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Author

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R Software Module

rwasp_univariatedataseries.wasp

Title produced by software

Univariate Data Series

Date of computation

Mon, 01 Dec 2008 09:17:16 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/01/t1228148278km9346eowpaygtg.htm/, Retrieved Sun, 05 May 2024 10:34:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26965, Retrieved Sun, 05 May 2024 10:34:01 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

198

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F    D    [Univariate Data Series] [Q5] [2008-12-01 16:17:16] [7ed4ec9f8cdf7df79ef87b9dc09dff20] [Current]

Feedback Forum

2008-12-03 10:06:13 [Romina Machiels] [reply] 
Bij deze vraag werd er een berekening gemaakt, maar er werd geen uitleg gegeven. 
We zien duidelijk dat zowel het gemiddelde als de standaard fout jaar na jaar toenemen.  
Naarmate de populatie stijgt (dus het aantal mensen dat een vlucht kan betalen neemt toe), zijn er meer reizigers en is er dus een stijgende trend.  
De meerderheid van deze reizigers gaan echter allen op reis gedurende de vakantiemaanden. Hierdoor worden de maanden die al een hogere waarde vertoonden, nog extremer.  
We kunnen dus besluiten dat een toename van de populatie een toename van seizonaliteit veroorzaakt en dus ook een toename van de standaard fout. 
Om de spreiding te stabiliseren (en dus de standaard fout te stabiliseren) gebruiken we de Lambda.  
2008-12-08 18:14:01 [Jeroen Aerts] [reply] 
Je hebt een verkeerde bewerking uitgevoerd. je moet namelijk de standard deviation mean plot berekenen, hier vind je de link naar de goede berekening:  
 
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/07/t1228671979phjd77e2ulx1do1.htm, Retrieved Sun, 07 Dec 2008 17:46:25 +0000 
 
De regressie dient om de standaardfout van het gemiddelde te kunnen verklaren.een Lamda van -0.31 is goed om de spreiding optimaal te stabiliseren. 
 
Er is een significante helling. Er zullen dus 2 transformaties moeten gebeuren om de spreiding te stabiliseren.

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26965&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26965&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26965&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Univariate Dataseries
Name of dataseries	Airline
Source	Box-Jenkins
Description	Airline Passengers
Number of observations	144

\begin{tabular}{lllllllll}
\hline
Univariate Dataseries \tabularnewline
Name of dataseries & Airline \tabularnewline
Source & Box-Jenkins \tabularnewline
Description & Airline Passengers \tabularnewline
Number of observations & 144 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26965&T=1

[TABLE]
[ROW][C]Univariate Dataseries[/C][/ROW]
[ROW][C]Name of dataseries[/C][C]Airline[/C][/ROW]
[ROW][C]Source[/C][C]Box-Jenkins[/C][/ROW]
[ROW][C]Description[/C][C]Airline Passengers[/C][/ROW]
[ROW][C]Number of observations[/C][C]144[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26965&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26965&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Univariate Dataseries
Name of dataseries	Airline
Source	Box-Jenkins
Description	Airline Passengers
Number of observations	144

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Airline ; par2 = Box-Jenkins ; par3 = Airline Passengers ;

Parameters (R input):

par1 = Airline ; par2 = Box-Jenkins ; par3 = Airline Passengers ; 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):

bitmap(file='test1.png')
plot(x,col=2,type='b',main=main,xlab=xlab,ylab=ylab)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Univariate Dataseries',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Name of dataseries',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Source',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')

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Dataset

Tables (Output of Computation)

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Input Parameters & R Code