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Author's title

Investigation validity (productie kledij – investeringen) / totale producti...

Author*Unverified author*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationMon, 27 Oct 2008 13:40:22 -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/t12251365362diwnkbi28hchwf.htm/, Retrieved Sun, 19 May 2024 15:24:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19490, Retrieved Sun, 19 May 2024 15:24:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Explorative Data Analysis] [Investigation val...] [2008-10-26 16:46:50] [2d9298e0f43790a501ecec52b0f4048b]
F   PD    [Univariate Explorative Data Analysis] [Investigation val...] [2008-10-27 19:40:22] [46e0445318a71ab85f6f82e54c656dac] [Current]
Feedback Forum
2008-11-03 09:28:02 [Siem Van Opstal] [reply
Zeer goed nieuw model, met juiste conclusies

Post a new message
Dataseries X:
1.645833333
1.53526971
1.766437684
1.756120527
1.841975309
1.769799366
1.814851485
2.012797075
1.687194526
2.249173098
1.395010395
1.705515088
1.469811321
1.599418041
1.390196078
1.599808978
1.565116279
1.264929425
1.692235734
1.517761989
1.515240905
2.320652174
1.397330595
1.507216495
1.55313093
1.547224927
1.395514781
1.373205742
1.554919908
1.174638487
1.491803279
1.366159355
1.42494929
1.562435501
1.315457413
1.382474227
1.315882875
1.343051506
1.27926078
1.378815081
1.324942792
1.123966942
1.32427695
1.260199456
1.199230029
1.426181102
1.278012685
1.370177268
1.299904489
1.26848249
1.167176351
1.172958736
1.377008653
1.171368861
1.15459364
1.206798867
1.045036765
1.449657869
1.222222222
1.404170804
1.238961039




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 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 & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19490&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]9 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=19490&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19490&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 time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations61
minimum1.045036765
Q11.27926078
median1.395514781
mean1.45842537216393
Q31.562435501
maximum2.320652174

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 1.045036765 \tabularnewline
Q1 & 1.27926078 \tabularnewline
median & 1.395514781 \tabularnewline
mean & 1.45842537216393 \tabularnewline
Q3 & 1.562435501 \tabularnewline
maximum & 2.320652174 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19490&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]1.045036765[/C][/ROW]
[ROW][C]Q1[/C][C]1.27926078[/C][/ROW]
[ROW][C]median[/C][C]1.395514781[/C][/ROW]
[ROW][C]mean[/C][C]1.45842537216393[/C][/ROW]
[ROW][C]Q3[/C][C]1.562435501[/C][/ROW]
[ROW][C]maximum[/C][C]2.320652174[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19490&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19490&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
# observations61
minimum1.045036765
Q11.27926078
median1.395514781
mean1.45842537216393
Q31.562435501
maximum2.320652174



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')