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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 computationThu, 30 Oct 2008 15:56:10 -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/30/t1225404012w4sz3x3yn5vogpi.htm/, Retrieved Sat, 18 May 2024 20:16:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20182, Retrieved Sat, 18 May 2024 20:16:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

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...] [2007-10-22 19:45:25] [b9964c45117f7aac638ab9056d451faa]
F R  D  [Univariate Explorative Data Analysis] [Q7] [2008-10-26 14:53:24] [4300be8b33fd3dcdacd2aa9800ceba23]
F    D    [Univariate Explorative Data Analysis] [] [2008-10-27 20:23:41] [fd59abe368d8219a006d49608e51987e]
-   P       [Univariate Explorative Data Analysis] [Q7 Correctie] [2008-10-30 21:15:11] [547636b63517c1c2916a747d66b36ebf]
- R             [Univariate Explorative Data Analysis] [Q7 waarde - gemid...] [2008-10-30 21:56:10] [e11d930c9e2984715c66c796cf63ef19] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
356.2
359.5
368.4
371
397.5
416.7
413.2
424.3
415
421.7
422.1
429.2
452.1
471.5
488.3
506.2
517.3
538.6
545.3
546.7
540.3
549.2
563.9
581.7
590.7
594.1
604
628.1
662.4
688.6
705.9
701.5
686.2
645.7
668.7
696.7
715.5
741.4
754.3
771.3
797.7
809.9
790.1
830.3
847.7
834.8
824.5
764.6
780
803.2
751.1
755.2
708.2
685.4
680
710.6
702.8
656.3
575.6
567.2
545.2

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'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 & 6 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20182&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20182&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20182&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Descriptive Statistics
# observations61
minimum-256.445901639344
Q1-106.445901639344
median15.4540983606561
mean3.20525254789491e-13
Q3102.854098360656
maximum235.054098360656

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & -256.445901639344 \tabularnewline
Q1 & -106.445901639344 \tabularnewline
median & 15.4540983606561 \tabularnewline
mean & 3.20525254789491e-13 \tabularnewline
Q3 & 102.854098360656 \tabularnewline
maximum & 235.054098360656 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20182&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-256.445901639344[/C][/ROW]
[ROW][C]Q1[/C][C]-106.445901639344[/C][/ROW]
[ROW][C]median[/C][C]15.4540983606561[/C][/ROW]
[ROW][C]mean[/C][C]3.20525254789491e-13[/C][/ROW]
[ROW][C]Q3[/C][C]102.854098360656[/C][/ROW]
[ROW][C]maximum[/C][C]235.054098360656[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20182&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20182&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
minimum-256.445901639344
Q1-106.445901639344
median15.4540983606561
mean3.20525254789491e-13
Q3102.854098360656
maximum235.054098360656


Figures (Output of Computation)

Input Parameters & R Code

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)
x <- x -612.645901639344
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')