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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_meanplot.wasp
Title produced by softwareMean Plot
Date of computationMon, 03 Nov 2008 12:12:34 -0700
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/03/t1225739595mc1jcspliuwyv4a.htm/, Retrieved Sun, 19 May 2024 12:06:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21014, Retrieved Sun, 19 May 2024 12:06:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

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] [Mean plot] [2008-11-03 19:12:34] [9ba97de59bb4d2edf0cfeac4ca7d2b73] [Current]
F R P       [Mean Plot] [Mean plot] [2008-11-03 20:26:03] [8b0d202c3a0c4ea223fd8b8e731dacd8]
F R PD      [Mean Plot] [Mean plot Diesel] [2008-11-03 20:41:03] [8b0d202c3a0c4ea223fd8b8e731dacd8]
- RMPD      [Kendall tau Correlation Matrix] [Correlatie] [2008-11-03 21:09:38] [8b0d202c3a0c4ea223fd8b8e731dacd8]
- RMPD      [Star Plot] [Star plot] [2008-11-03 21:19:51] [8b0d202c3a0c4ea223fd8b8e731dacd8]
- RMPD      [Notched Boxplots] [Notched boxplots: Q3] [2008-11-03 21:40:54] [8b0d202c3a0c4ea223fd8b8e731dacd8]
-   P       [Mean Plot] [feedback op hypot...] [2008-11-04 22:28:12] [b635de6fc42b001d22cbe6e730fec936]
Feedback Forum
2008-11-04 22:31:53 [Bas van Keken] [reply] 
De drie vragen die ontstaan bij de meanplot (EDA 1.3.3.20) zijn:

1. Are there any shifts in location?
2. What is the magnitude of the shifts in location?
3. Is there a distinct pattern in the shifts in location?

De laatste vraag is nu van toepassing. Seizoensgebondenheid betekent of er over de jaren overeenkomsten zijn tussen de seizoenen. Men moet hiervoor de periode in de module verhogen. In de onderstaande link heb ik deze verhoogd naar 60:
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/04/t12258377661d18fzmhf4domw4.htm

Er is nu geen (seizoens)patroon waar te nemen.
  2008-11-05 14:37:18 [Bas van Keken] [reply] 
Excuses, deze opmerking klopt niet. De periode is juist en ook de interpretatie.
2008-11-05 16:02:39 [Bas van Keken] [reply] 
De betrouwbaarheidsintervallen van de boxplots komen allemaal overeen. Dit zijn de inkepingen in de boxplots en niet de stippellijnen. De stijging in het zesde jaar komt waarschijnlijk wel door goede resultaten de eerste maanden, maar zal hoogstwaarschijnlijk worden bijgesteld naarmate het jaar vordert. Voor de vraagstelling is de tweede vraag uit het handboek nu de belangrijkste vraag (in plaats van vraag3 zoals eerder gesteld).

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





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=21014&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=21014&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21014&T=0

As an alternative you can also use a QR Code:  
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


Figures (Output of Computation)

Input Parameters & R Code

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()