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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 computationTue, 20 Oct 2009 15:27:32 -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/20/t1256074226wv1aj0ygwthsic9.htm/, Retrieved Thu, 02 May 2024 14:58:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49195, Retrieved Thu, 02 May 2024 14:58:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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      [Univariate Explorative Data Analysis] [Workshop3 - histo...] [2009-10-20 19:05:41] [df6326eec97a6ca984a853b142930499]
-   PD          [Univariate Explorative Data Analysis] [Workshop 3 centra...] [2009-10-20 21:27:32] [0cc924834281808eda7297686c82928f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
423,4
404,1
500
472,6
496,1
562
434,8
538,2
577,6
518,1
625,2
561,2
523,3
536,1
607,3
637,3
606,9
652,9
617,2
670,4
729,9
677,2
710
844,3
748,2
653,9
742,6
854,2
808,4
1819
1936,5
1966,1
2083,1
1620,1
1527,6
1795
1685,1
1851,8
2164,4
1981,8
1726,5
2144,6
1758,2
1672,9
1837,3
1596,1
1446
1898,4
1964,1
1755,9
2255,3
1881,2
2117,9
1656,5
1544,1
2098,9
2133,3
1963,5
1801,2
2365,4
1936,5
1667,6
1983,5
2058,6
2448,3
1858,1
1625,4
2130,6
2515,7
2230,2
2086,9
2235
2100,2
2288,6
2490
2573,7
2543,8
2004,7
2390
2338,4
2724,5
2292,5
2386
2477,9
2337
2605,1
2560,8
2839,3
2407,2
2085,2
2735,6
2798,7
3053,2
2405
2471,9
2727,3
2790,7
2385,4
3206,6
2705,6
3518,4
1954,9
2584,3
2535,8
2685,9
2866
2236,6
2934,9
2668,6
2371,2
3165,9
2887,2
3112,2
2671,2
2432,6
2812,3
3095,7
2862,9
2607,3
2862,5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49195&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49195&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49195&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Descriptive Statistics
# observations120
minimum404.1
Q11507.2
median2070.85
mean1884.57416666667
Q32496.425
maximum3518.4

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 120 \tabularnewline
minimum & 404.1 \tabularnewline
Q1 & 1507.2 \tabularnewline
median & 2070.85 \tabularnewline
mean & 1884.57416666667 \tabularnewline
Q3 & 2496.425 \tabularnewline
maximum & 3518.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49195&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]120[/C][/ROW]
[ROW][C]minimum[/C][C]404.1[/C][/ROW]
[ROW][C]Q1[/C][C]1507.2[/C][/ROW]
[ROW][C]median[/C][C]2070.85[/C][/ROW]
[ROW][C]mean[/C][C]1884.57416666667[/C][/ROW]
[ROW][C]Q3[/C][C]2496.425[/C][/ROW]
[ROW][C]maximum[/C][C]3518.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49195&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49195&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
# observations120
minimum404.1
Q11507.2
median2070.85
mean1884.57416666667
Q32496.425
maximum3518.4


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 12 ;
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')