Free Statistics

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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 computationSat, 01 Nov 2008 05:04:36 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/01/t1225537524excne2bplqi9q4v.htm/, Retrieved Sun, 19 May 2024 12:38:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20347, Retrieved Sun, 19 May 2024 12:38:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact234
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Mean Plot] [workshop 3] [2007-10-26 12:14:28] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F    D    [Mean Plot] [Hypotheses Testin...] [2008-11-01 11:04:36] [dafd615cb3e0decc017580d68ecea30a] [Current]
F R         [Mean Plot] [Testing Hypothese...] [2008-11-01 14:30:28] [33f4701c7363e8b81858dafbf0350eed]
F             [Mean Plot] [T4] [2008-11-03 18:59:42] [b187fac1a1b0cb3920f54366df47fea3]
-               [Mean Plot] [task 4 , I] [2008-11-03 20:38:39] [1e82cb4c98d4057b5653dbe7a07f2cda]
F               [Mean Plot] [task 4] [2008-11-03 23:01:48] [b641c14ac36cb6fee377f3b099dcac19]
-               [Mean Plot] [] [2008-11-09 19:44:34] [888addc516c3b812dd7be4bd54caa358]
F    D      [Mean Plot] [Testing Hypothese...] [2008-11-01 15:12:37] [33f4701c7363e8b81858dafbf0350eed]
F    D        [Mean Plot] [T5] [2008-11-03 19:05:19] [b187fac1a1b0cb3920f54366df47fea3]
-               [Mean Plot] [Task 5] [2008-11-03 20:50:18] [1e82cb4c98d4057b5653dbe7a07f2cda]
F               [Mean Plot] [task 5] [2008-11-03 23:06:08] [b641c14ac36cb6fee377f3b099dcac19]
-               [Mean Plot] [] [2008-11-09 19:54:39] [888addc516c3b812dd7be4bd54caa358]
-               [Mean Plot] [] [2008-11-09 19:54:39] [888addc516c3b812dd7be4bd54caa358]
F           [Mean Plot] [T1 - Q2] [2008-11-03 18:44:09] [b187fac1a1b0cb3920f54366df47fea3]
F             [Mean Plot] [q2] [2008-11-03 22:50:51] [b641c14ac36cb6fee377f3b099dcac19]
-             [Mean Plot] [] [2008-11-09 18:39:24] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-11-09 14:14:02 [Bob Leysen] [reply
Het gaat hier ook om periodieke gemiddelden en geen waarden van een dataset. Er is een significant verschil voor de periode 7 (juli). Een mogelijke verklaring is dat data 6 ongeveer overeen komt met het begin van de zomer, de periode waarin mensen volop zomerkledij aankopen. We zien dat de productie hier op gang komt. Deze trend zet zich dan voort tot augustus om vervolgens weer af te bouwen (logisch, zomer loopt op zijn einde, mensen zullen minder geneigd zijn zomerkledij te kopen, productie volgt deze tendens en daalt). Ongeveer hetzelfde fenomeen doet zich voor in oktober, maar dan ditmaal omwille van de winter en de bijhorende winterkledij.
  2008-11-09 19:23:14 [Bob Leysen] [reply
De grafiek is correct.
2008-11-10 22:27:51 [Ilknur Günes] [reply
In je antwoord kan je beter ook een bestudering van de Notched Boxplot grafiek opnemen. Daar zie je bijvoorbeeld al beter dat 1 eigenlijk geen outlier is, want het valt in de getrouwheidsinterval van 2 EN 12. Bij 7 is er, zoals je zegt, sezonaliteit, vermits we een plotse stijging kunnen waarnemen.
2008-11-11 08:16:03 [Jeroen Michel] [reply
Net zoals in in mijn conclusie zeg (word document) gaat het hier inderdaad niet over 'waarden' van een dataset, maar over de gemiddelden periodiek gezien. Bij 7, wat overeenkomt met maand 7, juli, is er een outlier waar te nemen wat wijst op seizoenaliteit. Net zoals beschreven in het document kan dit er op duiden dat mensen meer kledij zullen aankopen. Vanaf oktober is er een vergelijkbare trend, dit is dan wel van toepassing voor de winterkledij.

De grafieken geven een correct beeld weer.
  2008-11-11 09:06:41 [Jeroen Michel] [reply
Een kleine rechtzetting hier! Maand 7 hier is september en NIET julie aangezien maand 1 hier overeenstemd met maart.

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Dataseries X:
109.20
88.60
94.30
98.30
86.40
80.60
104.10
108.20
93.40
71.90
94.10
94.90
96.40
91.10
84.40
86.40
88.00
75.10
109.70
103.00
82.10
68.00
96.40
94.30
90.00
88.00
76.10
82.50
81.40
66.50
97.20
94.10
80.70
70.50
87.80
89.50
99.60
84.20
75.10
92.00
80.80
73.10
99.80
90.00
83.10
72.40
78.80
87.30
91.00
80.10
73.60
86.40
74.50
71.20
92.40
81.50
85.30
69.90
84.20
90.70
100.30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20347&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20347&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20347&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135



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))
ari <- array(0,dim=par1)
j <- 0
for (i in 1:n)
{
j = j + 1
ari[j] = ari[j] + 1
arr[j,ari[j]] <- x[i]
if (j == par1) j = 0
}
ari
arr
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='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()