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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 computationWed, 05 Nov 2008 12:36:09 -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/05/t1225913857fm8ryvxic6biga8.htm/, Retrieved Sun, 19 May 2024 09:19:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21913, Retrieved Sun, 19 May 2024 09:19:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordshundrasmet
Estimated Impact196

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 R PD    [Mean Plot] [workshop 1 task 1 Q3] [2008-11-05 19:36:09] [fb0a4305582623ea5408efbbf6f8b708] [Current]
F R P       [Mean Plot] [workshop 1 task 4 Q3] [2008-11-05 20:53:16] [923dc41d40e6465538c66cadc847dd5d]
Feedback Forum
2008-11-10 12:55:19 [Käthe Vanderheggen] [reply] 
Hundra ziet in dat de daling slechts geleidelijk gebeurt (de inkepingen overlappen wel). Maar de daling is toch significant omdat bij vergelijking van de eerste met de vijfde boxplot er toch wel een groot verschil is.
2008-11-10 17:26:00 [Hundra Smet] [reply] 
deze vraag is correct opgelost. er is inderdaad een daling over de jaren heen en de deze is niet significant (inkepingen overlappen niet)
2008-11-12 09:35:48 [Stef Vermeiren] [reply] 
Q3: De inkepingen overlappen elkaar dus de waarden zijn niet significant, ook al verschillen de medianen wel!

Maar men kan jaar 1 en 5 misschien wel vergelijken. Dit is namelijk eerder een twijfelgeval. Hier is echter meer odnerzoek en analyse voor nodig.

Het is is een dalende trend . de notches overlappen, dus dit is meer te wijten aan het toeval.
2008-11-12 10:19:35 [407693b66d7f2e0b350979005057872d] [reply] 
De medianen dalen jaar op jaar maar de inkepingen overlappen elkaar wel dus dit betekent dat het toeval kan zijn of de medianen lager liggen . Jaar 6 moeten we hier geen rekening mee houden omdat er hier te weinig metingenvoor zijn

2008-11-12 10:20:37 [407693b66d7f2e0b350979005057872d] [reply] 
Het antwoord is niet helemaal correct. De punten in de scatterplots van de Mean liggen ver uit elkaar, van de median liggen ze dichter bij elkaar dan de mean en van de midrange liggen de punten op 2 lijnen. Als we kijken naar de Boxplots dan zien we dat de midrange de kleinste variantie heeft dit geeft normaal ook het beste resultaat maar we zien dat de midrange tov de mean veel meer outliers heeft en is daarom minder betrouwbaar dan de mean die een relatief grote spreiding heeft

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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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21913&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21913&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21913&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'George Udny Yule' @ 72.249.76.132


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ;
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()