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Author's title

Author*Unverified author*
R Software Modulerwasp_fitdistrnorm.wasp
Title produced by softwareML Fitting and QQ Plot- Normal Distribution
Date of computationTue, 15 Jun 2021 07:12:30 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2021/Jun/15/t1623734133ckkjt85esy83u0t.htm/, Retrieved Sat, 27 Apr 2024 02:13:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319454, Retrieved Sat, 27 Apr 2024 02:13:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [ML Fitting and QQ Plot- Normal Distribution] [] [2021-06-15 05:12:30] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319454&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319454&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319454&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







ParameterEstimated ValueStandard Deviation
mean79.20919540229880.171136467221197
standard deviation3.569334017661280.121011756480418

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 79.2091954022988 & 0.171136467221197 \tabularnewline
standard deviation & 3.56933401766128 & 0.121011756480418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319454&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]79.2091954022988[/C][C]0.171136467221197[/C][/ROW]
[ROW][C]standard deviation[/C][C]3.56933401766128[/C][C]0.121011756480418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319454&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319454&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
mean79.20919540229880.171136467221197
standard deviation3.569334017661280.121011756480418



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)
library(car)
par1 <- as.numeric(par1)
if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2)
x <- na.omit(x)
x <- as.ts(x) #otherwise the fitdistr function does not work properly
r <- fitdistr(x,'normal')
print(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$estimate[2])^2),min(x),max(x),add=T)
dev.off()
bitmap(file='test3.png')
qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,r$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')