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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 computationMon, 27 Oct 2008 14:04:55 -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/2008/Oct/27/t1225137980n17d1r6stnprnwq.htm/, Retrieved Fri, 17 May 2024 03:06:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19548, Retrieved Fri, 17 May 2024 03:06:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Explorative Data Analysis] [Q7] [2008-10-25 11:35:27] [c5a66f1c8528a963efc2b82a8519f117]
F         [Univariate Explorative Data Analysis] [Q7] [2008-10-27 20:04:55] [5f3e73ccf1ddc75508eed47fa51813d3] [Current]
Feedback Forum
2008-11-02 11:38:41 [Ciska Tanghe] [reply
Q7 moet net zoals Q2 opgelost worden aan de hand van vier assumpties. Dit heeft de student niet gedaan.
2008-11-02 16:54:58 [Stijn Loomans] [reply
Hier had je je eigen getallen reeksen moet gaan toetsen via de 4 assumptions zoals als in q2. Je moet je getallen reeksen niet direct gaan aanpassen( als je goede uitleg hebt) Maar dit mag natuurlijk altijd

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Dataseries X:
1671
1385
1632
1313
1300
1431
1398
1198
1292
1434
1660
1837
1455
1315
1642
1069
1209
1586
1122
1063
1125
1414
1347
1403
1299
1547
1515
1247
1639
1296
1063
1282
1365
1268
1532
1455
1393
1515
1510
1225
1577
1417
1224
1693
1633
1639
1914
1586
1552
2081
1500
1437
1470
1849
1387
1592
1589
1798
1935
1887
2027
2080
1556
1682
1785
1869
1781
2082
2570
1862
1936
1504
1765
1607
1577
1493
1615
1700
1335
1523
1621
1539
1637
1523
1418
1819
1594
1359
1261
1722
1407
1380
1642
1681
1542
1704
1431




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=19548&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=19548&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19548&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
# observations97
minimum1063
Q11385
median1532
mean1544.75257731959
Q31671
maximum2570

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 97 \tabularnewline
minimum & 1063 \tabularnewline
Q1 & 1385 \tabularnewline
median & 1532 \tabularnewline
mean & 1544.75257731959 \tabularnewline
Q3 & 1671 \tabularnewline
maximum & 2570 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19548&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]97[/C][/ROW]
[ROW][C]minimum[/C][C]1063[/C][/ROW]
[ROW][C]Q1[/C][C]1385[/C][/ROW]
[ROW][C]median[/C][C]1532[/C][/ROW]
[ROW][C]mean[/C][C]1544.75257731959[/C][/ROW]
[ROW][C]Q3[/C][C]1671[/C][/ROW]
[ROW][C]maximum[/C][C]2570[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19548&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19548&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
# observations97
minimum1063
Q11385
median1532
mean1544.75257731959
Q31671
maximum2570



Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')