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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 12:50:07 -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/t12251335700mcqmg8q9i6vtb7.htm/, Retrieved Sun, 19 May 2024 14:46:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19403, Retrieved Sun, 19 May 2024 14:46:29 +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...] [2008-10-27 18:50:07] [708e5cce6cfef15b7edd0dea71956401] [Current]
-   P     [Univariate Explorative Data Analysis] [recomputation] [2008-11-03 10:55:59] [fe7291e888d31b8c4db0b24d6c0f75c6]
Feedback Forum
2008-11-03 11:02:28 [256f97d8b7c07ed49f142eff724c6520] [reply] 
Vergeten met lags te werken,
Link met lags:
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/03/t1225709833q6ebc9dwrn8pyqz.htm

Er is geen terugkerend patroon. Inderdaad geen gelijke spreiding van gegevens. De punten in Q-Q plot liggen allemaal ongeveer op 1 rechte, maar naarmate het einde kan je wel enkele outliers vaststellen.
2008-11-03 11:17:05 [256f97d8b7c07ed49f142eff724c6520] [reply] 
Hier ben je ook de lags vergeten.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.6
101.2
111.6
109.4
105.4
119.6
87.7
93.8
115.6
121.3
104.9
103.9
95.2
102
117.4
111.3
109.6
123
88.8
98.8
119.9
122.1
115.5
107.1
99.3
102.5
111.2
109.7
109.8
124.4
85.6
95.4
115.1
116.2
120
109.9
104
104.3
120.2
112.5
122.3
130
94.8
103.9
128.8
137.6
130.8
125.2
119.1
120.4
136.6
129.8
135.8
151
105
117.3
144.6
154.6
137.3
129
125.3

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'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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19403&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19403&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19403&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'George Udny Yule' @ 72.249.76.132






Descriptive Statistics
# observations61
minimum85.6
Q1104
median115.1
mean114.852459016393
Q3123
maximum154.6

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 85.6 \tabularnewline
Q1 & 104 \tabularnewline
median & 115.1 \tabularnewline
mean & 114.852459016393 \tabularnewline
Q3 & 123 \tabularnewline
maximum & 154.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19403&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]85.6[/C][/ROW]
[ROW][C]Q1[/C][C]104[/C][/ROW]
[ROW][C]median[/C][C]115.1[/C][/ROW]
[ROW][C]mean[/C][C]114.852459016393[/C][/ROW]
[ROW][C]Q3[/C][C]123[/C][/ROW]
[ROW][C]maximum[/C][C]154.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19403&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19403&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
minimum85.6
Q1104
median115.1
mean114.852459016393
Q3123
maximum154.6


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')