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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 computationFri, 23 Oct 2009 08:04:14 -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/23/t1256306782i7mxnst664qn21j.htm/, Retrieved Thu, 02 May 2024 00:28:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49984, Retrieved Thu, 02 May 2024 00:28:01 +0000
QR Codes:

Original text written by user:workshop 3 part 2 assumpties 4plot geboortecijfer
IsPrivate?No (this computation is public)
User-defined keywordsworkshop 3 part 2 assumpties 4plot geboortecijfer
Estimated Impact125

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]
- RMPD        [Univariate Explorative Data Analysis] [workshop 3 part 2...] [2009-10-23 14:04:14] [85defb7a20869746625978e6577e6e44] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
45319
46603
47943
45773
53225
57281
62241
61814
70727
67625
65618
63052
62410
60571
62543
62985
62739
63552
64171
63063
62985
63005
61880
62555
62254
63290
65570
66277
67061
66779
67350
67746
64551
65550
64260
61208
59603
56345
53474
50877
51749
51580
51039
50708
51245
49937
50274
51134
52514
54027
57526
59303
60939
60808
60109
59678
60092
60292
60927
59801
58352
59298
59234
56696
55434
56458
56951
56756
58545
58459

Tables (Output of Computation)





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=49984&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=49984&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49984&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Descriptive Statistics
# observations70
minimum45319
Q155661.75
median60100.5
mean59024.8571428571
Q363000
maximum70727

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 70 \tabularnewline
minimum & 45319 \tabularnewline
Q1 & 55661.75 \tabularnewline
median & 60100.5 \tabularnewline
mean & 59024.8571428571 \tabularnewline
Q3 & 63000 \tabularnewline
maximum & 70727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49984&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]70[/C][/ROW]
[ROW][C]minimum[/C][C]45319[/C][/ROW]
[ROW][C]Q1[/C][C]55661.75[/C][/ROW]
[ROW][C]median[/C][C]60100.5[/C][/ROW]
[ROW][C]mean[/C][C]59024.8571428571[/C][/ROW]
[ROW][C]Q3[/C][C]63000[/C][/ROW]
[ROW][C]maximum[/C][C]70727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49984&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49984&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
# observations70
minimum45319
Q155661.75
median60100.5
mean59024.8571428571
Q363000
maximum70727


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')