Free Statistics

of Irreproducible Research!

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, 02 Nov 2010 12:07:39 +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/Nov/02/t1288699624lmcgi5o6s7m41zi.htm/, Retrieved Fri, 29 Mar 2024 14:25:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91291, Retrieved Fri, 29 Mar 2024 14:25:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact890
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Univariate Explorative Data Analysis] [Monthly US soldie...] [2010-11-02 12:07:39] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- RMP     [(Partial) Autocorrelation Function] [Soldiers] [2010-11-29 09:48:36] [b98453cac15ba1066b407e146608df68]
-   PD      [(Partial) Autocorrelation Function] [] [2010-12-03 11:32:19] [8a9a6f7c332640af31ddca253a8ded58]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-03 14:12:17] [8a9a6f7c332640af31ddca253a8ded58]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-03 14:14:33] [8a9a6f7c332640af31ddca253a8ded58]
-    D          [(Partial) Autocorrelation Function] [] [2010-12-07 13:28:58] [f72e5115d7374b3b3f29ba3966e5379d]
-   P             [(Partial) Autocorrelation Function] [] [2010-12-07 15:13:37] [f72e5115d7374b3b3f29ba3966e5379d]
-   P             [(Partial) Autocorrelation Function] [] [2010-12-07 15:20:07] [f72e5115d7374b3b3f29ba3966e5379d]
- RMP             [Variance Reduction Matrix] [] [2010-12-07 15:29:14] [f72e5115d7374b3b3f29ba3966e5379d]
- RMP             [Standard Deviation-Mean Plot] [] [2010-12-07 15:39:58] [f72e5115d7374b3b3f29ba3966e5379d]
- RMP             [Spectral Analysis] [] [2010-12-07 16:29:36] [f72e5115d7374b3b3f29ba3966e5379d]
- RMP             [Spectral Analysis] [] [2010-12-07 16:34:30] [f72e5115d7374b3b3f29ba3966e5379d]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-17 14:07:41] [8a9a6f7c332640af31ddca253a8ded58]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-17 14:09:32] [8a9a6f7c332640af31ddca253a8ded58]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-17 14:11:00] [8a9a6f7c332640af31ddca253a8ded58]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-14 12:47:55] [9b13650c94c5192ca5135ec8a1fa39f7]
-   PD      [(Partial) Autocorrelation Function] [Workshop 9] [2010-12-14 12:34:06] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
-             [(Partial) Autocorrelation Function] [Workshop 9] [2010-12-14 13:09:27] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
- R P         [(Partial) Autocorrelation Function] [] [2011-01-10 20:58:25] [a7c91bc614e4e21e8b9c8593f39a36f1]
- R PD      [(Partial) Autocorrelation Function] [WS9_autocorrelation] [2011-12-06 18:22:15] [2adcc8dcd741502b8a9375c7fd3d7ce3]
- RMPD      [Spectral Analysis] [WS9_spectral-anal...] [2011-12-06 18:23:40] [2adcc8dcd741502b8a9375c7fd3d7ce3]
- RM          [Spectral Analysis] [P AF] [2011-12-17 17:18:03] [9ef609fa6add02911e58c08267119249]
- RMPD      [Variance Reduction Matrix] [WS9_variance-redu...] [2011-12-06 18:25:03] [2adcc8dcd741502b8a9375c7fd3d7ce3]
- RM          [Variance Reduction Matrix] [VRM] [2011-12-17 17:23:33] [9ef609fa6add02911e58c08267119249]
- R P       [(Partial) Autocorrelation Function] [Soldiers autocorr...] [2012-12-01 14:17:53] [22a7ed72f77de7f3efc5689ed05063a7]
- R P         [(Partial) Autocorrelation Function] [Soldiers] [2012-12-01 14:22:50] [22a7ed72f77de7f3efc5689ed05063a7]
-   P           [(Partial) Autocorrelation Function] [Soldiers] [2012-12-01 14:26:54] [22a7ed72f77de7f3efc5689ed05063a7]
- RMP           [Spectral Analysis] [Soldiers] [2012-12-01 14:31:07] [22a7ed72f77de7f3efc5689ed05063a7]
- RMP           [Variance Reduction Matrix] [Soldiers VRM] [2012-12-01 14:39:07] [22a7ed72f77de7f3efc5689ed05063a7]
- R P       [(Partial) Autocorrelation Function] [] [2012-12-04 15:50:48] [74be16979710d4c4e7c6647856088456]
- R P       [(Partial) Autocorrelation Function] [] [2012-12-04 15:53:51] [74be16979710d4c4e7c6647856088456]
- R P       [(Partial) Autocorrelation Function] [paper arima acf] [2012-12-12 18:35:45] [74be16979710d4c4e7c6647856088456]
- RMP     [Spectral Analysis] [Soldiers] [2010-11-29 09:50:20] [b98453cac15ba1066b407e146608df68]
-    D      [Spectral Analysis] [CP] [2010-12-04 08:37:02] [c1605865773cc027e55b238d879a644c]
- R PD        [Spectral Analysis] [] [2010-12-10 11:15:17] [22937c5b58c14f6c22964f32d64ff823]
-   PD        [Spectral Analysis] [Cumulatief period...] [2010-12-12 14:28:13] [c1605865773cc027e55b238d879a644c]
-    D      [Spectral Analysis] [ws 9] [2010-12-14 12:45:12] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
-   P         [Spectral Analysis] [ws 9] [2010-12-14 13:12:01] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
- RM            [Standard Deviation-Mean Plot] [] [2010-12-14 13:28:34] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
- RM              [ARIMA Backward Selection] [] [2010-12-14 13:51:17] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
- R         [Spectral Analysis] [WS 9 - Cumulatiev...] [2011-12-01 16:49:05] [6a3e51c0c7ab195427042dfaef1df5a0]
-   P         [Spectral Analysis] [WS 9 - Cumulatiev...] [2011-12-01 16:54:15] [6a3e51c0c7ab195427042dfaef1df5a0]
-   PD      [Spectral Analysis] [Spectrum Analysis] [2011-12-07 13:53:52] [57eb71340681272e66d705d5c4d9e797]
- RM          [Spectral Analysis] [Spectrum analyses] [2011-12-21 13:00:05] [57eb71340681272e66d705d5c4d9e797]
- RM          [Spectral Analysis] [Spectrum analyses] [2011-12-21 13:00:05] [57eb71340681272e66d705d5c4d9e797]
- R P         [Spectral Analysis] [Spectrum analyses -] [2011-12-21 13:01:57] [57eb71340681272e66d705d5c4d9e797]
- RMPD      [Variance Reduction Matrix] [Variance Reductio...] [2011-12-07 13:59:45] [57eb71340681272e66d705d5c4d9e797]
- R P         [Variance Reduction Matrix] [Variance Reductio...] [2011-12-21 13:09:12] [57eb71340681272e66d705d5c4d9e797]
- R P       [Spectral Analysis] [PR CP Diff.] [2011-12-14 15:43:50] [b8fde34a99ee6a7d49500940cae4da2a]

[Truncated]
Feedback Forum

Post a new message
Dataseries X:
37
30
47
35
30
43
82
40
47
19
52
136
80
42
54
66
81
63
137
72
107
58
36
52
79
77
54
84
48
96
83
66
61
53
30
74
69
59
42
65
70
100
63
105
82
81
75
102
121
98
76
77
63
37
35
23
40
29
37
51
20
28
13
22
25
13
16
13
16
17
9
17
25
14
8
7
10
7
10
3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91291&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]2 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=91291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91291&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Descriptive Statistics
# observations80
minimum3
Q125
median49.5
mean51.8
Q375.25
maximum137

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 80 \tabularnewline
minimum & 3 \tabularnewline
Q1 & 25 \tabularnewline
median & 49.5 \tabularnewline
mean & 51.8 \tabularnewline
Q3 & 75.25 \tabularnewline
maximum & 137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91291&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]80[/C][/ROW]
[ROW][C]minimum[/C][C]3[/C][/ROW]
[ROW][C]Q1[/C][C]25[/C][/ROW]
[ROW][C]median[/C][C]49.5[/C][/ROW]
[ROW][C]mean[/C][C]51.8[/C][/ROW]
[ROW][C]Q3[/C][C]75.25[/C][/ROW]
[ROW][C]maximum[/C][C]137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91291&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
# observations80
minimum3
Q125
median49.5
mean51.8
Q375.25
maximum137



Parameters (Session):
par1 = 8 ; par2 = 11 ; par3 = TRUE ;
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')