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 computationFri, 24 Dec 2010 15:16:17 +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/24/t12932036449y2cpyxx6gol1g4.htm/, Retrieved Tue, 30 Apr 2024 06:19:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115093, Retrieved Tue, 30 Apr 2024 06:19:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
-   PD  [Multiple Regression] [Mini-Tutorial FMPS] [2010-11-22 11:26:18] [3cdf9c5e1f396891d2638627ccb7b98d]
-    D    [Multiple Regression] [Mini-Tutorial FMPS] [2010-11-22 22:19:35] [3cdf9c5e1f396891d2638627ccb7b98d]
-    D      [Multiple Regression] [Mini-Tutorial FMP...] [2010-11-22 23:58:11] [3cdf9c5e1f396891d2638627ccb7b98d]
-    D        [Multiple Regression] [] [2010-11-24 15:02:47] [afdb2fc47981b6a655b732edc8065db9]
- RMPD          [Univariate Explorative Data Analysis] [Univariate EDA (Pop)] [2010-12-17 16:23:24] [1251ac2db27b84d4a3ba43449388906b]
-                   [Univariate Explorative Data Analysis] [] [2010-12-24 15:16:17] [4f70e6cd0867f10d298e58e8e27859b5] [Current]
Feedback Forum

Post a new message
Dataseries X:
15
12
9
10
13
16
14
16
10
8
12
15
14
14
12
12
10
4
14
15
16
12
12
12
12
12
11
11
11
11
11
11
15
15
9
16
13
9
16
12
15
5
11
17
9
13
16
16
14
16
11
11
11
12
12
12
14
10
9
12
10
14
8
16
14
14
12
14
7
19
15
8
10
13
13
10
12
15
7
14
10
6
11
12
14
12
14
11
10
13
8
9
6
12
14
11
8
7
9
14
13
15
5
15
13
12
6
7
13
16
10
16
15
8
11
13
16
11
14
9
8
8
11
12
11
14
11
14
13
12
4
15
10
13
15
12
13
8
10
15
16
16
14
14
12
15
13
16
14
8
16
16
12
11
16
9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115093&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]4 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=115093&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115093&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations156
minimum4
Q110
median12
mean12.0448717948718
Q314
maximum19

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 156 \tabularnewline
minimum & 4 \tabularnewline
Q1 & 10 \tabularnewline
median & 12 \tabularnewline
mean & 12.0448717948718 \tabularnewline
Q3 & 14 \tabularnewline
maximum & 19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115093&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]156[/C][/ROW]
[ROW][C]minimum[/C][C]4[/C][/ROW]
[ROW][C]Q1[/C][C]10[/C][/ROW]
[ROW][C]median[/C][C]12[/C][/ROW]
[ROW][C]mean[/C][C]12.0448717948718[/C][/ROW]
[ROW][C]Q3[/C][C]14[/C][/ROW]
[ROW][C]maximum[/C][C]19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115093&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115093&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
# observations156
minimum4
Q110
median12
mean12.0448717948718
Q314
maximum19



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')