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*Unverified author*
R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Tue, 20 Apr 2010 13:30:26 +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/Apr/20/t12717703592d9pziq3q6ov3wa.htm/, Retrieved Tue, 20 Apr 2010 15:32:41 +0200
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Apr/20/t12717703592d9pziq3q6ov3wa.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:
KDGP1W52
 
Dataseries X:
» Textbox « » Textfile « » CSV «
15136 16733 20016 17708 18019 19227 22893 23739 21133 22591 26786 29740 15028 17977 20008 21354 19498 22125 25817 28779 20960 22254 27392 29945 16933 17892 20533 23569 22417 22084 26580 27454 24081 23451 28991 31386 16896 20045 23471 21747 25621 23859 25500 30998 24475 23145 29701 34365 17556 22077 25702 22214 26886 23191 27831 35406 23195 25110 30009 36242 18450 21845 26488 22394 28057 25451 24872 33424 24052 28449 33533 37351 19969 21701 26249 24493 24603 26485 30723 34569 26689 26157 32064 38870 21337 19419 23166 28286 24570 24001 33151 24878 26804 28967 33311 40226 20504 23060 23562 27562 23940 24584 34303 25517 23494 29095 32903 34379 16991 21109 23740 25552 21752 20294 29009 25500 24166 26960 31222 38641 14672 17543 25453 32683 22449 22316 27595 25451 25421 25288 32568 35110 16052 22146 21198 19543 22084 23816 29961 26773 26635 26972 30207 38687 16974 21697 24 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean25392.1477272727402.57959720170563.0736080610425
Geometric Mean24839.8852720432
Harmonic Mean24288.3541605287
Quadratic Mean25944.6232255969
Winsorized Mean ( 1 / 58 )25390.2386363636400.1000448742263.4597245405098
Winsorized Mean ( 2 / 58 )25392.2045454545399.09212012433563.6249208266596
Winsorized Mean ( 3 / 58 )25393.2613636364398.67112874569463.6947587439528
Winsorized Mean ( 4 / 58 )25384.7613636364390.36400911156265.0284369745307
Winsorized Mean ( 5 / 58 )25400.9545454545387.25325892319565.5926166149899
Winsorized Mean ( 6 / 58 )25405.0795454545386.29821057870665.7654600765446
Winsorized Mean ( 7 / 58 )25368.5284090909379.68280173119966.8150579731838
Winsorized Mean ( 8 / 58 )25332.3920454545373.40551265541967.8415052453481
Winsorized Mean ( 9 / 58 )25318.125370.98592393090968.2455138236327
Winsorized Mean ( 10 / 58 )25314.375363.02954725950669.7308943338005
Winsorized Mean ( 11 / 58 )25307.3125360.71807838232170.1581484728832
Winsorized Mean ( 12 / 58 )25307.2443181818360.47199462947670.2058542555983
Winsorized Mean ( 13 / 58 )25313.8920454545358.44461711302270.6214874959966
Winsorized Mean ( 14 / 58 )25267.2784090909348.12409077304272.5812406518106
Winsorized Mean ( 15 / 58 )25265.2329545455345.99347675372773.0222812048242
Winsorized Mean ( 16 / 58 )25258.7784090909344.1553502076673.3935369415295
Winsorized Mean ( 17 / 58 )25284.9545454545337.17785114073274.9899628932062
Winsorized Mean ( 18 / 58 )25339.0568181818324.9206622158777.9853661671634
Winsorized Mean ( 19 / 58 )25354.8181818182322.05425302116478.7284066084106
Winsorized Mean ( 20 / 58 )25340.0454545455318.91084002319179.4580875730117
Winsorized Mean ( 21 / 58 )25330.5316.67246701226979.9895874718361
Winsorized Mean ( 22 / 58 )25273.125307.9928255009682.0575120829274
Winsorized Mean ( 23 / 58 )25240.1931818182291.22165150659486.6700434230822
Winsorized Mean ( 24 / 58 )25224.7840909091288.18685766083187.529265892466
Winsorized Mean ( 25 / 58 )25224.2159090909287.86632110152787.6247551730603
Winsorized Mean ( 26 / 58 )25195.4090909091283.51735514260988.86725498069
Winsorized Mean ( 27 / 58 )25222.1022727273278.25499821411990.6438426429225
Winsorized Mean ( 28 / 58 )25223.6931818182271.19659169168993.0088871120246
Winsorized Mean ( 29 / 58 )25166.1875263.61291580085695.4664433779548
Winsorized Mean ( 30 / 58 )25215.4488636364253.82641575633399.3413108265396
Winsorized Mean ( 31 / 58 )25206.8181818182247.433585880106101.873066633857
Winsorized Mean ( 32 / 58 )25202.4545454545246.054736257904102.426211861406
Winsorized Mean ( 33 / 58 )25211.6420454545244.575724366991103.083174385794
Winsorized Mean ( 34 / 58 )25198.8920454545237.718428260628106.003107246810
Winsorized Mean ( 35 / 58 )25194.5170454545236.559256459183106.504042253792
Winsorized Mean ( 36 / 58 )25256.2897727273229.274152533995110.157597328737
Winsorized Mean ( 37 / 58 )25193.2215909091222.270816765602113.344711453852
Winsorized Mean ( 38 / 58 )25146.8011363636215.409682465744116.739418806593
Winsorized Mean ( 39 / 58 )25128.8522727273213.321238322514117.798173638649
Winsorized Mean ( 40 / 58 )25145.8977272727210.994850691083119.177779196559
Winsorized Mean ( 41 / 58 )25194.3522727273205.653346911920122.508836598307
Winsorized Mean ( 42 / 58 )25151.1590909091200.840854773826125.229297192709
Winsorized Mean ( 43 / 58 )25082.0170454545193.790718632781129.428371092338
Winsorized Mean ( 44 / 58 )25080.5170454545191.704829078055130.828822445796
Winsorized Mean ( 45 / 58 )25044.2102272727187.074600997472133.872851224797
Winsorized Mean ( 46 / 58 )25002.1306818182179.627033693656139.189130765573
Winsorized Mean ( 47 / 58 )24952.4602272727172.871975349073144.340690137237
Winsorized Mean ( 48 / 58 )24905.0056818182165.305062244662150.660877190543
Winsorized Mean ( 49 / 58 )24917.5340909091162.515490749709153.324055300579
Winsorized Mean ( 50 / 58 )24920.375161.593034926287154.216888193032
Winsorized Mean ( 51 / 58 )24902.1193181818158.223761339481157.385459095189
Winsorized Mean ( 52 / 58 )24925.7556818182152.845145139362163.078491365174
Winsorized Mean ( 53 / 58 )24839.3295454545137.910893602473180.111439325843
Winsorized Mean ( 54 / 58 )24854.0568181818135.977783640896182.780275959042
Winsorized Mean ( 55 / 58 )24864.9943181818130.987993525618189.826515002833
Winsorized Mean ( 56 / 58 )24892.3579545455124.190964763380200.436142854455
Winsorized Mean ( 57 / 58 )24919.5625121.856396390649204.499420942275
Winsorized Mean ( 58 / 58 )24920.5511363636120.757254029073206.368978300583
Trimmed Mean ( 1 / 58 )25374.3678160920392.34913535313264.6729291075253
Trimmed Mean ( 2 / 58 )25358.1279069767384.00632979344966.0357029026487
Trimmed Mean ( 3 / 58 )25340.4882352941375.58148824885867.4700139068187
Trimmed Mean ( 4 / 58 )25322.0595238095366.64868271561569.0635497072006
Trimmed Mean ( 5 / 58 )25305.4397590361359.55268490176170.3803387421518
Trimmed Mean ( 6 / 58 )25284.9390243902352.67615283518571.6944959876734
Trimmed Mean ( 7 / 58 )25263.1851851852345.45293648482673.1306135135282
Trimmed Mean ( 8 / 58 )25246.63125338.94238156445974.4864986593559
Trimmed Mean ( 9 / 58 )25234.6898734177333.01284645788475.7769261511331
Trimmed Mean ( 10 / 58 )25224.2307692308326.99268435246377.1400461731486
Trimmed Mean ( 11 / 58 )25213.9285714286321.66332075603278.3860855262146
Trimmed Mean ( 12 / 58 )25204.0986842105316.2167412197979.7051370113644
Trimmed Mean ( 13 / 58 )25194.0133333333310.34434090489381.1808369370401
Trimmed Mean ( 14 / 58 )25183.0472972973304.22481359464782.7777556989532
Trimmed Mean ( 15 / 58 )25183.0472972973298.8474625115384.2672281225265
Trimmed Mean ( 16 / 58 )25168.5069444444293.250396034485.8259947294053
Trimmed Mean ( 17 / 58 )25161.5140845070287.36614925818687.5590745446517
Trimmed Mean ( 18 / 58 )25152.3857142857281.72450582528189.2800775019715
Trimmed Mean ( 19 / 58 )25139.1594202899276.87299024807290.796720177601
Trimmed Mean ( 20 / 58 )25124.4705882353271.86456341948292.415393430547
Trimmed Mean ( 21 / 58 )25110.3134328358266.71307604426594.1472904338157
Trimmed Mean ( 22 / 58 )25096.3333333333261.2982980481996.0447638610525
Trimmed Mean ( 23 / 58 )25085.4538461538256.25614680273597.8921058446437
Trimmed Mean ( 24 / 58 )25076.203125252.36982381490199.362922024275
Trimmed Mean ( 25 / 58 )25067.5555555556248.390201876014100.920065953601
Trimmed Mean ( 26 / 58 )25058.6612903226244.039010009436102.683014856328
Trimmed Mean ( 27 / 58 )25051.0737704918239.664258220133104.525697559301
Trimmed Mean ( 28 / 58 )25041.7833333333235.324772952558106.413715050654
Trimmed Mean ( 29 / 58 )25032.093220339231.190174963086108.274900628177
Trimmed Mean ( 30 / 58 )25032.093220339227.337259831677110.109945192763
Trimmed Mean ( 31 / 58 )25015.2807017544223.945514500982111.702530669105
Trimmed Mean ( 32 / 58 )25005.5714285714220.755038346405113.272936445206
Trimmed Mean ( 33 / 58 )24995.7272727273217.323599210547115.016166507122
Trimmed Mean ( 34 / 58 )24985.0648148148213.622263970191116.959086335220
Trimmed Mean ( 35 / 58 )24974.6226415094210.126092915988118.855408649771
Trimmed Mean ( 36 / 58 )24963.9903846154206.314458094841120.99971381133
Trimmed Mean ( 37 / 58 )24949.9803921569202.684744385843123.097475677107
Trimmed Mean ( 38 / 58 )24938.41199.30061558542125.129618524994
Trimmed Mean ( 39 / 58 )24928.5612244898196.155838544841127.085491869217
Trimmed Mean ( 40 / 58 )24919.1458333333192.802053964617129.247304792233
Trimmed Mean ( 41 / 58 )24908.5319148936189.211855386346131.643611147059
Trimmed Mean ( 42 / 58 )24895.1956521739185.624147763567134.116147883321
Trimmed Mean ( 43 / 58 )24883.2777777778182.049919089912136.683816736487
Trimmed Mean ( 44 / 58 )24874.0340909091178.732610314336139.168974521008
Trimmed Mean ( 45 / 58 )24864.4302325581175.140384216495141.968571918985
Trimmed Mean ( 46 / 58 )24856.0595238095171.526330590456144.911043326386
Trimmed Mean ( 47 / 58 )24849.243902439168.193042652783147.742400699283
Trimmed Mean ( 48 / 58 )24844.4125165.09818874961150.482647254715
Trimmed Mean ( 49 / 58 )24844.4125162.352219838929153.027858348031
Trimmed Mean ( 50 / 58 )24837.9736842105159.448219581181155.774543920602
Trimmed Mean ( 51 / 58 )24834.0540540541156.142511363269159.047358962205
Trimmed Mean ( 52 / 58 )24830.7916666667152.669265125266162.644338703620
Trimmed Mean ( 53 / 58 )24826.2149.236897562911166.354302491007
Trimmed Mean ( 54 / 58 )24825.5588235294147.072953447601168.797581347098
Trimmed Mean ( 55 / 58 )24824.1515151515144.700006753663171.555980349138
Trimmed Mean ( 56 / 58 )24822.109375142.472830738372174.223458931490
Trimmed Mean ( 57 / 58 )24818.5483870968140.639462161178176.469306734505
Trimmed Mean ( 58 / 58 )24813.35138.659347288221178.951873676589
Median24669
Midrange26939
Midmean - Weighted Average at Xnp24812.0333333333
Midmean - Weighted Average at X(n+1)p24874.0340909091
Midmean - Empirical Distribution Function24812.0333333333
Midmean - Empirical Distribution Function - Averaging24874.0340909091
Midmean - Empirical Distribution Function - Interpolation24874.0340909091
Midmean - Closest Observation24812.0333333333
Midmean - True Basic - Statistics Graphics Toolkit24874.0340909091
Midmean - MS Excel (old versions)24852.5164835165
Number of observations176
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Apr/20/t12717703592d9pziq3q6ov3wa/1ykl61271770224.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Apr/20/t12717703592d9pziq3q6ov3wa/1ykl61271770224.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Apr/20/t12717703592d9pziq3q6ov3wa/2ykl61271770224.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Apr/20/t12717703592d9pziq3q6ov3wa/2ykl61271770224.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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