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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_fitdistrnorm.wasp

Title produced by software

Maximum-likelihood Fitting - Normal Distribution

Date of computation

Sun, 09 Nov 2008 05:58:19 -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/Nov/09/t12262355606zzczl0os72j5cl.htm/, Retrieved Sun, 19 May 2024 08:46:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22737, Retrieved Sun, 19 May 2024 08:46:05 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

204

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

F     [Partial Correlation] [Partial correlation] [2008-11-08 12:17:14] [82d201ca7b4e7cd2c6f885d29b5b6937]
F RM D  [Box-Cox Linearity Plot] [Box Cox Linearity...] [2008-11-09 12:31:54] [82d201ca7b4e7cd2c6f885d29b5b6937]
- RMPD    [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-11-09 12:55:12] [82d201ca7b4e7cd2c6f885d29b5b6937]
F    D        [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-11-09 12:58:19] [00a0a665d7a07edd2e460056b0c0c354] [Current]
F               [Maximum-likelihood Fitting - Normal Distribution] [maximum likelihoo...] [2008-11-10 22:36:30] [8d78428855b119373cac369316c08983] 
- RMPD          [Testing Mean with known Variance - Critical Value] [critical value] [2008-11-11 00:28:19] [8d78428855b119373cac369316c08983] 
F RMPD          [Testing Mean with known Variance - p-value] [p-value] [2008-11-11 00:48:00] [8d78428855b119373cac369316c08983] 
- RMPD          [Testing Mean with known Variance - Type II Error] [type 2 error] [2008-11-11 01:19:31] [8d78428855b119373cac369316c08983] 
- RMPD          [Testing Mean with known Variance - Sample Size] [sample size] [2008-11-11 01:44:50] [8d78428855b119373cac369316c08983] 
F RMPD          [Testing Population Mean with known Variance - Confidence Interval] [confidence interval] [2008-11-11 01:58:15] [8d78428855b119373cac369316c08983] 
F RMPD          [Testing Sample Mean with known Variance - Confidence Interval] [confidence interval] [2008-11-11 02:12:01] [8d78428855b119373cac369316c08983] 
-    D          [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-12-10 19:20:50] [82d201ca7b4e7cd2c6f885d29b5b6937] 

Feedback Forum

2008-11-21 21:56:53 [Kim Wester] [reply] 
Er kan worden gezegd dat op de grafiek de echte waarden worden weergegeven door het histogram en de geschatte waarden door de curve. Deze lopen gelijk op. Je kan dus concluderen dat de normaalverdeling een goede benadering is voor Yt.
2008-11-23 11:04:16 [Inge Meelberghs] [reply] 
Aan de hand van de histogram en het verloop van de curve kunnen we stellen dat er sprake is van een normaal verdeling. Dit mogen we zeggen omdat de histogram hetzelfde verloop aanneemt als de Gauss-curve. 
2008-11-23 17:09:08 [Michaël De Kuyer] [reply] 
Inderdaad, de tijdreeks benadert de normaalverdeling. De Gausscurve en het histogram komen sterk overeen.
2008-11-24 12:20:17 [Bonifer Spillemaeckers] [reply] 
Het histogram en de Gauss-curve vertonen hier inderdaad een gelijkaardig verloop. We kunnen hier stellen dat we te maken hebben met een normaalverdeling. 

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Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22737&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22737&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22737&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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Parameter	Estimated Value	Standard Deviation
mean	112.559016393443	1.48672596079449
standard deviation	11.6117009534572	1.05127400864387

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 112.559016393443 & 1.48672596079449 \tabularnewline
standard deviation & 11.6117009534572 & 1.05127400864387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22737&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]112.559016393443[/C][C]1.48672596079449[/C][/ROW]
[ROW][C]standard deviation[/C][C]11.6117009534572[/C][C]1.05127400864387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22737&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22737&T=1

As an alternative you can also use a QR Code:

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

Parameter	Estimated Value	Standard Deviation
mean	112.559016393443	1.48672596079449
standard deviation	11.6117009534572	1.05127400864387

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 8 ; par2 = 0 ;

Parameters (R input):

par1 = 8 ; par2 = 0 ;

R code (references can be found in the software module):

library(MASS)
par1 <- as.numeric(par1)
if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2)
x <- as.ts(x) #otherwise the fitdistr function does not work properly
r <- fitdistr(x,'normal')
r
bitmap(file='test1.png')
myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F)
curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,r$estimate[1])
a<-table.element(a,r$sd[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'standard deviation',header=TRUE)
a<-table.element(a,r$estimate[2])
a<-table.element(a,r$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code