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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 computationMon, 15 Dec 2014 17:47:00 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418665632v7c4tm26o7ktxge.htm/, Retrieved Thu, 16 May 2024 08:11:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268808, Retrieved Thu, 16 May 2024 08:11:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cronbach Alpha] [] [2014-12-14 22:25:21] [2b9d0c54c8c845c625e475ed5f1f3af1]
-    D  [Cronbach Alpha] [] [2014-12-14 23:28:38] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMPD    [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 13:26:13] [2b9d0c54c8c845c625e475ed5f1f3af1]
-    D      [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 14:08:02] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM          [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 14:08:41] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D          [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 16:14:57] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP             [Percentiles] [] [2014-12-15 16:22:39] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                [Tukey lambda PPCC Plot] [] [2014-12-15 16:26:30] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP                 [Kernel Density Estimation] [] [2014-12-15 16:30:20] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP                   [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 16:35:22] [2b9d0c54c8c845c625e475ed5f1f3af1]
- R  D                    [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 17:24:27] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP                       [Percentiles] [] [2014-12-15 17:27:50] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                          [Percentiles] [] [2014-12-15 17:28:11] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                            [Tukey lambda PPCC Plot] [] [2014-12-15 17:35:55] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                              [Kernel Density Estimation] [] [2014-12-15 17:40:21] [2b9d0c54c8c845c625e475ed5f1f3af1]
-                                   [Kernel Density Estimation] [] [2014-12-15 17:42:13] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                  [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 17:47:00] [b22ed12f8980e34362f6926e9ebd1315] [Current]
- RM                                      [Percentiles] [] [2014-12-15 17:50:51] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                                        [Tukey lambda PPCC Plot] [] [2014-12-15 17:56:56] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                                        [Kernel Density Estimation] [] [2014-12-15 18:08:51] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                        [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 18:36:43] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                        [Percentiles] [] [2014-12-15 18:50:26] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                        [Tukey lambda PPCC Plot] [] [2014-12-15 18:51:10] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                          [Notched Boxplots] [] [2014-12-15 19:44:02] [2b9d0c54c8c845c625e475ed5f1f3af1]
-    D                                        [Kernel Density Estimation] [] [2014-12-15 18:53:06] [2b9d0c54c8c845c625e475ed5f1f3af1]
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Dataseries X:
20
19
18
24
20
20
24
21
28
10
22
19
27
23
24
24
25
24
21
28
28
22
26
26
21
26
23
20
24
25
24
20
24
25
23
21
23
21
18
24
18
21
23
25
22
22
23
24
25
22
24
21
24
25
23
27
27
23
18
20
23
24
26
20
23
22
23
17
20
22
18
19
19
16
26
25
23
18
22
26
25
26
26
24
22
21
22
28
22
26
20
24
21
23
23
23
22
23
21
27
23
26
27
27
23
23
23
28
24
20
23
22
15
27
23
23
20
18
22
20
21
25
19
25
24
22
28
22
21
23
19
21
25
23
28
14
23
24
25
15
23
26
21
26
23
15
16
20
20
21
28
19
21
22
27
20
17
26
21
24
21
25
22
17
14
23
28
24
22
24
25
21
22
16
18
27
17
25
24
21
21
19
27
28
19
23
25
26
25
25
24
24
24
22
21
17
23
17
25
19
8
14
22
25
28
25
24
15
24
28
24
25
23
26
26
22
25
22
26
20
26
26
21
21
24
21
18
23
26
23
25
20
25
26
19
21
23
24
6
22
21
28
24
14
20
28
19
24
21
21
26
24
26
25
23
24
24
26
23
20
16
24
20
23
23
18
21
25
23
26
26
24
23
21
23
20
23
24




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268808&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268808&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268808&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







ParameterEstimated ValueStandard Deviation
mean22.47841726618710.205677731720201
standard deviation3.429333106087480.145436118838422

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 22.4784172661871 & 0.205677731720201 \tabularnewline
standard deviation & 3.42933310608748 & 0.145436118838422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268808&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]22.4784172661871[/C][C]0.205677731720201[/C][/ROW]
[ROW][C]standard deviation[/C][C]3.42933310608748[/C][C]0.145436118838422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268808&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268808&T=1

As an alternative you can also use a QR Code:  

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

ParameterEstimated ValueStandard Deviation
mean22.47841726618710.205677731720201
standard deviation3.429333106087480.145436118838422



Parameters (Session):
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')