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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, 19 Dec 2009 17:55:27 -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/20/t12612706442ihzzch0nuoiqnb.htm/, Retrieved Sat, 27 Apr 2024 09:46:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69766, Retrieved Sat, 27 Apr 2024 09:46:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
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] [WS 3 I] [2009-10-24 22:53:45] [4a2be4899cba879e4eea9daa25281df8]
-  M D          [Univariate Explorative Data Analysis] [PAPER 1] [2009-12-20 00:55:27] [71c065898bd1c08eef04509b4bcee039] [Current]
-    D            [Univariate Explorative Data Analysis] [PAPER 4] [2009-12-20 01:07:41] [4a2be4899cba879e4eea9daa25281df8]
-    D            [Univariate Explorative Data Analysis] [paper 12] [2009-12-21 00:18:29] [4a2be4899cba879e4eea9daa25281df8]
- RMPD            [Central Tendency] [paper 13] [2009-12-21 00:48:00] [4a2be4899cba879e4eea9daa25281df8]
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Dataseries X:
144,63
124,24
135,21
119,80
102,79
109,42
99,61
83,02
95,29
116,18
81,25
71,35
128,63
134,85
167,22
147,01
104,08
111,61
82,63
80,48
93,46
104,55
87,97
63,36
136,50
117,44
133,53
121,53
102,82
124,11
82,47
85,96
90,34
90,80
84,80
49,10
146,65
135,41
158,36
124,67
122,70
108,72
83,33
79,52
83,55
96,35
79,77
42,99
142,84
121,85
140,67
118,67
115,19
118,30
93,70
85,76
93,73
113,70
90,93
58,46
144,86
138,19
137,77
146,55
118,52
123,15
92,73
81,64
94,17
103,34
71,46
52,82
116,78
110,56
127,52
120,22
94,15
104,45
87,32
77,88
91,95
103,19
85,96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69766&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69766&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69766&T=0

As an alternative you can also use a 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'Gwilym Jenkins' @ 72.249.127.135







Descriptive Statistics
# observations83
minimum42.99
Q185.96
median104.08
mean105.892048192771
Q3123.63
maximum167.22

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 83 \tabularnewline
minimum & 42.99 \tabularnewline
Q1 & 85.96 \tabularnewline
median & 104.08 \tabularnewline
mean & 105.892048192771 \tabularnewline
Q3 & 123.63 \tabularnewline
maximum & 167.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69766&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]83[/C][/ROW]
[ROW][C]minimum[/C][C]42.99[/C][/ROW]
[ROW][C]Q1[/C][C]85.96[/C][/ROW]
[ROW][C]median[/C][C]104.08[/C][/ROW]
[ROW][C]mean[/C][C]105.892048192771[/C][/ROW]
[ROW][C]Q3[/C][C]123.63[/C][/ROW]
[ROW][C]maximum[/C][C]167.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69766&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69766&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics
# observations83
minimum42.99
Q185.96
median104.08
mean105.892048192771
Q3123.63
maximum167.22



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')