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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 computationSat, 25 Oct 2008 10:13:58 -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/25/t12249513374swbip7w3ys8xnl.htm/, Retrieved Wed, 22 May 2024 15:36:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18776, Retrieved Wed, 22 May 2024 15:36:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Univariate Explorative Data Analysis] [Lag plot: task 2] [2008-10-25 16:13:58] [0831954c833179c36e9320daee0825b5] [Current]
-         [Univariate Explorative Data Analysis] [Taskt 2] [2008-10-26 18:36:48] [6816386b1f3c2f6c0c9f2aa1e5bc9362]
-           [Univariate Explorative Data Analysis] [Task 2 ] [2008-10-27 20:39:39] [a7a7b7de998247cdf0f65ef79d563d66]
-   P       [Univariate Explorative Data Analysis] [Task 2 ] [2008-10-27 20:53:48] [a7a7b7de998247cdf0f65ef79d563d66]
-         [Univariate Explorative Data Analysis] [task 2] [2008-10-26 18:44:20] [73d6180dc45497329efd1b6934a84aba]
-   P     [Univariate Explorative Data Analysis] [Bob reproduce] [2008-10-29 19:33:03] [ed2ba3b6182103c15c0ab511ae4e6284]
Feedback Forum
2008-10-29 17:30:07 [Niels Stas] [reply
De punten liggen inderdaad ver uit elkaar, wat een zeer lage correlatie aangeeft en er dus op wijst dat een duidelijke voorspelling moeilijk tot zelfs onbestaand is.
2008-10-29 19:36:06 [Tom Ardies] [reply
Je had de lags op meer dan 1 moeten zetten, 12 of meer had beter geweest. Deze grafieken had je beter gebruikt voor Q2 van taak 1. De dataset is niet gewijzigd. Dit moest gebeuren om taak 2 tot een goed eind te brengen. Met een nieuwe dataset had je de assumptie kunnen toetsen en model beoordelen.

lags 12: http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/29/t1225308814hucauga07d2yxmu.htm
2008-10-30 13:56:57 [Bob Leysen] [reply
Ik heb de lags op 36 gezet, dus had ik dus ook moeten doen voor Q2. De grafische punten liggen zer ver uit elkaar. We kunnen vaststellen dat er geen afhankelijkheid is tussen beide datasetten. De horizontaal waar te nemen lijn geeft de spreiding weer. Er is dus ook geen correlatie.
2008-11-03 16:44:24 [Jeroen Michel] [reply
Je hebt inderdaad gebruikt van lag 1 en 36. Voor een concretere berekening had je beter ook gebruik gemaakt van lag 1.

Onderstaande links geeft een juiste oplossing weer. OPMERKING! In de opgave was duidelijk omschreven om 2x een nieuw model uit te voeren (2x nieuwe software).

http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/27/t1225089268qwpw3kd7cfi59hf.htm/

http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/28/t1225153537glhgvpad46hdvbo.htm/

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Dataseries X:
109.20
88.60
94.30
98.30
86.40
80.60
104.10
108.20
93.40
71.90
94.10
94.90
96.40
91.10
84.40
86.40
88.00
75.10
109.70
103.00
82.10
68.00
96.40
94.30
90.00
88.00
76.10
82.50
81.40
66.50
97.20
94.10
80.70
70.50
87.80
89.50
99.60
84.20
75.10
92.00
80.80
73.10
99.80
90.00
83.10
72.40
78.80
87.30
91.00
80.10
73.60
86.40
74.50
71.20
92.40
81.50
85.30
69.90
84.20
90.70
100.30




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=18776&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=18776&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18776&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
# observations61
minimum66.5
Q180.6
median87.3
mean86.8934426229508
Q394.1
maximum109.7

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 66.5 \tabularnewline
Q1 & 80.6 \tabularnewline
median & 87.3 \tabularnewline
mean & 86.8934426229508 \tabularnewline
Q3 & 94.1 \tabularnewline
maximum & 109.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18776&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]66.5[/C][/ROW]
[ROW][C]Q1[/C][C]80.6[/C][/ROW]
[ROW][C]median[/C][C]87.3[/C][/ROW]
[ROW][C]mean[/C][C]86.8934426229508[/C][/ROW]
[ROW][C]Q3[/C][C]94.1[/C][/ROW]
[ROW][C]maximum[/C][C]109.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18776&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18776&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
# observations61
minimum66.5
Q180.6
median87.3
mean86.8934426229508
Q394.1
maximum109.7



Parameters (Session):
par1 = 0 ; par2 = 1 ;
Parameters (R input):
par1 = 0 ; par2 = 1 ;
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')