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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_fitdistrnorm.wasp
Title produced by softwareMaximum-likelihood Fitting - Normal Distribution
Date of computationThu, 13 Nov 2008 04:40:34 -0700
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/Nov/13/t1226576504kjxgqz631wmhx0i.htm/, Retrieved Sun, 19 May 2024 11:10:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24580, Retrieved Sun, 19 May 2024 11:10:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Box-Cox Linearity Plot] [Q3 Box-Cox linear...] [2008-11-08 12:51:34] [2d4aec5ed1856c4828162be37be304d9]
F RMPD  [Maximum-likelihood Fitting - Normal Distribution] [Q5 Maximum-likeli...] [2008-11-08 13:00:54] [2d4aec5ed1856c4828162be37be304d9]
F    D      [Maximum-likelihood Fitting - Normal Distribution] [tijdreeksQ5] [2008-11-13 11:40:34] [89a49ebb3ece8e9a225c7f9f53a14c57] [Current]
Feedback Forum
2008-11-20 10:35:08 [7bf28d4d60530086dbc44ae6b648927e] [reply] 
In orde.
2008-11-20 13:28:27 [6066575aa30c0611e452e930b1dff53d] [reply] 
Dit is een volledig antwoord. Het is inderdaad zo dat de waarde van de data series zich op de x-as bevindt en dat de dichtheid zich op de y-as bevindt. Verder had men ook eventueel nog kunnen vermelden dat er ook zeer weinig waarden kleiner zijn dan 100.
2008-11-20 13:50:12 [Alexander Hendrickx] [reply] 
De vraag werd goed beantwoord en ik heb hier niets aan toe te voegen
2008-11-20 13:51:00 [Alexander Hendrickx] [reply] 
de vraag werd zeer goed beantwoord. Ik heb hier niets aan toe te voegen.
2008-11-21 11:41:00 [Natalie De Wilde] [reply] 
Goed beantwoordt. Je had nog kunnen zeggen dat het histogram niet helemaal overeenkomt met de normal density. Er zijn nog wel redelijk veel waarden die kleiner zijn dan 100.
2008-11-21 14:07:29 [Thomas Plasschaert] [reply] 
ik zou hier niet meteen van een goede conclusie uitgaan, rechts kunnen we inderdaad zien dat de density daalt, maar links is hier geen sprake van, alsook in het midden van de grafiek is de dichtheid nogal klein tegenover de curve.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7
117,5
120,6
127,5
112,3
124,5
115,2
105,4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24580&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24580&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24580&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






ParameterEstimated ValueStandard Deviation
mean113.2847058823531.05212456783820
standard deviation9.700109227794390.74396441657136

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 113.284705882353 & 1.05212456783820 \tabularnewline
standard deviation & 9.70010922779439 & 0.74396441657136 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24580&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]113.284705882353[/C][C]1.05212456783820[/C][/ROW]
[ROW][C]standard deviation[/C][C]9.70010922779439[/C][C]0.74396441657136[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24580&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24580&T=1

As an alternative you can also use a QR Code:  
QR Code


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

ParameterEstimated ValueStandard Deviation
mean113.2847058823531.05212456783820
standard deviation9.700109227794390.74396441657136


Figures (Output of Computation)

Input Parameters & R Code

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')