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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 computationSun, 09 Nov 2008 11:46:42 -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/09/t1226256430mjlkybw58zf5pg6.htm/, Retrieved Sun, 19 May 2024 12:04:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22815, Retrieved Sun, 19 May 2024 12:04:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Maximum-likelihood Fitting - Normal Distribution] [various eda topîc...] [2008-11-04 20:49:44] [077ffec662d24c06be4c491541a44245]
F    D    [Maximum-likelihood Fitting - Normal Distribution] [] [2008-11-09 18:46:42] [6d40a467de0f28bd2350f82ac9522c51] [Current]
Feedback Forum
2008-11-19 14:43:22 [2df1bcd103d52957f4a39bd4617794c8] [reply] 
Correcte hantering van de juiste methode.

Vervolgens trekt student conclusie dat er bij benadering een normaalverdeling aanwezig is. Dit is, naar mijn mening correct, daar de curve en het histogram ongeveer eenzelfde verloop kennen.

2008-11-22 13:46:30 [Jeroen Michel] [reply] 
De student geeft hier een correcte conclusie weer. Er is een 'bijna' normaalverdeling, daar het histogram vrijwel gelijk loopt met de Gauss-curve.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
299,63
305,945
382,252
348,846
335,367
373,617
312,612
312,232
337,161
331,476
350,103
345,127
297,256
295,979
361,007
321,803
354,937
349,432
290,979
349,576
327,625
349,377
336,777
339,134
323,321
318,86
373,583
333,03
408,556
414,646
291,514
348,857
349,368
375,765
364,136
349,53
348,167
332,856
360,551
346,969
392,815
372,02
371,027
342,672
367,343
390,786
343,785
362,6
349,468
340,624
369,536
407,782
392,239
404,824
373,669
344,902
396,7
398,911
366,009
392,484

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=22815&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=22815&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22815&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
mean352.1359166666673.94138973363257
standard deviation30.52987359854372.78698340795063

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 352.135916666667 & 3.94138973363257 \tabularnewline
standard deviation & 30.5298735985437 & 2.78698340795063 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22815&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]352.135916666667[/C][C]3.94138973363257[/C][/ROW]
[ROW][C]standard deviation[/C][C]30.5298735985437[/C][C]2.78698340795063[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22815&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22815&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
mean352.1359166666673.94138973363257
standard deviation30.52987359854372.78698340795063


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')