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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, 24 Oct 2009 03:15:42 -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/24/t12563758746ig08akvkv3g3cb.htm/, Retrieved Fri, 03 May 2024 12:33:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50040, Retrieved Fri, 03 May 2024 12:33:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
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]
-   PD      [Univariate Data Series] [y[t]/x[t]= c+e[t]] [2009-10-17 12:00:47] [f7fc9270f813d017f9fa5b506fdc7682]
- RMPD          [Univariate Explorative Data Analysis] [WS 3 Review 1 part 2] [2009-10-24 09:15:42] [eba9f01697e64705b70041e6f338cb22] [Current]
- RMP             [Central Tendency] [WS 3 Review 1 part 2] [2009-10-24 09:23:42] [83058a88a37d754675a5cd22dab372fc]
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Dataseries X:
4.241
4.336
4.452
4.567
4.737
4.800
4.091
3.738
3.750
3.914
4.092
4.206
4.269
4.355
4.421
4.534
4.684
4.720
3.959
3.662
3.667
3.814
4.032
4.143
4.212
4.297
4.396
4.485
4.632
4.641
3.765
3.559
3.568
3.733
3.907
3.997
4.086
4.208
4.332
4.484
4.622
4.564
3.777
3.643
3.660
3.827
3.980
4.052
4.130
4.217
4.423
4.543
4.701
4.671
3.884
3.776
3.806
4.090
4.268
4.424
4.534
4.655
4.775
4.884
5.060
5.041
4.174
4.000
3.996
4.173
4.361
4.520
4.735
4.808
4.972
5.049
5.172
5.111
4.316
4.174
4.156
4.374
4.611
4.820
4.809
4.933
5.082
5.166
5.405
5.359
4.474
4.331
4.370
4.584
4.831
4.901
4.933
5.011
5.210
5.257
5.586
5.459
4.560
4.434
4.427
4.652
4.802
4.835
4.831
4.883
4.953
5.036
5.278
5.181
4.489
4.341
4.310




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50040&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50040&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50040&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations117
minimum3.559
Q14.13
median4.434
mean4.45921367521368
Q34.808
maximum5.586

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 117 \tabularnewline
minimum & 3.559 \tabularnewline
Q1 & 4.13 \tabularnewline
median & 4.434 \tabularnewline
mean & 4.45921367521368 \tabularnewline
Q3 & 4.808 \tabularnewline
maximum & 5.586 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50040&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]117[/C][/ROW]
[ROW][C]minimum[/C][C]3.559[/C][/ROW]
[ROW][C]Q1[/C][C]4.13[/C][/ROW]
[ROW][C]median[/C][C]4.434[/C][/ROW]
[ROW][C]mean[/C][C]4.45921367521368[/C][/ROW]
[ROW][C]Q3[/C][C]4.808[/C][/ROW]
[ROW][C]maximum[/C][C]5.586[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50040&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50040&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
# observations117
minimum3.559
Q14.13
median4.434
mean4.45921367521368
Q34.808
maximum5.586



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')