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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, 19 Oct 2009 02:06:26 -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/2009/Oct/19/t1255939618il5v5fodklay2vi.htm/, Retrieved Mon, 29 Apr 2024 19:00:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=47592, Retrieved Mon, 29 Apr 2024 19:00:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
-    D      [Univariate Data Series] [Workshop 3 Part 2...] [2009-10-16 16:18:18] [f924a0adda9c1905a1ba8f1c751261ff]
-    D        [Univariate Data Series] [Part 2: Y[t] / X[t]] [2009-10-17 12:08:18] [f924a0adda9c1905a1ba8f1c751261ff]
- RMPD            [Univariate Explorative Data Analysis] [Part 2: Y[t] / X[...] [2009-10-19 08:06:26] [ac86848d66148c9c4c9404e0c9a511eb] [Current]
- RMP               [Harrell-Davis Quantiles] [] [2009-11-26 08:46:38] [2c5be225250d91402426bbbf07a5e2b3]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.726312915
0.871109254
0.92312693
0.914985007
0.864649152
0.952917714
0.89673913
0.928465368
0.976293267
0.902078597
0.866015822
1.013092269
0.775124733
0.837080264
0.887078525
0.843943846
0.840667678
0.904054597
0.847387566
0.91680261
0.931830676
0.886396222
0.951210428
1.002194587
0.74977342
0.810713966
0.910578783
0.895750091
0.901639344
1.001920347
0.903665162
0.927658248
0.96778569
0.962466905
0.946676406
1.053143453
0.813919198
0.809928152
0.953738215
0.889963408
0.908836101
1.036773044
0.842280252
0.929182347
0.974188741
0.93054066
0.924016282
0.948803393
0.797335748
0.828050713
0.888408744
0.885501135
0.909828748
1.048023348
0.854685378
0.900766047
0.909833388
0.863134082
0.784979884
0.91875595

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47592&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47592&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47592&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Descriptive Statistics
# observations60
minimum0.726312915
Q10.861021906
median0.9038598795
mean0.9007133655
Q30.9355421085
maximum1.053143453

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & 0.726312915 \tabularnewline
Q1 & 0.861021906 \tabularnewline
median & 0.9038598795 \tabularnewline
mean & 0.9007133655 \tabularnewline
Q3 & 0.9355421085 \tabularnewline
maximum & 1.053143453 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47592&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]0.726312915[/C][/ROW]
[ROW][C]Q1[/C][C]0.861021906[/C][/ROW]
[ROW][C]median[/C][C]0.9038598795[/C][/ROW]
[ROW][C]mean[/C][C]0.9007133655[/C][/ROW]
[ROW][C]Q3[/C][C]0.9355421085[/C][/ROW]
[ROW][C]maximum[/C][C]1.053143453[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47592&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47592&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
# observations60
minimum0.726312915
Q10.861021906
median0.9038598795
mean0.9007133655
Q30.9355421085
maximum1.053143453


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')