Free Statistics

of Irreproducible Research!

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 computationTue, 23 Nov 2010 09:53:44 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/23/t1290505916iomq8c27s4llvtv.htm/, Retrieved Sun, 05 May 2024 11:38:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98882, Retrieved Sun, 05 May 2024 11:38:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
-    D  [Univariate Explorative Data Analysis] [Workshop 7 mini-t...] [2010-11-21 11:57:56] [87d60b8864dc39f7ed759c345edfb471]
-    D    [Univariate Explorative Data Analysis] [Ws 7 (2)] [2010-11-23 09:04:55] [717f3d787904f94c39256c5c1fc72d4c]
F    D        [Univariate Explorative Data Analysis] [Ws 7 (2)] [2010-11-23 09:53:44] [c1f1b5e209adb4577289f490325e36f2] [Current]
Feedback Forum
2010-11-27 14:37:34 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply
Gezien de student werkt met cijfers in verband met koersen is het opstellen van een 'run sequence plot' naar mijn mening een heel logische stap. Ook de interpretatie - dat er invloed zou kunnen zijn van de crisis - is naar mijn mening goed geformuleerd.

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Dataseries X:
1.3954	 
1.4790 	
1.4619 	
1.4670 	
1.4799 	 
1.4508 	
1.4678 	
1.4824 	
1.5189 	 
1.5348 	
1.5666 	
1.5446 	
1.5803 	
1.5718 	
1.5832 	
1.5801 	 
1.5605 	
1.5416 	 
1.5479 	
1.5580 	
1.5790 	 
1.5554  
1.5761 	
1.5360 	
1.5621 	
1.5773 
1.5710
1.5925 	
1.5844 	
1.5696 	
1.5540 	
1.5012 	
1.4676 	
1.4770 	
1.4660 	
1.4241 	
1.4214 	
1.4469 	
1.4618 	
1.3834 
1.3412 	
1.3437 	
1.2630 	
1.2759 	
1.2743 	
1.2797 	
1.2573 	
1.2705 	
1.2680 	
1.3371 	
1.3885 	
1.4060 	
1.3855	
1.3431	
1.3257	
1.2978	
1.2793	
1.2945	
1.2890	
1.2848	
1.2694	
1.2636	
1.2900	
1.3559	
1.3305	
1.3482	
1.3146	
1.3027	
1.3247	
1.3267	
1.3621	
1.3479	
1.4011	
1.4135	
1.3964	
1.4010	
1.3955	
1.4077	
1.3975	
1.3949	
1.4138	
1.4210	
1.4253	
1.4169	
1.4174	
1.4346	
1.4296	
1.4311	
1.4594	
1.4722	
1.4669	
1.4571	
1.4709	
1.4893	
1.4997	
1.4713
1.4846	
1.4914
1.4859	
1.4957
1.4843	
1.4619	
1.4340	
1.4426	
1.4318	




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98882&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98882&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98882&T=0

As an alternative you can also use a 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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations105
minimum1.2573
Q11.3482
median1.434
mean1.43158857142857
Q31.4914
maximum1.5925

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 105 \tabularnewline
minimum & 1.2573 \tabularnewline
Q1 & 1.3482 \tabularnewline
median & 1.434 \tabularnewline
mean & 1.43158857142857 \tabularnewline
Q3 & 1.4914 \tabularnewline
maximum & 1.5925 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98882&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]105[/C][/ROW]
[ROW][C]minimum[/C][C]1.2573[/C][/ROW]
[ROW][C]Q1[/C][C]1.3482[/C][/ROW]
[ROW][C]median[/C][C]1.434[/C][/ROW]
[ROW][C]mean[/C][C]1.43158857142857[/C][/ROW]
[ROW][C]Q3[/C][C]1.4914[/C][/ROW]
[ROW][C]maximum[/C][C]1.5925[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98882&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98882&T=1

As an alternative you can also use a QR Code:  

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

Descriptive Statistics
# observations105
minimum1.2573
Q11.3482
median1.434
mean1.43158857142857
Q31.4914
maximum1.5925



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
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')