Gemiddelde prijs van een kiwi

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

Title produced by software: Central Tendency

Date of computation: Sun, 27 Apr 2008 05:57:36 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Apr/27/t12092977754jmvb2ahw3r7t6p.htm/, Retrieved Sun, 27 Apr 2008 14:02:55 +0200

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Dataseries X:

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Text written by user:

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.406145833333333 0.00432092468901376 93.9951196941679 Geometric Mean 0.403948508617233 Harmonic Mean 0.401744057656114 Quadratic Mean 0.408323554304671 Winsorized Mean ( 1 / 32 ) 0.40625 0.0043002702893427 94.4708059413856 Winsorized Mean ( 2 / 32 ) 0.40625 0.0043002702893427 94.4708059413856 Winsorized Mean ( 3 / 32 ) 0.40625 0.0043002702893427 94.4708059413856 Winsorized Mean ( 4 / 32 ) 0.40625 0.00415502760351419 97.7731169959993 Winsorized Mean ( 5 / 32 ) 0.406770833333333 0.0040730575815799 99.8686675024984 Winsorized Mean ( 6 / 32 ) 0.406770833333333 0.0040730575815799 99.8686675024984 Winsorized Mean ( 7 / 32 ) 0.406770833333333 0.0040730575815799 99.8686675024984 Winsorized Mean ( 8 / 32 ) 0.4059375 0.00394473367844518 102.906186599649 Winsorized Mean ( 9 / 32 ) 0.4059375 0.00394473367844518 102.906186599649 Winsorized Mean ( 10 / 32 ) 0.406979166666667 0.00379900665590855 107.127784583819 Winsorized Mean ( 11 / 32 ) 0.406979166666667 0.00379900665590855 107.127784583819 Winsorized Mean ( 12 / 32 ) 0.406979166666667 0.00379900665590855 107.127784583819 Winsorized Mean ( 13 / 32 ) 0.406979166666667 0.00379900665590855 107.127784583819 Winsorized Mean ( 14 / 32 ) 0.406979166666667 0.00379900665590855 107.127784583819 Winsorized Mean ( 15 / 32 ) 0.405416666666667 0.00358149687743001 113.197548550589 Winsorized Mean ( 16 / 32 ) 0.405416666666667 0.00358149687743001 113.197548550589 Winsorized Mean ( 17 / 32 ) 0.405416666666667 0.00358149687743001 113.197548550589 Winsorized Mean ( 18 / 32 ) 0.405416666666667 0.00358149687743001 113.197548550589 Winsorized Mean ( 19 / 32 ) 0.405416666666667 0.00358149687743001 113.197548550589 Winsorized Mean ( 20 / 32 ) 0.4075 0.00331794694499845 122.816912613469 Winsorized Mean ( 21 / 32 ) 0.4075 0.00331794694499845 122.816912613469 Winsorized Mean ( 22 / 32 ) 0.4075 0.00331794694499845 122.816912613469 Winsorized Mean ( 23 / 32 ) 0.405104166666667 0.00300946894418656 134.609851166337 Winsorized Mean ( 24 / 32 ) 0.405104166666667 0.00300946894418656 134.609851166337 Winsorized Mean ( 25 / 32 ) 0.405104166666667 0.00300946894418656 134.609851166337 Winsorized Mean ( 26 / 32 ) 0.405104166666667 0.00300946894418656 134.609851166337 Winsorized Mean ( 27 / 32 ) 0.407916666666667 0.00268163289261603 152.115029536623 Winsorized Mean ( 28 / 32 ) 0.407916666666667 0.00268163289261603 152.115029536623 Winsorized Mean ( 29 / 32 ) 0.407916666666667 0.00268163289261603 152.115029536623 Winsorized Mean ( 30 / 32 ) 0.404791666666667 0.00230359733298044 175.721538166107 Winsorized Mean ( 31 / 32 ) 0.404791666666667 0.00230359733298044 175.721538166107 Winsorized Mean ( 32 / 32 ) 0.404791666666667 0.00230359733298044 175.721538166107 Trimmed Mean ( 1 / 32 ) 0.406276595744681 0.00424319079205288 95.747897196987 Trimmed Mean ( 2 / 32 ) 0.406304347826087 0.00417806420822541 97.2470329743116 Trimmed Mean ( 3 / 32 ) 0.406333333333333 0.0041036812437508 99.0167874154721 Trimmed Mean ( 4 / 32 ) 0.406363636363636 0.00401857565789538 101.121310374049 Trimmed Mean ( 5 / 32 ) 0.406395348837209 0.00396948962698042 102.379748286772 Trimmed Mean ( 6 / 32 ) 0.406309523809524 0.00393499882778423 103.255309999244 Trimmed Mean ( 7 / 32 ) 0.406219512195122 0.00389426745323988 104.312176056928 Trimmed Mean ( 8 / 32 ) 0.406125 0.00384631070152402 105.588193860439 Trimmed Mean ( 9 / 32 ) 0.406153846153846 0.00381573049037583 106.441963649755 Trimmed Mean ( 10 / 32 ) 0.406184210526316 0.00377882885998999 107.48944331059 Trimmed Mean ( 11 / 32 ) 0.406081081081081 0.0037598079443158 108.005804311097 Trimmed Mean ( 12 / 32 ) 0.405972222222222 0.00373548166213285 108.680020126354 Trimmed Mean ( 13 / 32 ) 0.405857142857143 0.00370491731406411 109.545533261021 Trimmed Mean ( 14 / 32 ) 0.405735294117647 0.00366697632730464 110.645735860498 Trimmed Mean ( 15 / 32 ) 0.405606060606061 0.00362025374761857 112.038019675519 Trimmed Mean ( 16 / 32 ) 0.405625 0.00359725286497949 112.759657223127 Trimmed Mean ( 17 / 32 ) 0.405645161290323 0.00356714669953285 113.716983196527 Trimmed Mean ( 18 / 32 ) 0.405666666666667 0.00352846909607532 114.969596054529 Trimmed Mean ( 19 / 32 ) 0.405689655172414 0.00347936679337640 116.598702943512 Trimmed Mean ( 20 / 32 ) 0.405714285714286 0.00341746035097173 118.718066648213 Trimmed Mean ( 21 / 32 ) 0.405555555555556 0.00338189641871375 119.919567409401 Trimmed Mean ( 22 / 32 ) 0.405384615384615 0.00333478330222758 121.562506059637 Trimmed Mean ( 23 / 32 ) 0.4052 0.00327314365522736 123.795360876654 Trimmed Mean ( 24 / 32 ) 0.405208333333333 0.00324787960471350 124.760884838611 Trimmed Mean ( 25 / 32 ) 0.405217391304348 0.00321137968205222 126.181713600864 Trimmed Mean ( 26 / 32 ) 0.405227272727273 0.0031604157867939 128.219607818868 Trimmed Mean ( 27 / 32 ) 0.405238095238095 0.00309054410445271 131.121925959331 Trimmed Mean ( 28 / 32 ) 0.405 0.00305924408293525 132.385644630034 Trimmed Mean ( 29 / 32 ) 0.404736842105263 0.00301104751329981 134.417288441162 Trimmed Mean ( 30 / 32 ) 0.404444444444444 0.00293972367896065 137.579068175359 Trimmed Mean ( 31 / 32 ) 0.404411764705882 0.00293090899464043 137.981686038497 Trimmed Mean ( 32 / 32 ) 0.404375 0.00290777253736124 139.066930031248 Median 0.405 Midrange 0.4 Midmean - Weighted Average at Xnp 0.403207547169811 Midmean - Weighted Average at X(n+1)p 0.403207547169811 Midmean - Empirical Distribution Function 0.403207547169811 Midmean - Empirical Distribution Function - Averaging 0.403207547169811 Midmean - Empirical Distribution Function - Interpolation 0.403207547169811 Midmean - Closest Observation 0.403207547169811 Midmean - True Basic - Statistics Graphics Toolkit 0.403207547169811 Midmean - MS Excel (old versions) 0.403207547169811 Number of observations 96

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/27/t12092977754jmvb2ahw3r7t6p/1rdn11209297451.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/27/t12092977754jmvb2ahw3r7t6p/1rdn11209297451.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/27/t12092977754jmvb2ahw3r7t6p/2fwp61209297451.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/27/t12092977754jmvb2ahw3r7t6p/2fwp61209297451.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

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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.

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