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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, 22 Oct 2009 14:33:00 -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/22/t12562436517sisjn9zjtjpg5s.htm/, Retrieved Thu, 02 May 2024 21:10:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49822, Retrieved Thu, 02 May 2024 21:10:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKVN WS3
Estimated Impact170

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]
- RMPD      [Central Tendency] [] [2009-10-20 15:12:09] [90f6d58d515a4caed6fb4b8be4e11eaa]
-    D        [Central Tendency] [] [2009-10-20 15:25:16] [90f6d58d515a4caed6fb4b8be4e11eaa]
- RMPD          [Univariate Explorative Data Analysis] [] [2009-10-20 17:46:31] [90f6d58d515a4caed6fb4b8be4e11eaa]
-    D              [Univariate Explorative Data Analysis] [WS3 Q2 Yt-Xt] [2009-10-22 20:33:00] [f1100e00818182135823a11ccbd0f3b9] [Current]
-    D                [Univariate Explorative Data Analysis] [WS3 Q2 Yt-Xt Assu...] [2009-10-23 07:32:53] [1b4c3bbe3f2ba180dd536c5a6a81a8e6]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5018
3246
4078
2960
1624
147
2188
-71
1422
3281
3453
3844
4916
3029
3424
3142
1039
1003
2263
-116
1546
2972
3529
4024
4793
3252
4150
2299
1084
1526
1242
1325
1563
3128
4002
4358
4821
3638
4698
2805
1800
1717
881
1544
1442
3737
3964
4214
5290
3823
4624
2888
2461
1259
1457
1493
1093
4367
4507
3707

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=49822&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=49822&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49822&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
# observations60
minimum-116
Q11517.75
median3000.5
mean2781.88333333333
Q33973.5
maximum5290

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & -116 \tabularnewline
Q1 & 1517.75 \tabularnewline
median & 3000.5 \tabularnewline
mean & 2781.88333333333 \tabularnewline
Q3 & 3973.5 \tabularnewline
maximum & 5290 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49822&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]-116[/C][/ROW]
[ROW][C]Q1[/C][C]1517.75[/C][/ROW]
[ROW][C]median[/C][C]3000.5[/C][/ROW]
[ROW][C]mean[/C][C]2781.88333333333[/C][/ROW]
[ROW][C]Q3[/C][C]3973.5[/C][/ROW]
[ROW][C]maximum[/C][C]5290[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49822&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49822&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
minimum-116
Q11517.75
median3000.5
mean2781.88333333333
Q33973.5
maximum5290


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')