## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareCentral Tendency
Date of computationSat, 12 Nov 2011 09:22:30 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/12/t1321107779epyui7zq7q4v65x.htm/, Retrieved Tue, 21 Mar 2023 07:45:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=141469, Retrieved Tue, 21 Mar 2023 07:45:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-19 12:03:37] [74be16979710d4c4e7c6647856088456]
- RM D    [Central Tendency] [] [2011-11-12 14:22:30] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
255
280.2
299.9
339.2
374.2
393.5
389.2
381.7
375.2
369
357.4
352.1
346.5
342.9
340.3
328.3
322.9
314.3
308.9
294
285.6
281.2
280.3
278.8
274.5
270.4
263.4
259.9
258
262.7
284.7
311.3
322.1
327
331.3
333.3
321.4
327
320
314.7
316.7
314.4
321.3
318.2
307.2
301.3
287.5
277.7
274.4
258.8
253.3
251
248.4
249.5
246.1
244.5
243.6
244
240.8
249.8
248
259.4
260.5
260.8
261.3
259.5
256.6
257.9
256.5
254.2
253.3
253.8
255.5
257.1
257.3
253.2
252.8
252
250.7
252.2
250
251
253.4
251.2
255.6
261.1
258.9
259.9
261.2
264.7
267.1
266.4
267.7
268.6
267.5
268.5
268.5
270.5
270.9
270.1
269.3
269.8
270.1
264.9
263.7
264.8
263.7
255.9
276.2
360.1
380.5
373.7
369.8
366.6
359.3
345.8
326.2
324.5
328.1
327.5
324.4
316.5
310.9
301.5
291.7
290.4
287.4
277.7
281.6
288
276
272.9
283
283.3
276.8
284.5
282.7
281.2
287.4
283.1
284
285.5
289.2
292.5
296.4
305.2
303.9
311.5
316.3
316.7
322.5
317.1
309.8
303.8
290.3
293.7
291.7
296.5
289.1
288.5
293.8
297.7
305.4
302.7
302.5
303
294.5
294.1
294.5
297.1
289.4
292.4
287.9
286.6
280.5
272.4
269.2
270.6
267.3
262.5
266.8
268.8
263.1
261.2
266
262.5
265.2
261.3
253.7
249.2
239.1
236.4
235.2
245.2
246.2
247.7
251.4
253.3
254.8
250
249.3
241.5
243.3
248
253
252.9
251.5
251.6
253.5
259.8
334.1
448
445.8
445
448.2
438.2
439.8
423.4
410.8
408.4
406.7
405.9
402.7
405.1
399.6
386.5
381.4
375.2
357.7
359
355
352.7
344.4
343.8
338
339
333.3
334.4
328.3
330.7
330
331.6
351.2
389.4
410.9
442.8
462.8
466.9
461.7
439.2
430.3
416.1
402.5
397.3
403.3
395.9
387.8
378.6
377.1
370.4
362
350.3
348.2
344.6
343.5
342.8
347.6
346.6
349.5
342.1
342
342.8
339.3
348.2
333.7
334.7
354
367.7
363.3
358.4
353.1
343.1
344.6
344.4
333.9
331.7
324.3
321.2
322.4
321.7
320.5
312.8
309.7
315.6
309.7
304.6
302.5
301.5
298.8
291.3
293.6
294.6
285.9
297.6
301.1
293.8
297.7
292.9
292.1
287.2
288.2
283.8
299.9
292.4
293.3
300.8
293.7
293.1
294.4
292.1
291.9
282.5
277.9
287.5
289.2
285.6
293.2
290.8
283.1
275
287.8
287.8
287.4
284
277.8
277.6
304.9
294
300.9
324
332.9
341.6
333.4
348.2
344.7
344.7
329.3
323.5
323.2
317.4
330.1
329.2
334.9
315.8
315.4
319.6
317.3
313.8
315.8
311.3


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141469&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141469&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141469&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gertrude Mary Cox' @ cox.wessa.net

Parameters (Session):
Parameters (R input):
par1 = ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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 <- 3nodenom <- n/denomif (nodenom>40) denom <- n/40sqrtn = 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])/nwin[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 <- 3nodenom <- n/denomif (nodenom>40) denom <- n/40sqrtn = 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 - iqvalue <- (1-f)*data[i] + f*data[i+1]}q2 <- function(data,n,p,i,f) {np <- (n+1)*pi <<- floor(np)f <<- np - iqvalue <- (1-f)*data[i] + f*data[i+1]}q3 <- function(data,n,p,i,f) {np <- n*pi <<- floor(np)f <<- np - iif (f==0) {qvalue <- data[i]} else {qvalue <- data[i+1]}}q4 <- function(data,n,p,i,f) {np <- n*pi <<- floor(np)f <<- np - iif (f==0) {qvalue <- (data[i]+data[i+1])/2} else {qvalue <- data[i+1]}}q5 <- function(data,n,p,i,f) {np <- (n-1)*pi <<- floor(np)f <<- np - iif (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+0.5i <<- floor(np)f <<- np - iqvalue <- data[i]}q7 <- function(data,n,p,i,f) {np <- (n+1)*pi <<- floor(np)f <<- np - iif (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)*pi <<- floor(np)f <<- np - iif (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 <- 0myn <- 0roundno4 <- 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 / mynreturn(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)midmbitmap(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('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('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('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('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('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('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('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('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('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')mylabel <- paste(mymid,hyperlink('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')