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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 computationFri, 11 Dec 2009 13:05:01 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/11/t1260561938ztqhpqftdmhyrh9.htm/, Retrieved Mon, 29 Apr 2024 00:50:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66740, Retrieved Mon, 29 Apr 2024 00:50:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [ARIMA Backward Selection] [] [2009-11-27 14:53:14] [b98453cac15ba1066b407e146608df68]
-   PD    [ARIMA Backward Selection] [WS9] [2009-12-03 23:50:09] [37a8d600db9abe09a2528d150ccff095]
- RMPD      [Harrell-Davis Quantiles] [] [2009-12-04 21:24:16] [74be16979710d4c4e7c6647856088456]
- RMP         [Univariate Explorative Data Analysis] [] [2009-12-04 21:35:31] [74be16979710d4c4e7c6647856088456]
-    D            [Univariate Explorative Data Analysis] [] [2009-12-11 20:05:01] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D              [Univariate Explorative Data Analysis] [] [2009-12-14 17:14:02] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-0.0175986496695149
4.88533001639715e-06
-0.0797142045361252
0.0380359724366437
0.00379990057404902
0.0592823368877745
-0.0401047028912839
-0.0903371585255128
0.0600435985327014
-0.0751519168673696
0.184740243449584
0.108923749072312
0.148749967789766
0.0299253269806808
-0.132723413231867
0.130073522884216
-0.0524172791064149
-0.0488662775462986
0.0210676927748520
-0.165146636794414
-0.0573375413155754
0.00334278216483919
-0.120892947016097
0.0140181973103131
-0.166333957140904
-0.204256136740815
-0.170162160910135
-0.40685370432818
0.089890889862059
0.121852449126500
0.0718684968241188
0.146330323762528
-0.254402885578116
-0.175254145082071
0.0883657966655966
0.0494861859369645
-0.179560126045166
0.0352805435009704
0.107242027471589
0.0159604480893762
0.229492599513338
-0.472622684816943
-0.0310496393734398
0.0823390463619987
-0.0459447059808648
-0.0671207054879601
0.062392997118939
0.0541581853860086
-0.000768654964170624

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66740&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66740&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66740&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Descriptive Statistics
# observations49
minimum-0.472622684816943
Q1-0.0797142045361252
median0.00334278216483919
mean-0.0224071850641123
Q30.062392997118939
maximum0.229492599513338

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 49 \tabularnewline
minimum & -0.472622684816943 \tabularnewline
Q1 & -0.0797142045361252 \tabularnewline
median & 0.00334278216483919 \tabularnewline
mean & -0.0224071850641123 \tabularnewline
Q3 & 0.062392997118939 \tabularnewline
maximum & 0.229492599513338 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66740&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]49[/C][/ROW]
[ROW][C]minimum[/C][C]-0.472622684816943[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0797142045361252[/C][/ROW]
[ROW][C]median[/C][C]0.00334278216483919[/C][/ROW]
[ROW][C]mean[/C][C]-0.0224071850641123[/C][/ROW]
[ROW][C]Q3[/C][C]0.062392997118939[/C][/ROW]
[ROW][C]maximum[/C][C]0.229492599513338[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66740&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66740&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
# observations49
minimum-0.472622684816943
Q1-0.0797142045361252
median0.00334278216483919
mean-0.0224071850641123
Q30.062392997118939
maximum0.229492599513338


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)
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')