gemiddelde consumptieprijs van forel

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Wed, 20 Oct 2010 10:56:33 +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/Oct/20/t12875722544cljtnuuhhan0x2.htm/, Retrieved Wed, 20 Oct 2010 12:57:36 +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/Oct/20/t12875722544cljtnuuhhan0x2.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 «

17,88 18,11 18,16 18,27 18,29 18,35 18,35 18,38 18,41 18,41 18,42 18,43 18,48 18,54 18,65 18,66 18,69 18,72 18,72 18,73 18,84 18,83 18,91 18,91 18,94 18,97 19 19,08 19,18 19,24 19,23 19,25 19,3 19,33 19,35 19,35 19,31 19,47 19,7 19,76 19,9 19,97 20,1 20,26 20,44 20,43 20,57 20,6 20,69 20,93 20,98 21,11 21,14 21,16 21,32 21,32 21,48 21,58 21,74 21,75 21,81 21,89 22,21 22,37 22,47 22,51 22,55 22,61 22,58 22,85 22,93 22,98 23,01 23,11 23,18 23,18 23,21 23,22 23,12 23,15 23,16 23,21 23,21 23,22

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 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 20.4501190476190 0.194763747173518 104.999617969969 Geometric Mean 20.3742080395545 Harmonic Mean 20.2996248006628 Quadratic Mean 20.5269530420488 Winsorized Mean ( 1 / 28 ) 20.4528571428571 0.194347221626369 105.238742142543 Winsorized Mean ( 2 / 28 ) 20.4538095238095 0.194135246960732 105.358557212162 Winsorized Mean ( 3 / 28 ) 20.4577380952381 0.193588152187940 105.676601920231 Winsorized Mean ( 4 / 28 ) 20.4586904761905 0.193459000725257 105.752073563354 Winsorized Mean ( 5 / 28 ) 20.4604761904762 0.192677327758867 106.190367224120 Winsorized Mean ( 6 / 28 ) 20.4604761904762 0.192677327758867 106.190367224120 Winsorized Mean ( 7 / 28 ) 20.4613095238095 0.192066380563588 106.532488735244 Winsorized Mean ( 8 / 28 ) 20.4632142857143 0.191534264981264 106.838399320957 Winsorized Mean ( 9 / 28 ) 20.46 0.190992966501419 107.124363659999 Winsorized Mean ( 10 / 28 ) 20.46 0.190639681699978 107.322881666364 Winsorized Mean ( 11 / 28 ) 20.4482142857143 0.188300759832758 108.593371072298 Winsorized Mean ( 12 / 28 ) 20.4510714285714 0.186684237492932 109.548999440008 Winsorized Mean ( 13 / 28 ) 20.4526190476190 0.184254644244411 111.001918738553 Winsorized Mean ( 14 / 28 ) 20.4576190476190 0.179849224402806 113.748719882163 Winsorized Mean ( 15 / 28 ) 20.4165476190476 0.172919523534117 118.069649983852 Winsorized Mean ( 16 / 28 ) 20.4165476190476 0.171351692676558 119.149961696531 Winsorized Mean ( 17 / 28 ) 20.4165476190476 0.169695864935587 120.312581728478 Winsorized Mean ( 18 / 28 ) 20.4079761904762 0.168402161513294 121.185951576192 Winsorized Mean ( 19 / 28 ) 20.4011904761905 0.166772577200446 122.329407020376 Winsorized Mean ( 20 / 28 ) 20.4011904761905 0.160389335968524 127.197923434225 Winsorized Mean ( 21 / 28 ) 20.3636904761905 0.154249499828737 132.017870390505 Winsorized Mean ( 22 / 28 ) 20.2982142857143 0.140278609823108 144.699283171614 Winsorized Mean ( 23 / 28 ) 20.2763095238095 0.137307083647533 147.671256173926 Winsorized Mean ( 24 / 28 ) 20.2677380952381 0.133985462513510 151.268187719951 Winsorized Mean ( 25 / 28 ) 20.2736904761905 0.132526616445930 152.978254632058 Winsorized Mean ( 26 / 28 ) 20.2334523809524 0.124904380415259 161.991535554510 Winsorized Mean ( 27 / 28 ) 20.2270238095238 0.117715364545027 171.829938153798 Winsorized Mean ( 28 / 28 ) 20.2070238095238 0.107067758311358 188.731174802043 Trimmed Mean ( 1 / 28 ) 20.4476829268293 0.194082147864913 105.355815317241 Trimmed Mean ( 2 / 28 ) 20.44225 0.193664362454247 105.555042450463 Trimmed Mean ( 3 / 28 ) 20.4360256410256 0.193192963476889 105.780382852662 Trimmed Mean ( 4 / 28 ) 20.4280263157895 0.192751819318043 105.980977964638 Trimmed Mean ( 5 / 28 ) 20.4193243243243 0.192153305130002 106.265798085074 Trimmed Mean ( 6 / 28 ) 20.4097222222222 0.191540269837887 106.555776701663 Trimmed Mean ( 7 / 28 ) 20.3995714285714 0.190685418989194 106.980237590833 Trimmed Mean ( 8 / 28 ) 20.3886764705882 0.189679145981267 107.490343048054 Trimmed Mean ( 9 / 28 ) 20.3768181818182 0.188459112949349 108.123283946979 Trimmed Mean ( 10 / 28 ) 20.3646875 0.186979697240261 108.913897073179 Trimmed Mean ( 11 / 28 ) 20.3517741935484 0.185140409248288 109.926159697827 Trimmed Mean ( 12 / 28 ) 20.3395 0.18324375186857 110.996963293943 Trimmed Mean ( 13 / 28 ) 20.3260344827586 0.181099174625175 112.237035452137 Trimmed Mean ( 14 / 28 ) 20.3114285714286 0.178780215604667 113.61116498675 Trimmed Mean ( 15 / 28 ) 20.2951851851852 0.17656670973537 114.943441012197 Trimmed Mean ( 16 / 28 ) 20.2821153846154 0.174963977447094 115.921663879345 Trimmed Mean ( 17 / 28 ) 20.268 0.173038865517524 117.129755441834 Trimmed Mean ( 18 / 28 ) 20.2527083333333 0.170709756267904 118.638259324497 Trimmed Mean ( 19 / 28 ) 20.2369565217391 0.167804771993784 120.598218282426 Trimmed Mean ( 20 / 28 ) 20.2204545454545 0.164211536132165 123.136626218393 Trimmed Mean ( 21 / 28 ) 20.2023809523810 0.160666009869866 125.741474308998 Trimmed Mean ( 22 / 28 ) 20.18625 0.157207068861422 128.405485492476 Trimmed Mean ( 23 / 28 ) 20.175 0.155546002946771 129.704393669981 Trimmed Mean ( 24 / 28 ) 20.1647222222222 0.153634014768303 131.251677908911 Trimmed Mean ( 25 / 28 ) 20.1541176470588 0.151414670467002 133.105448665564 Trimmed Mean ( 26 / 28 ) 20.1415625 0.148246545256352 135.865307789606 Trimmed Mean ( 27 / 28 ) 20.1316666666667 0.145531197692851 138.332309400458 Trimmed Mean ( 28 / 28 ) 20.1210714285714 0.143182219424004 140.527724109284 Median 20.035 Midrange 20.55 Midmean - Weighted Average at Xnp 20.1704651162791 Midmean - Weighted Average at X(n+1)p 20.2023809523810 Midmean - Empirical Distribution Function 20.1704651162791 Midmean - Empirical Distribution Function - Averaging 20.2023809523810 Midmean - Empirical Distribution Function - Interpolation 20.2023809523810 Midmean - Closest Observation 20.1704651162791 Midmean - True Basic - Statistics Graphics Toolkit 20.2023809523810 Midmean - MS Excel (old versions) 20.2204545454545 Number of observations 84

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Oct/20/t12875722544cljtnuuhhan0x2/152ob1287572190.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t12875722544cljtnuuhhan0x2/152ob1287572190.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t12875722544cljtnuuhhan0x2/252ob1287572190.png (open in new window) http://www.freestatistics.org/blog/date/2010/Oct/20/t12875722544cljtnuuhhan0x2/252ob1287572190.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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