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Description of Statistical Computation

Author's title

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

Author*The author of this computation has been verified*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationSun, 26 Oct 2008 10:46:50 -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/26/t1225039978xzmjtd51ywlzsvh.htm/, Retrieved Sat, 18 May 2024 02:40:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18979, Retrieved Sat, 18 May 2024 02:40:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

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] [Investigation val...] [2008-10-26 16:46:50] [8a2d94dac8ebd598299eaec920908ca6] [Current]
F   PD    [Univariate Explorative Data Analysis] [Investigation val...] [2008-10-27 19:40:22] [495cd80c1a9baafb03c09cd9ab8d8fb5]
F         [Univariate Explorative Data Analysis] [Investigating Values] [2008-10-27 21:29:19] [85841a4a203c2f9589565c024425a91b]
Feedback Forum
2008-11-03 10:04:59 [Joris Deboel] [reply] 
Veronderstelling 1: is inderdaad correct, in het begin zijn er twee uitschieters nadien niet meer.

Veronderstelling 2: Ook hier wordt een juiste conclusie getrokken.

Veronderstelling 3: Hier gaat de student naar het Q-Q plot kijken terwijl het aangeraden is om naar het run sequency plot te kijken.

Veronderstelling 4: hier trekt de student ook de juiste conclusie. Maar aan de hand van het run sequency plot zouden we toch al een kleine condlusie moeten kunnen trekken.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

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=18979&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=18979&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18979&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
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=18979&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=18979&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18979&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
minimum1.045036765
Q11.27926078
median1.395514781
mean1.45842537216393
Q31.562435501
maximum2.320652174


Figures (Output of Computation)

Input Parameters & R Code

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