Verbruik zonne-energie

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sat, 05 Jun 2010 15:13:53 +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/Jun/05/t1275750862bq7b3jg0e9fuv2s.htm/, Retrieved Sat, 05 Jun 2010 17:14:24 +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/Jun/05/t1275750862bq7b3jg0e9fuv2s.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 «

5,074 4,643 5,451 5,397 5,635 5,708 5,578 5,574 5,352 5,302 4,923 4,982 5,101 4,763 5,505 5,385 5,794 5,695 5,798 5,705 5,422 5,311 4,968 5,053 5,236 4,782 5,531 5,566 5,961 5,868 5,872 5,908 5,594 5,526 5,111 5,177 5,835 5,348 6,038 6,039 6,408 6,214 6,138 6,529 6,058 6,026 5,678 5,733 6,488 5,936 6,84 6,694 7,193 6,991 7,209 7,104 6,83 6,848 6,396 6,414 7,151 6,882 7,698 7,626 7,936 8,054 8,128 8,062 7,708 7,574 7,039 7,146 7,07 6,607 7,699 7,663 7,988 7,723 8,087 8,028 7,362

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 6.2527037037037 0.109865360143206 56.9124216727955 Geometric Mean 6.17759061655638 Harmonic Mean 6.10509319604907 Quadratic Mean 6.32944984932038 Winsorized Mean ( 1 / 27 ) 6.25367901234568 0.109496656788639 57.1129676079254 Winsorized Mean ( 2 / 27 ) 6.25353086419753 0.109288822079895 57.2202238544203 Winsorized Mean ( 3 / 27 ) 6.25845679012346 0.108385721021795 57.742447354896 Winsorized Mean ( 4 / 27 ) 6.2593950617284 0.107783551791227 58.0737501938385 Winsorized Mean ( 5 / 27 ) 6.25779012345679 0.107152106775532 58.4009993995354 Winsorized Mean ( 6 / 27 ) 6.2591975308642 0.105614226997920 59.2647194301526 Winsorized Mean ( 7 / 27 ) 6.2426049382716 0.101853052705229 61.2903076782411 Winsorized Mean ( 8 / 27 ) 6.24379012345679 0.101205079527845 61.6944342377489 Winsorized Mean ( 9 / 27 ) 6.2439012345679 0.100868081868328 61.9016552998262 Winsorized Mean ( 10 / 27 ) 6.25192592592593 0.0997247288106173 62.6918318103293 Winsorized Mean ( 11 / 27 ) 6.25518518518519 0.097804537233348 63.9559816152617 Winsorized Mean ( 12 / 27 ) 6.25948148148148 0.0955721805807538 65.494806579123 Winsorized Mean ( 13 / 27 ) 6.25258024691358 0.0939113662512269 66.5795898463131 Winsorized Mean ( 14 / 27 ) 6.22233333333333 0.0868731567883335 71.6255004810526 Winsorized Mean ( 15 / 27 ) 6.19474074074074 0.0822690571899245 75.2985502974673 Winsorized Mean ( 16 / 27 ) 6.1980987654321 0.0809561811916119 76.5611553583792 Winsorized Mean ( 17 / 27 ) 6.1918024691358 0.0792967302342897 78.0839569404884 Winsorized Mean ( 18 / 27 ) 6.19624691358025 0.0784378509403672 78.9956231499888 Winsorized Mean ( 19 / 27 ) 6.1931975308642 0.076121139687548 81.3597583573395 Winsorized Mean ( 20 / 27 ) 6.19813580246914 0.073267562578956 84.5959055317253 Winsorized Mean ( 21 / 27 ) 6.19554320987654 0.0714357866911246 86.7288441389321 Winsorized Mean ( 22 / 27 ) 6.18386419753086 0.0693659706682972 89.1483841133231 Winsorized Mean ( 23 / 27 ) 6.16285185185185 0.0637643692619944 96.6504008928559 Winsorized Mean ( 24 / 27 ) 6.15514814814815 0.062074017722948 99.1582045747406 Winsorized Mean ( 25 / 27 ) 6.15391358024691 0.0615854525208745 99.9247927610995 Winsorized Mean ( 26 / 27 ) 6.15583950617284 0.0605404758410328 101.681386223935 Winsorized Mean ( 27 / 27 ) 6.12417283950617 0.0527321053554975 116.137461195975 Trimmed Mean ( 1 / 27 ) 6.2493417721519 0.108175539669061 57.7703775850840 Trimmed Mean ( 2 / 27 ) 6.24477922077922 0.10661606434048 58.5725918454129 Trimmed Mean ( 3 / 27 ) 6.24005333333333 0.104903136605488 59.483953819231 Trimmed Mean ( 4 / 27 ) 6.23324657534247 0.103264350926671 60.3620370380166 Trimmed Mean ( 5 / 27 ) 6.22578873239437 0.101519200422996 61.3262191433113 Trimmed Mean ( 6 / 27 ) 6.21827536231884 0.0996212582295757 62.4191610588667 Trimmed Mean ( 7 / 27 ) 6.21002985074627 0.097749740387808 63.5298858708869 Trimmed Mean ( 8 / 27 ) 6.20423076923077 0.0964146114077084 64.3494868531383 Trimmed Mean ( 9 / 27 ) 6.19787301587302 0.0949161472497544 65.2984049127537 Trimmed Mean ( 10 / 27 ) 6.19108196721311 0.0931418194040825 66.469411987262 Trimmed Mean ( 11 / 27 ) 6.18272881355932 0.091178205323173 67.8092839362783 Trimmed Mean ( 12 / 27 ) 6.17336842105263 0.089127252074732 69.264655617076 Trimmed Mean ( 13 / 27 ) 6.1628 0.0870013367287687 70.8356932401264 Trimmed Mean ( 14 / 27 ) 6.15224528301887 0.0846697413392016 72.6616756554377 Trimmed Mean ( 15 / 27 ) 6.14429411764706 0.0831821214487808 73.8655616210797 Trimmed Mean ( 16 / 27 ) 6.13873469387755 0.0821720536906969 74.7058691874041 Trimmed Mean ( 17 / 27 ) 6.13234042553191 0.0810424979398864 75.668205958812 Trimmed Mean ( 18 / 27 ) 6.12604444444444 0.0798344053547024 76.7343906079912 Trimmed Mean ( 19 / 27 ) 6.1186976744186 0.0783314544781889 78.1129077096652 Trimmed Mean ( 20 / 27 ) 6.1109512195122 0.0767565993922848 79.6146685483103 Trimmed Mean ( 21 / 27 ) 6.10189743589744 0.0751608064198977 81.1845658202258 Trimmed Mean ( 22 / 27 ) 6.09213513513513 0.0733102457735522 83.1007326582033 Trimmed Mean ( 23 / 27 ) 6.08248571428571 0.0711998061019521 85.4284027905372 Trimmed Mean ( 24 / 27 ) 6.07390909090909 0.0696595667095323 87.194184199224 Trimmed Mean ( 25 / 27 ) 6.06506451612903 0.0677808127048729 89.480551709186 Trimmed Mean ( 26 / 27 ) 6.05513793103448 0.0650125740800737 93.1379508766501 Trimmed Mean ( 27 / 27 ) 6.04351851851852 0.0610371277970725 99.0138090804526 Median 5.961 Midrange 6.3855 Midmean - Weighted Average at Xnp 6.086975 Midmean - Weighted Average at X(n+1)p 6.1109512195122 Midmean - Empirical Distribution Function 6.1109512195122 Midmean - Empirical Distribution Function - Averaging 6.1109512195122 Midmean - Empirical Distribution Function - Interpolation 6.1109512195122 Midmean - Closest Observation 6.09523809523809 Midmean - True Basic - Statistics Graphics Toolkit 6.1109512195122 Midmean - MS Excel (old versions) 6.1109512195122 Number of observations 81

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jun/05/t1275750862bq7b3jg0e9fuv2s/1g7z41275750831.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/05/t1275750862bq7b3jg0e9fuv2s/1g7z41275750831.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/05/t1275750862bq7b3jg0e9fuv2s/2ryy71275750831.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/05/t1275750862bq7b3jg0e9fuv2s/2ryy71275750831.ps (open in new window)

Parameters (Session):

par1 = 0 ;

Parameters (R input):

par1 = 0 ;

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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