800995 0.0358303297416147 834.266388742644 Winsorized Mean ( 14 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 15 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 16 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 17 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 18 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 19 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 20 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 21 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 22 / 67 ) 29.9192039800995 0.0331910168258031 901.424748061348 Winsorized Mean ( 23 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 24 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 25 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 26 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 27 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 28 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 29 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 30 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 31 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 32 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 33 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 34 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 35 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 36 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 37 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 38 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 39 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 40 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 41 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 42 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 43 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 44 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 45 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 46 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 47 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 48 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 49 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 50 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 51 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 52 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 53 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 54 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 55 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 56 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 57 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 58 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 59 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 60 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 61 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 62 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 63 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 64 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 65 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 66 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Winsorized Mean ( 67 / 67 ) 29.837960199005 0.0243458005009006 1225.58961238104 Trimmed Mean ( 1 / 67 ) 29.8914572864322 0.0356034783318968 839.565646024329 Trimmed Mean ( 2 / 67 ) 29.8908629441624 0.0353619873108597 845.282327641775 Trimmed Mean ( 3 / 67 ) 29.8902564102564 0.0351048756056711 851.455984234501 Trimmed Mean ( 4 / 67 ) 29.8896373056995 0.0348310731134830 858.13139343471 Trimmed Mean ( 5 / 67 ) 29.8890052356021 0.0345394096397579 865.359470452477 Trimmed Mean ( 6 / 67 ) 29.8883597883598 0.0342286020025136 873.198379126466 Trimmed Mean ( 7 / 67 ) 29.8877005347594 0.0338972389105671 881.714897594276 Trimmed Mean ( 8 / 67 ) 29.887027027027 0.0335437631193747 890.986110314036 Trimmed Mean ( 9 / 67 ) 29.8863387978142 0.0331664502297300 901.101522496505 Trimmed Mean ( 10 / 67 ) 29.885635359116 0.0327633833092944 912.165727116406 Trimmed Mean ( 11 / 67 ) 29.8849162011173 0.0323324222656689 924.301803173269 Trimmed Mean ( 12 / 67 ) 29.8841807909604 0.0318711665543274 937.655693901885 Trimmed Mean ( 13 / 67 ) 29.8834285714286 0.0313769093229117 952.401916450307 Trimmed Mean ( 14 / 67 ) 29.8826589595376 0.0308465804102748 968.751108294125 Trimmed Mean ( 15 / 67 ) 29.8826589595376 0.0305614649885091 977.78882559371 Trimmed Mean ( 16 / 67 ) 29.876449704142 0.0302535017280736 987.53691300529 Trimmed Mean ( 17 / 67 ) 29.8732335329341 0.0299206884495515 998.413976446517 Trimmed Mean ( 18 / 67 ) 29.8699393939394 0.0295607779544444 1010.45850146337 Trimmed Mean ( 19 / 67 ) 29.8665644171779 0.0291712357726157 1023.83610519562 Trimmed Mean ( 20 / 67 ) 29.8631055900621 0.0287491879475979 1038.74605587102 Trimmed Mean ( 21 / 67 ) 29.8595597484277 0.0282913557705578 1055.43049935775 Trimmed Mean ( 22 / 67 ) 29.855923566879 0.0277939731555151 1074.18696131808 Trimmed Mean ( 23 / 67 ) 29.8521935483871 0.0272526805341134 1095.38559008975 Trimmed Mean ( 24 / 67 ) 29.8530065359477 0.0274013671928895 1089.47142402786 Trimmed Mean ( 25 / 67 ) 29.8538410596026 0.0275522158781876 1083.53684478921 Trimmed Mean ( 26 / 67 ) 29.8546979865772 0.0277052646470268 1077.58212624693 Trimmed Mean ( 27 / 67 ) 29.8555782312925 0.0278605512912564 1071.60759021528 Trimmed Mean ( 28 / 67 ) 29.8564827586207 0.0280181131606190 1065.61361171835 Trimmed Mean ( 29 / 67 ) 29.8574125874126 0.0281779869569887 1059.60062487741 Trimmed Mean ( 30 / 67 ) 29.8574125874126 0.0283402084954058 1053.53538920692 Trimmed Mean ( 31 / 67 ) 29.8593525179856 0.0285048124268311 1047.51969845904 Trimmed Mean ( 32 / 67 ) 29.8603649635036 0.0286718319167219 1041.45298599105 Trimmed Mean ( 33 / 67 ) 29.8614074074074 0.0288412982725662 1035.36973700700 Trimmed Mean ( 34 / 67 ) 29.8624812030075 0.0290132405123748 1029.27079759569 Trimmed Mean ( 35 / 67 ) 29.8635877862595 0.029187684864788 1023.15712687055 Trimmed Mean ( 36 / 67 ) 29.8647286821705 0.0293646541898617 1017.02981036574 Trimmed Mean ( 37 / 67 ) 29.865905511811 0.0295441673077127 1010.89007521340 Trimmed Mean ( 38 / 67 ) 29.86712 0.0297262382199577 1004.73930737552 Trimmed Mean ( 39 / 67 ) 29.8683739837398 0.0299108752062014 998.579071251891 Trimmed Mean ( 40 / 67 ) 29.8696694214876 0.0300980797746268 992.411132043987 Trimmed Mean ( 41 / 67 ) 29.8710084033613 0.030287845441899 986.237481324405 Trimmed Mean ( 42 / 67 ) 29.8723931623932 0.0304801563129701 980.060366346667 Trimmed Mean ( 43 / 67 ) 29.8738260869565 0.0306749854257919 973.882323733338 Trimmed Mean ( 44 / 67 ) 29.8753097345133 0.0308722928191885 967.706218306677 Trimmed Mean ( 45 / 67 ) 29.8768468468468 0.0310720232739275 961.535287980956 Trimmed Mean ( 46 / 67 ) 29.8784403669725 0.0312741036670188 955.37319582661 Trimmed Mean ( 47 / 67 ) 29.8800934579439 0.0314784398670104 949.224090653186 Trimmed Mean ( 48 / 67 ) 29.8818095238095 0.0316849130829891 943.092677753073 Trimmed Mean ( 49 / 67 ) 29.8835922330097 0.0318933755614043 936.984301817626 Trimmed Mean ( 50 / 67 ) 29.8854455445545 0.0321036455017878 930.90504450313 Trimmed Mean ( 51 / 67 ) 29.8873737373737 0.032315501033748 924.861839714678 Trimmed Mean ( 52 / 67 ) 29.8893814432990 0.0325286730617047 918.862610429906 Trimmed Mean ( 53 / 67 ) 29.8914736842105 0.032742836738657 912.91643185332 Trimmed Mean ( 54 / 67 ) 29.8936559139785 0.0329576012731389 907.033726946094 Trimmed Mean ( 55 / 67 ) 29.8936559139785 0.0331724977008260 901.157826087789 Trimmed Mean ( 56 / 67 ) 29.8983146067416 0.0333869641591972 895.50863217689 Trimmed Mean ( 57 / 67 ) 29.9008045977011 0.0336003280837413 889.896209441171 Trimmed Mean ( 58 / 67 ) 29.9034117647059 0.0338117845885686 884.40796984185 Trimmed Mean ( 59 / 67 ) 29.9061445783133 0.0340203700907817 879.06582140377 Trimmed Mean ( 60 / 67 ) 29.9061445783133 0.03422492996966 873.811709909259 Trimmed Mean ( 61 / 67 ) 29.9120253164557 0.0344240786948629 868.92740344913 Trimmed Mean ( 62 / 67 ) 29.9151948051948 0.0346161503786987 864.197620992638 Trimmed Mean ( 63 / 67 ) 29.9185333333333 0.0347991370574032 859.74928872463 Trimmed Mean ( 64 / 67 ) 29.9220547945205 0.0349706111143183 855.634312386074 Trimmed Mean ( 65 / 67 ) 29.9257746478873 0.0351276270185299 851.915634156028 Trimmed Mean ( 66 / 67 ) 29.9297101449275 0.0352665958070296 848.67023482209 Trimmed Mean ( 67 / 67 ) 29.9338805970149 0.035383123242545 845.993170015646 Median 30.13 Midrange 29.95 Midmean - Weighted Average at Xnp 29.8290243902439 Midmean - Weighted Average at X(n+1)p 29.8290243902439 Midmean - Empirical Distribution Function 29.8290243902439 Midmean - Empirical Distribution Function - Averaging 29.8290243902439 Midmean - Empirical Distribution Function - Interpolation 29.8290243902439 Midmean - Closest Observation 29.8290243902439 Midmean - True Basic - Statistics Graphics Toolkit 29.8290243902439 Midmean - MS Excel (old versions) 29.8290243902439 Number of observations 201

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437615pmhuyhhi1wrcirp/16ymj1290437726.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437615pmhuyhhi1wrcirp/16ymj1290437726.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437615pmhuyhhi1wrcirp/26ymj1290437726.png (open in new window) http://www.freestatistics.org/blog/date/2010/Nov/22/t1290437615pmhuyhhi1wrcirp/26ymj1290437726.ps (open in new window)

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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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