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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 computationTue, 11 Nov 2008 02:14:40 -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/11/t1226394943yxvb2k4pwrg6ocv.htm/, Retrieved Sun, 19 May 2024 19:48:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23237, Retrieved Sun, 19 May 2024 19:48:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact217

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Maximum-likelihood Fitting - Normal Distribution] [] [2007-11-01 21:31:44] [74be16979710d4c4e7c6647856088456]
F R PD    [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-11-11 09:14:40] [8a2d94dac8ebd598299eaec920908ca6] [Current]
-    D      [Maximum-likelihood Fitting - Normal Distribution] [Q5] [2008-11-12 13:54:53] [74be16979710d4c4e7c6647856088456]
F             [Maximum-likelihood Fitting - Normal Distribution] [q5] [2008-11-12 13:55:57] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-11-14 17:55:55 [Kevin Neelen] [reply] 
Door gebruikt te maken van het Maximum-likelihood Fitting - Normal Distribution Plot, kunnen we nagaan of het histogram gelijk loopt met de vloeiende lijn van de normaalverdeling.

Hier kunnen we zien dat het histogram grotendeels gelijk loopt met de grafiekcurve. We kunnen concluderen dat we hier te maken hebben met een normaalverdeling. De conclusie van de student klopt.
2008-11-17 20:59:49 [Kevin Engels] [reply] 
De grafiek van de normaalverdeling loopt gelijk met het histogram. Het antwoord van de student is dus correct.
2008-11-20 14:58:57 [Julie Leurentop] [reply] 
We kunnen hier inderdaad besluiten dat de grafiek een normale verdeling volgt.
2008-11-21 10:07:22 [90714a39acc78a7b2ecd294ecc6b2864] [reply] 
De overeenstemming tussen het histogram en de lijn van de normaalverdeling is goed genoeg om te spreken van een normaalverdeling.
2008-11-21 11:31:58 [Stijn Van de Velde] [reply] 
Aan het antwoord van de student heb ik niets toe te voegen.
2008-11-23 16:23:40 [Karen Van den Broeck] [reply] 
De student heeft gelijk wanneer hij zegt dat we hier kunnen spreken van een normaalverdeling. Zijn antwoord is volledig en helemaal correct.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2,1
2,2
2,2
2,7
3,1
3,2
3,1
3,1
2,8
3
2,8
2,7
3,2
3,1
3
2
1,7
1,2
1,4
1,3
1,3
1,1
0,9
1,2
0,9
1,3
1,4
1,5
1,1
1,6
1,5
1,6
1,7
1,6
1,7
1,6
1,6
1,3
1,1
1,6
1,9
1,6
1,7
1,6
1,4
2,1
1,9
1,7
1,8
2
2,5
2,1
2,1
2,3
2,4
2,4
2,3
1,7
2
2,3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23237&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23237&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23237&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






ParameterEstimated ValueStandard Deviation
mean1.9550.0822741015008841
standard deviation0.6372924498742050.0581765750873054

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 1.955 & 0.0822741015008841 \tabularnewline
standard deviation & 0.637292449874205 & 0.0581765750873054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23237&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]1.955[/C][C]0.0822741015008841[/C][/ROW]
[ROW][C]standard deviation[/C][C]0.637292449874205[/C][C]0.0581765750873054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23237&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23237&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
mean1.9550.0822741015008841
standard deviation0.6372924498742050.0581765750873054


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')