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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 computationWed, 21 Oct 2009 12:13:46 -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/21/t1256148957ezz083my7jol11m.htm/, Retrieved Thu, 02 May 2024 08:35:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49561, Retrieved Thu, 02 May 2024 08:35:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS3 deel 2 vraag 3 EDA
Estimated Impact150

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]
-           [Univariate Data Series] [WS3 deel 1 -EDA] [2009-10-20 19:35:12] [c620fe7250af73a91c51407172a85dab]
- RMPD          [Univariate Explorative Data Analysis] [WS3 deel 2 vraag ...] [2009-10-21 18:13:46] [b4ff140915b3f24d4faed3d78f95eba4] [Current]
- RMPD            [Harrell-Davis Quantiles] [WS3 deel 3] [2009-10-21 18:38:46] [c620fe7250af73a91c51407172a85dab]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,920720721
0,943119266
0,97
1,015217391
1,026086957
1,021052632
1,0125
1,021052632
1,024175824
1,042696629
0,988888889
0,942574257
0,92815534
0,945098039
1,002083333
1,036956522
1,049462366
1,061702128
1,072340426
1,091304348
1,111111111
1,077777778
1,011111111
0,904081633
0,86
0,883673469
0,941935484
0,977777778
0,988888889
0,991208791
0,98021978
0,958241758
0,960869565
0,972727273
0,971084337
0,997619048
1,014814815
1,031168831
0,997468354
0,984810127
1,0125
1,060759494
1,094736842
1,101408451
1,097058824
1,092307692
1,084057971
1,07804878
1,03908046
1,031325301
0,972151899
0,973333333
0,994871795
1,055421687
1,116666667
1,163414634
1,2
1,227777778
1,22739726
1,187654321
1,152941176

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=49561&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=49561&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49561&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
# observations61
minimum0.86
Q10.973333333
median1.015217391
mean1.02778183601639
Q31.077777778
maximum1.227777778

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.86 \tabularnewline
Q1 & 0.973333333 \tabularnewline
median & 1.015217391 \tabularnewline
mean & 1.02778183601639 \tabularnewline
Q3 & 1.077777778 \tabularnewline
maximum & 1.227777778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49561&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.86[/C][/ROW]
[ROW][C]Q1[/C][C]0.973333333[/C][/ROW]
[ROW][C]median[/C][C]1.015217391[/C][/ROW]
[ROW][C]mean[/C][C]1.02778183601639[/C][/ROW]
[ROW][C]Q3[/C][C]1.077777778[/C][/ROW]
[ROW][C]maximum[/C][C]1.227777778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49561&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49561&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
# observations61
minimum0.86
Q10.973333333
median1.015217391
mean1.02778183601639
Q31.077777778
maximum1.227777778


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')