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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 computationSat, 18 Dec 2010 15:10:03 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/18/t12926850619k2z74rdqpxcpoe.htm/, Retrieved Tue, 30 Apr 2024 06:18:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112026, Retrieved Tue, 30 Apr 2024 06:18:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

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] [WS2] [2009-10-12 16:56:43] [4f76e114ed5e444b1133aad392380aad]
- RMPD    [Univariate Explorative Data Analysis] [Paper EDA Calculator] [2010-12-18 15:10:03] [33ba4313a043c7c916d0d88da7cd101b] [Current]
- RMP       [Central Tendency] [Paper CT Verkeers...] [2010-12-19 15:11:24] [abf4ff90b26c6b37be4a30063b404639]
- RMPD      [Central Tendency] [Paper CT Auto Ins...] [2010-12-19 15:15:16] [abf4ff90b26c6b37be4a30063b404639]
-    D      [Univariate Explorative Data Analysis] [] [2010-12-24 15:18:46] [dd4fe494cff2ee46c12b15bdc7b848ca]
- RMPD      [Histogram and QQPlot (Reddy-Moores Data)] [] [2010-12-24 15:38:57] [dd4fe494cff2ee46c12b15bdc7b848ca]
- RMPD      [Histogram and QQPlot (Reddy-Moores Data)] [] [2010-12-24 15:42:08] [dd4fe494cff2ee46c12b15bdc7b848ca]
- RMPD      [Histogram and QQPlot (Reddy-Moores Data)] [] [2010-12-24 15:43:22] [dd4fe494cff2ee46c12b15bdc7b848ca]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5124
4742
5434
5684
6332
6334
5636
5940
6195
6022
4535
4320
4872
4662
4663
5491
6018
6393
5610
5777
6094
6478
5216
5201
4784
4205
4681
4896
5752
6452
5995
5601
6119
6569
5798
5492
5018
4773
5502
5908
5902
6125
5419
5559
5962
6023
5346
5379
4859
5156
5010
5508
6426
6043
5499
5191
5790
5949
5219
4729

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'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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112026&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112026&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112026&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'Gwilym Jenkins' @ 72.249.127.135






Descriptive Statistics
# observations60
minimum4205
Q15097.5
median5533.5
mean5523.53333333333
Q36000.75
maximum6569

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & 4205 \tabularnewline
Q1 & 5097.5 \tabularnewline
median & 5533.5 \tabularnewline
mean & 5523.53333333333 \tabularnewline
Q3 & 6000.75 \tabularnewline
maximum & 6569 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112026&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]4205[/C][/ROW]
[ROW][C]Q1[/C][C]5097.5[/C][/ROW]
[ROW][C]median[/C][C]5533.5[/C][/ROW]
[ROW][C]mean[/C][C]5523.53333333333[/C][/ROW]
[ROW][C]Q3[/C][C]6000.75[/C][/ROW]
[ROW][C]maximum[/C][C]6569[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112026&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112026&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
minimum4205
Q15097.5
median5533.5
mean5523.53333333333
Q36000.75
maximum6569


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')