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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 03:27:49 -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/t1225099765xh8vbokpudb1ftu.htm/, Retrieved Sun, 19 May 2024 12:58:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19136, Retrieved Sun, 19 May 2024 12:58:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

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] [Beurskoers Eurone...] [2008-10-13 22:20:32] [82970caad4b026be9dd352fdec547fe4]
-   PD  [Univariate Data Series] [Beurskoers Eurone...] [2008-10-20 20:09:06] [82970caad4b026be9dd352fdec547fe4]
F RMP       [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-27 09:27:49] [c33ddd06d9ea3933c8ac89c0e74c9b3a] [Current]
F RMP         [Tukey lambda PPCC Plot] [Investigating Dis...] [2008-10-27 10:05:32] [82970caad4b026be9dd352fdec547fe4]
-               [Tukey lambda PPCC Plot] [Investigating Dis...] [2008-11-03 08:50:35] [38f43994ada0e6172896e12525dcc585]
F RMP         [Harrell-Davis Quantiles] [Investigating Dis...] [2008-10-27 10:20:53] [82970caad4b026be9dd352fdec547fe4]
-   P         [Univariate Explorative Data Analysis] [Verbetering Q7 va...] [2008-10-30 14:13:28] [73d6180dc45497329efd1b6934a84aba]
-   PD        [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-11-03 08:22:22] [38f43994ada0e6172896e12525dcc585]
Feedback Forum
2008-10-30 15:12:48 [Gregory Van Overmeiren] [reply] 
Om te zien of er daadwerkelijk een dalend verloop is kan je best je aantal lags op 36 zetten. Zo kom je net iets meer te weten. Als je dit doet zie je dat je idd te maken hebt met een dalend verloop.
(http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/30/t1225376260hm47supij5q3g3g.htm )

Als je dan kijkt naar je lag plot zou ik stellen dat je hier te maken hebt met een negatieve correlatie.

Je hebt hier ook idd te maken met een normaalverdeling (geen perfecte maar komt dicht in de buurt ) Dit kan je zien adhv het density plot.
2008-11-03 10:09:14 [Karen Van den Broeck] [reply] 
Je hebt dit goed opgelost.
Aan de hand van het density plot kan je zien of het normaal verdeeld is . Als we dit bekijken zien we dat het gaat om een normaalverdeling. Deze normaalverdeling is hier wel niet perfect.

Je algemene conclusie is ook goed. Omdat niet aan alle 4 de voorwaarden voldaan is, is het geen geldig model.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 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=19136&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]6 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=19136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19136&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 time6 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Descriptive Statistics
# observations60
minimum2120.88
Q12952.115
median3499.27
mean3444.10433333333
Q34003.87
maximum4696.96

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & 2120.88 \tabularnewline
Q1 & 2952.115 \tabularnewline
median & 3499.27 \tabularnewline
mean & 3444.10433333333 \tabularnewline
Q3 & 4003.87 \tabularnewline
maximum & 4696.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19136&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]2120.88[/C][/ROW]
[ROW][C]Q1[/C][C]2952.115[/C][/ROW]
[ROW][C]median[/C][C]3499.27[/C][/ROW]
[ROW][C]mean[/C][C]3444.10433333333[/C][/ROW]
[ROW][C]Q3[/C][C]4003.87[/C][/ROW]
[ROW][C]maximum[/C][C]4696.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19136&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
minimum2120.88
Q12952.115
median3499.27
mean3444.10433333333
Q34003.87
maximum4696.96


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')