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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 12:50:04 -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/t1225133456z8t3la8gcd9g21m.htm/, Retrieved Sun, 19 May 2024 16:31:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19402, Retrieved Sun, 19 May 2024 16:31:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Explorative Data Analysis] [Investigating Dis...] [2007-10-21 18:26:46] [b9964c45117f7aac638ab9056d451faa]
F    D    [Univariate Explorative Data Analysis] [Q2 Univariate exp...] [2008-10-27 18:50:04] [db9a5fd0f9c3e1245d8075d8bb09236d] [Current]
Feedback Forum
2008-11-03 18:42:30 [Stijn Van de Velde] [reply] 
Niet volledig juist.

Net zoals de student zegt zie je hier duidelijk bij de run sequence plot dat de grafiek op lange termijn EEN DALEND verloop kent. (en dus niet dat deze minder snel stijgt zoals ik in eerste instantie zei)
De kleding productie stemt dus niet overeen met de economische groei (deze stijgt wel op lange termijn).
2008-11-03 18:44:54 [Stijn Van de Velde] [reply] 
Q4:

Deze berekening is niet juist, want ook hier heb ik geen rekening met een lag gehouden.

Ik heb daarom de berekening van Q3 gereproduceerd en hierbij rekening gehouden met een lag=36.
link:http://www.freestatistics.org/blog/date/2008/Oct/31/t1225460439z3sin9nd3ps5kpq.htm

Als we naar de autocorrelatie grafiek kijken zien we dat er elke 12de maand zich een piek voordoet. Men kan hier dus spreken van seizoenaliteit.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.989130435
0.919087137
0.925417076
0.925612053
1.066666667
0.851108765
1.030693069
0.989031079
0.913000978
0.792723264
0.978170478
0.987513007
0.909433962
0.883608147
0.82745098
0.8252149
1.023255814
0.815418024
1.026192703
0.914742451
0.807276303
0.739130435
0.98973306
0.972164948
0.853889943
0.856864654
0.775739042
0.789473684
0.931350114
0.73971079
0.885245902
0.842435094
0.818458418
0.72755418
0.923238696
0.922680412
0.883762201
0.818270165
0.771047228
0.825852783
0.924485126
0.755165289
0.874671341
0.815956482
0.799807507
0.712598425
0.832980973
0.910323253
0.869149952
0.779182879
0.750254842
0.75856014
0.920889988
0.743991641
0.816254417
0.769593957
0.784007353
0.683284457
0.850505051
0.900695134
0.868398268

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19402&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]3 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=19402&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19402&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Descriptive Statistics
# observations61
minimum0.683284457
Q10.792723264
median0.853889943
mean0.86210009042623
Q30.922680412
maximum1.066666667

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.683284457 \tabularnewline
Q1 & 0.792723264 \tabularnewline
median & 0.853889943 \tabularnewline
mean & 0.86210009042623 \tabularnewline
Q3 & 0.922680412 \tabularnewline
maximum & 1.066666667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19402&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.683284457[/C][/ROW]
[ROW][C]Q1[/C][C]0.792723264[/C][/ROW]
[ROW][C]median[/C][C]0.853889943[/C][/ROW]
[ROW][C]mean[/C][C]0.86210009042623[/C][/ROW]
[ROW][C]Q3[/C][C]0.922680412[/C][/ROW]
[ROW][C]maximum[/C][C]1.066666667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19402&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19402&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
# observations61
minimum0.683284457
Q10.792723264
median0.853889943
mean0.86210009042623
Q30.922680412
maximum1.066666667


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Lag plot, lowess, and regression line'))
lines(lowess(z))
abline(lm(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')