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Description of Statistical Computation

Author's title

Maximum-likelihood Normal Distribution Fitting - Aantal inschrjvingen tweed...

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 08:33:55 -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/t1226417752u05tjdnfwgnim2z.htm/, Retrieved Tue, 28 May 2024 07:01:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23604, Retrieved Tue, 28 May 2024 07:01:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2008-11-10 16:53:50] [819b576fab25b35cfda70f80599828ec]
F    D  [Bivariate Kernel Density Estimation] [Bivaritae Kernel ...] [2008-11-10 16:58:43] [819b576fab25b35cfda70f80599828ec]
F RMPD    [Partial Correlation] [Partial Correlati...] [2008-11-10 17:08:28] [819b576fab25b35cfda70f80599828ec]
- RMPD      [Trivariate Scatterplots] [Trivariate Scatte...] [2008-11-10 17:21:24] [819b576fab25b35cfda70f80599828ec]
- RMPD        [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-11-10 17:50:35] [819b576fab25b35cfda70f80599828ec]
F   PD            [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-11-11 15:33:55] [e08fee3874f3333d6b7a377a061b860d] [Current]
Feedback Forum
2008-11-14 18:31:07 [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 van de gegevens.
2008-11-21 17:27:59 [Michael Van Spaandonck] [reply] 
Ik moet me volledig aansluiten bij wat Kevin hierboven zegt.
Ik heb hier verder niets aan toe te voegen.
2008-11-22 15:35:21 [Jeroen Michel] [reply] 
Ook hier valt weinig op aan te merken. Er is een correcte uitvoering gebeurd en de student Kevin Neelen bevestigd ook nogmaals de gebruikswijze van deze techniek.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
54.281
63.654
68.918
58.686
67.074
60.183
54.326
54.085
53.564
60.873
53.398
45.164
59.672
56.298
62.361
56.930
62.954
62.431
52.528
54.060
53.093
52.695
52.333
41.747
58.576
57.851
63.721
63.384
61.141
59.231
63.472
49.214
55.816
61.713
48.664
45.351
57.888
54.091
59.098
58.962
55.433
60.403
60.721
48.440
57.981
60.258
47.312
46.980
54.846
56.824
67.744
62.849
54.691
65.461
53.724
54.560
57.722
55.458
48.490
46.362

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=23604&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=23604&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23604&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
mean56.59566666666670.766584343647798
standard deviation5.937936792822530.542056987744797

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 56.5956666666667 & 0.766584343647798 \tabularnewline
standard deviation & 5.93793679282253 & 0.542056987744797 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23604&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]56.5956666666667[/C][C]0.766584343647798[/C][/ROW]
[ROW][C]standard deviation[/C][C]5.93793679282253[/C][C]0.542056987744797[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23604&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23604&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
mean56.59566666666670.766584343647798
standard deviation5.937936792822530.542056987744797


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')