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 computationMon, 22 Nov 2010 18:46:05 +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/22/t1290452482aplvaawgrq3t9zs.htm/, Retrieved Fri, 03 May 2024 22:10:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98659, Retrieved Fri, 03 May 2024 22:10:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
F    D    [Univariate Explorative Data Analysis] [Mini-tutorial Seq...] [2010-11-22 18:46:05] [b4ba846736d082ffaee409a197f454c7] [Current]
Feedback Forum
2010-11-27 10:06:24 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply
De student heeft hier op een correcte wijze een 'run sequence plot' en ook de conclusies van de student in verband met het vervolg van het onderzoek naar meervoudige regressie zijn naar mijn mening correct. Het is volgens deze grafiek inderdaad niet relevant om de invloed van de maand te onderzoeken.

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Dataseries X:
69
53
43
60
49
62
45
50
75
82
60
59
21
40
62
54
47
59
37
43
48
79
62
16
38
58
60
72
67
55
47
59
49
47
57
39
49
26
53
75
65
49
48
45
31
67
61
49
69
54
80
57
34
69
44
70
51
66
18
74
59
48
55
44
56
65
77
46
70
39
55
44
45
45
25
49
65
45
71
48
41
40
64
56
52
41
45
42
54
40
40
51
48
80
38
57
51
46
58
67
72
26
54
53
69
64
47
43
66
54
62
52
64
55
74
32
38
66
37
26
64
28
65
48
44
64
39
50
52
48
70
66
61
31
61
54
34
62
47
52
37
46
61
70
63
34
46
40
30
35
51
56
44
58




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 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 & 16 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98659&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]16 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=98659&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98659&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 time16 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations154
minimum16
Q144
median52
mean52.2987012987013
Q362
maximum82

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 154 \tabularnewline
minimum & 16 \tabularnewline
Q1 & 44 \tabularnewline
median & 52 \tabularnewline
mean & 52.2987012987013 \tabularnewline
Q3 & 62 \tabularnewline
maximum & 82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98659&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]154[/C][/ROW]
[ROW][C]minimum[/C][C]16[/C][/ROW]
[ROW][C]Q1[/C][C]44[/C][/ROW]
[ROW][C]median[/C][C]52[/C][/ROW]
[ROW][C]mean[/C][C]52.2987012987013[/C][/ROW]
[ROW][C]Q3[/C][C]62[/C][/ROW]
[ROW][C]maximum[/C][C]82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98659&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98659&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
# observations154
minimum16
Q144
median52
mean52.2987012987013
Q362
maximum82



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')