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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 computationWed, 22 Dec 2010 16:37:28 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/22/t1293036222p0u8swnzksxaemd.htm/, Retrieved Mon, 06 May 2024 09:16:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114393, Retrieved Mon, 06 May 2024 09:16:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Univariate Explorative Data Analysis] [] [2010-12-22 16:37:28] [4dba6678eac10ee5c3460d144a14bd5c] [Current]
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Dataseries X:
2342.32
2258.39
2293.62
2418.80
2480.15
2440.06
2660.66
2737.27
2692.82
2645.08
2706.27
2753.20
2590.54
2627.25
2707.21
2656.76
2876.66
2880.69
2905.20
2614.36
2452.48
2442.33
2559.65
2633.66
2736.39
2882.18
2913.86
2887.87
3027.50
2906.75
3024.82
3043.60
3016.77
3069.10
2894.68
3168.83
3223.39
3267.67
3235.47
3359.12
3396.88
3318.52
3393.78
3257.35
3271.66
3226.28
3305.16
3301.11
3310.03
3370.81
3435.11
3427.55
3527.43
3516.08
3539.47
3651.25
3555.12
3680.59
3683.95
3754.09
3978.36
3832.02
3635.96
3681.69
3758.37
3624.96
3764.50
3913.42
3843.19
3908.12
3739.23
3834.44
3843.86
4011.05
4157.69
4321.27
4465.14
4556.10
4708.47
4610.56
4789.08
4755.48
5074.49
5117.12
5395.30
5485.62
5587.14
5569.08
5643.18
5654.63
5528.91
5616.21
5882.17
6029.38
6521.70
6448.27
6813.09
6877.74
6583.48
7008.99
7331.04
7672.79
8222.61
7622.42
7945.26
7442.08
7823.13
7908.25
7906.50
8545.72
8799.81
9063.37
8899.95
8952.02
8883.29
7539.07
7842.62
8592.10
9116.55
9181.43
9358.83
9306.58
9786.16
10789.04
10559.74
10970.80
10655.15
10829.28
10336.95
10729.86
10877.81
11497.12
10940.53
10128.31
10921.92
10733.91
10522.33
10447.89
10521.98
11215.10
10650.92
10971.14
10414.49
10787.99
10887.36
10495.28
9878.78
10734.97
10911.94
10502.40
10522.81
9949.75
8847.56
9075.14
9851.56
10021.57
9920.00
10106.13
10403.94
9946.22
9925.25
9243.26
8736.59
8663.50
7591.93
8397.03
8896.09
8341.63
8053.81
7891.08
7992.13
8480.09
8850.26
8985.44
9233.80
9415.82
9275.06
9801.12
9782.46
10453.92
10488.07
10583.92
10357.70
10225.57
10188.45
10435.48
10139.71
10173.92
10080.27
10027.47
10428.02
10783.01
10489.94
10766.23
10503.76
10192.51
10467.48
10274.97
10640.91
10481.60
10568.70
10440.07
10805.87
10717.50
10864.86
10993.41
11109.32
11367.14
11168.31
11150.22
11185.68
11381.15
11679.07
12080.73
12221.93
12463.15
12621.69
12268.63
12354.35
13062.91
13627.64
13408.62
13211.99
13357.74
13895.63
13930.01
13371.72
13264.82
12650.36
12266.39
12262.89
12820.13
12638.32
11350.01
11378.02
11543.55
10850.66
9325.01
8829.04
8776.39
8000.86
7062.93
7608.92
8168.12
8500.33
8447.00
9171.61
9496.28
9712.28
9712.73
10344.84
10428.05




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=114393&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=114393&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114393&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
# observations252
minimum2258.39
Q13750.375
median8627.8
mean7632.8619047619
Q310497.06
maximum13930.01

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 252 \tabularnewline
minimum & 2258.39 \tabularnewline
Q1 & 3750.375 \tabularnewline
median & 8627.8 \tabularnewline
mean & 7632.8619047619 \tabularnewline
Q3 & 10497.06 \tabularnewline
maximum & 13930.01 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114393&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]252[/C][/ROW]
[ROW][C]minimum[/C][C]2258.39[/C][/ROW]
[ROW][C]Q1[/C][C]3750.375[/C][/ROW]
[ROW][C]median[/C][C]8627.8[/C][/ROW]
[ROW][C]mean[/C][C]7632.8619047619[/C][/ROW]
[ROW][C]Q3[/C][C]10497.06[/C][/ROW]
[ROW][C]maximum[/C][C]13930.01[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114393&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114393&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
# observations252
minimum2258.39
Q13750.375
median8627.8
mean7632.8619047619
Q310497.06
maximum13930.01



Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ;
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')