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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_meanplot.wasp
Title produced by softwareMean Plot
Date of computationThu, 11 Nov 2010 14:01:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/11/t1289484113gzzcoqtng3xjom8.htm/, Retrieved Fri, 26 Apr 2024 18:56:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=93383, Retrieved Fri, 26 Apr 2024 18:56:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Mean Plot] [Colombia Coffee] [2008-01-07 13:38:24] [74be16979710d4c4e7c6647856088456]
-  MPD      [Mean Plot] [ws 6 - Q3 - Seaso...] [2010-11-11 14:01:36] [0829c729852d8a4b1b0c41cf0848af95] [Current]
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Dataseries X:
255,00
280,20
299,90
339,20
374,20
393,50
389,20
381,70
375,20
369,00
357,40
352,10
346,50
342,90
340,30
328,30
322,90
314,30
308,90
294,00
285,60
281,20
280,30
278,80
274,50
270,40
263,40
259,90
258,00
262,70
284,70
311,30
322,10
327,00
331,30
333,30
321,40
327,00
320,00
314,70
316,70
314,40
321,30
318,20
307,20
301,30
287,50
277,70
274,40
258,80
253,30
251,00
248,40
249,50
246,10
244,50
243,60
244,00
240,80
249,80
248,00
259,40
260,50
260,80
261,30
259,50
256,60
257,90
256,50
254,20
253,30
253,80
255,50
257,10
257,30
253,20
252,80
252,00
250,70
252,20
250,00
251,00
253,40
251,20
255,60
261,10
258,90
259,90
261,20
264,70
267,10
266,40
267,70
268,60
267,50
268,50
268,50
270,50
270,90
270,10
269,30
269,80
270,10
264,90
263,70
264,80
263,70
255,90
276,20
360,10
380,50
373,70
369,80
366,60
359,30
345,80
326,20
324,50
328,10
327,50
324,40
316,50
310,90
301,50
291,70
290,40
287,40
277,70
281,60
288,00
276,00
272,90
283,00
283,30
276,80
284,50
282,70
281,20
287,40
283,10
284,00
285,50
289,20
292,50
296,40
305,20
303,90
311,50
316,30
316,70
322,50
317,10
309,80
303,80
290,30
293,70
291,70
296,50
289,10
288,50
293,80
297,70
305,40
302,70
302,50
303,00
294,50
294,10
294,50
297,10
289,40
292,40
287,90
286,60
280,50
272,40
269,20
270,60
267,30
262,50
266,80
268,80
263,10
261,20
266,00
262,50
265,20
261,30
253,70
249,20
239,10
236,40
235,20
245,20
246,20
247,70
251,40
253,30
254,80
250,00
249,30
241,50
243,30
248,00
253,00
252,90
251,50
251,60
253,50
259,80
334,10
448,00
445,80
445,00
448,20
438,20
439,80
423,40
410,80
408,40
406,70
405,90
402,70
405,10
399,60
386,50
381,40
375,20
357,70
359,00
355,00
352,70
344,40
343,80
338,00
339,00
333,30
334,40
328,30
330,70
330,00
331,60
351,20
389,40
410,90
442,80
462,80
466,90
461,70
439,20
430,30
416,10
402,50
397,30
403,30
395,90
387,80
378,60
377,10
370,40
362,00
350,30
348,20
344,60
343,50
342,80
347,60
346,60
349,50
342,10
342,00
342,80
339,30
348,20
333,70
334,70
354,00
367,70
363,30
358,40
353,10
343,10
344,60
344,40
333,90
331,70
324,30
321,20
322,40
321,70
320,50
312,80
309,70
315,60
309,70
304,60
302,50
301,50
298,80
291,30
293,60
294,60
285,90
297,60
301,10
293,80
297,70
292,90
292,10
287,20
288,20
283,80
299,90
292,40
293,30
300,80
293,70
293,10
294,40
292,10
291,90
282,50
277,90
287,50
289,20
285,60
293,20
290,80
283,10
275,00
287,80
287,80
287,40
284,00
277,80
277,60
304,90
294,00
300,90
324,00
332,90
341,60
333,40
348,20
344,70
344,70
329,30
323,50
323,20
317,40
330,10
329,20
334,90
315,80
315,40
319,60
317,30
313,80
315,80
311,30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93383&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93383&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93383&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np+1))
darr <- array(NA,dim=c(par1,np+1))
ari <- array(0,dim=par1)
dx <- diff(x)
j <- 0
for (i in 1:n)
{
j = j + 1
ari[j] = ari[j] + 1
arr[j,ari[j]] <- x[i]
darr[j,ari[j]] <- dx[i]
if (j == par1) j = 0
}
ari
arr
darr
arr.mean <- array(NA,dim=par1)
arr.median <- array(NA,dim=par1)
arr.midrange <- array(NA,dim=par1)
for (j in 1:par1)
{
arr.mean[j] <- mean(arr[j,],na.rm=TRUE)
arr.median[j] <- median(arr[j,],na.rm=TRUE)
arr.midrange[j] <- (quantile(arr[j,],0.75,na.rm=TRUE) + quantile(arr[j,],0.25,na.rm=TRUE)) / 2
}
overall.mean <- mean(x)
overall.median <- median(x)
overall.midrange <- (quantile(x,0.75) + quantile(x,0.25)) / 2
bitmap(file='plot1.png')
plot(arr.mean,type='b',ylab='mean',main='Mean Plot',xlab='Periodic Index')
mtext(paste('#blocks = ',np))
abline(overall.mean,0)
dev.off()
bitmap(file='plot2.png')
plot(arr.median,type='b',ylab='median',main='Median Plot',xlab='Periodic Index')
mtext(paste('#blocks = ',np))
abline(overall.median,0)
dev.off()
bitmap(file='plot3.png')
plot(arr.midrange,type='b',ylab='midrange',main='Midrange Plot',xlab='Periodic Index')
mtext(paste('#blocks = ',np))
abline(overall.midrange,0)
dev.off()
bitmap(file='plot4.png')
z <- data.frame(t(arr))
names(z) <- c(1:par1)
(boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries'))
dev.off()
bitmap(file='plot4b.png')
z <- data.frame(t(darr))
names(z) <- c(1:par1)
(boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Differenced Periodic Subseries'))
dev.off()
bitmap(file='plot5.png')
z <- data.frame(arr)
names(z) <- c(1:np)
(boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks'))
dev.off()
bitmap(file='plot6.png')
z <- data.frame(cbind(arr.mean,arr.median,arr.midrange))
names(z) <- list('mean','median','midrange')
(boxplot(z,notch=TRUE,col='grey',ylab='Overall Central Tendency',main='Notched Box Plots'))
dev.off()