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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationMon, 27 Oct 2008 13:47:56 -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/Oct/27/t1225136941dqgx34z70byvizk.htm/, Retrieved Sun, 19 May 2024 14:39:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19506, Retrieved Sun, 19 May 2024 14:39:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [invoer vanuit vs] [2008-10-13 19:11:39] [57ce5bd741080980f0f51979adb31ad8]
F   PD  [Univariate Data Series] [Totale productie ...] [2008-10-19 13:44:22] [ed2ba3b6182103c15c0ab511ae4e6284]
F RMPD      [Univariate Explorative Data Analysis] [Totale productie ...] [2008-10-27 19:47:56] [a8228479d4547a92e2d3f176a5299609] [Current]
-   P         [Univariate Explorative Data Analysis] [Totale productie ...] [2008-10-29 14:28:38] [ed2ba3b6182103c15c0ab511ae4e6284]
Feedback Forum
2008-10-29 14:32:12 [Tom Ardies] [reply] 
De data is niet willekeurig. Bij lag 12 en 24 ziet men dat de autocorrelatie boven het betrouwbaarheidsinterval valt. http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/29/t1225290550o8dnl3wayqrgoeg.htm

De overige assumptie zijn correct geanalyseerd. Ik had de random component kunnen bekijken door de mediaan of gemiddelde van de reeks af te trekken.
2008-11-01 12:43:49 [Matthieu Blondeau] [reply] 
In de run sequence plot kan men terugkerende patronen vinden, wat wijst op seizoenaliteit. De histogram en density plot hebben inderdaad geen normaal verloop en de data in de lag plot vertonen een bepaalde structuur.
2008-11-03 09:06:44 [Jeroen Michel] [reply] 
Hier is er inderdaad spraken van seizoenaliteit. De links die je opgeeft geven inderdaad correcte informatie weer. Ook hier heb je de juiste conclusies getrokken.
2008-11-03 19:33:19 [Joris Deboel] [reply] 
We zien inderdaad dat er seizonaliteit is, verder zijn de asumpties correct, met de correcte conclusies

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
89.9
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
95.7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19506&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19506&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19506&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Descriptive Statistics
# observations60
minimum80.9
Q198.475
median105.6
mean105.095
Q3112.725
maximum122.4

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & 80.9 \tabularnewline
Q1 & 98.475 \tabularnewline
median & 105.6 \tabularnewline
mean & 105.095 \tabularnewline
Q3 & 112.725 \tabularnewline
maximum & 122.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19506&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]80.9[/C][/ROW]
[ROW][C]Q1[/C][C]98.475[/C][/ROW]
[ROW][C]median[/C][C]105.6[/C][/ROW]
[ROW][C]mean[/C][C]105.095[/C][/ROW]
[ROW][C]Q3[/C][C]112.725[/C][/ROW]
[ROW][C]maximum[/C][C]122.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19506&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19506&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Descriptive Statistics
# observations60
minimum80.9
Q198.475
median105.6
mean105.095
Q3112.725
maximum122.4


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 12 ;
Parameters (R input):
par1 = 0 ; par2 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
library(lattice)
bitmap(file='pic1.png')
plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(x)
grid()
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~x,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
} else {
densityplot(~x,col='black',main='Density Plot')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot1.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main='Lag plot (k=1), lowess, and regression line')
lines(lowess(z))
abline(lm(z))
dev.off()
if (par2 > 1) {
bitmap(file='lagplotpar2.png')
dum <- cbind(lag(x,k=par2),x)
dum
dum1 <- dum[(par2+1):length(x),]
dum1
z <- as.data.frame(dum1)
z
mylagtitle <- 'Lag plot (k='
mylagtitle <- paste(mylagtitle,par2,sep='')
mylagtitle <- paste(mylagtitle,'), and lowess',sep='')
plot(z,main=mylagtitle)
lines(lowess(z))
dev.off()
}
bitmap(file='pic5.png')
acf(x,lag.max=par2,main='Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(x,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(x,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')