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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 computationSun, 25 Nov 2012 13:05:12 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/25/t13538667441j5k3b0f4vekktk.htm/, Retrieved Mon, 29 Apr 2024 00:38:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=192805, Retrieved Mon, 29 Apr 2024 00:38:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [Question 8] [2012-10-14 09:55:28] [3f1165f0052bdaf7d486f8ac60253253]
- RMPD    [Univariate Explorative Data Analysis] [Univariate EDA - MR] [2012-11-25 18:05:12] [64435dfec13c3cda39d1733fd4b6eb52] [Current]
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Dataseries X:
14915
11773
11608
11468
11511
11200
11164
10960
10667
11556
11372
12333
13102
11115
12572
11557
12059
11420
11185
11113
10706
11523
11391
12634
13469
11735
13281
11968
11623
11084
11509
11134
10438
11530
11491
13093
13106
11305
13113
12203
11309
11088
11234
11619
10942
11445
11291
13281
13726
11300
11983
11092
11093
10692
10786
11166
10553
11103
10969
12090
12544
12264
13783
11214
11453
10883
10381
10348
10024
10805
10796
11907
12261
11377
12689
11474
10992
10764
12164
10409
10398
10349
10865
11630
12221
10884
12019
11021
10799
10423
10484
10450
9906
11049
11281
12485
12849
11380
12079
11366
11328
10444
10854
10434
10137
10992
10906
12367
14371
11695
11546
10922
10670
10254
10573
10239
10253
11176
10719
11817
12487
11519
12025
10976
11276
10657
11141
10423
10640
11426
10948
12540
12200
10644
12044
11338
11292
10612
10995
10686
10635
11285
11475
12535




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192805&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192805&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192805&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 time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Descriptive Statistics
# observations144
minimum9906
Q110841.75
median11291.5
mean11442.4583333333
Q311922.25
maximum14915

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 144 \tabularnewline
minimum & 9906 \tabularnewline
Q1 & 10841.75 \tabularnewline
median & 11291.5 \tabularnewline
mean & 11442.4583333333 \tabularnewline
Q3 & 11922.25 \tabularnewline
maximum & 14915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192805&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]144[/C][/ROW]
[ROW][C]minimum[/C][C]9906[/C][/ROW]
[ROW][C]Q1[/C][C]10841.75[/C][/ROW]
[ROW][C]median[/C][C]11291.5[/C][/ROW]
[ROW][C]mean[/C][C]11442.4583333333[/C][/ROW]
[ROW][C]Q3[/C][C]11922.25[/C][/ROW]
[ROW][C]maximum[/C][C]14915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192805&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192805&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
# observations144
minimum9906
Q110841.75
median11291.5
mean11442.4583333333
Q311922.25
maximum14915



Parameters (Session):
par2 = yellow ; par3 = FALSE ; par4 = Unknown ;
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')