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Author's title

Author*Unverified author*
R Software Modulerwasp_rngnorm.wasp
Title produced by softwareRandom Number Generator - Normal Distribution
Date of computationThu, 08 Sep 2011 22:49:44 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Sep/08/t1315536630a5e9a3ke2mcbo5f.htm/, Retrieved Sat, 18 May 2024 03:20:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=124283, Retrieved Sat, 18 May 2024 03:20:03 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact264
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Random Number Generator - Normal Distribution] [] [2011-09-09 02:49:44] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124283&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124283&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124283&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'George Udny Yule' @ yule.wessa.net







ParameterValueStandard Deviation
# simulated values1000-
true mean174-
true standard deviation4.78-
mean174.0136746199930.148600821212325
standard deviation4.69917057202410.105076648369125

\begin{tabular}{lllllllll}
\hline
Parameter & Value & Standard Deviation \tabularnewline
# simulated values & 1000 & - \tabularnewline
true mean & 174 & - \tabularnewline
true standard deviation & 4.78 & - \tabularnewline
mean & 174.013674619993 & 0.148600821212325 \tabularnewline
standard deviation & 4.6991705720241 & 0.105076648369125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124283&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]# simulated values[/C][C]1000[/C][C]-[/C][/ROW]
[ROW][C]true mean[/C][C]174[/C][C]-[/C][/ROW]
[ROW][C]true standard deviation[/C][C]4.78[/C][C]-[/C][/ROW]
[ROW][C]mean[/C][C]174.013674619993[/C][C]0.148600821212325[/C][/ROW]
[ROW][C]standard deviation[/C][C]4.6991705720241[/C][C]0.105076648369125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124283&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124283&T=1

As an alternative you can also use a QR Code:  

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

ParameterValueStandard Deviation
# simulated values1000-
true mean174-
true standard deviation4.78-
mean174.0136746199930.148600821212325
standard deviation4.69917057202410.105076648369125



Parameters (Session):
par1 = 1000 ; par2 = 174 ; par3 = 4.78 ; par4 = 2 ; par5 = N ; par6 = 20 ;
Parameters (R input):
par1 = 1000 ; par2 = 174 ; par3 = 4.78 ; par4 = 2 ; par5 = N ; par6 = 20 ; par7 = ; par8 = ;
R code (references can be found in the software module):
library(MASS)
library(msm)
par1 <- as.numeric(par1)
if (par1 > 10000) par1=10000 #impose restriction on number of random values
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
if (par6 == '0') par6 = 'Sturges' else {
par6 <- as.numeric(par6)
if (par6 > 50) par6 = 50 #impose restriction on the number of bins
}
if (par7 == '') par7 <- -Inf else par7 <- as.numeric(par7)
if (par8 == '') par8 <- Inf else par8 <- as.numeric(par8)
x <- rtnorm(par1,par2,par3,par7,par8)
x <- as.ts(x) #otherwise the fitdistr function does not work properly
if ((par7 == -Inf) & (par8 == Inf)) (r <- fitdistr(x,'normal'))
bitmap(file='test1.png')
myhist<-hist(x,col=par4,breaks=par6,main=main,ylab=ylab,xlab=xlab,freq=F)
if ((par7 == -Inf) & (par8 == Inf)) {
curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T)
}
dev.off()
load(file='createtable')
if (par5 == 'Y')
{
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Index',1,TRUE)
a<-table.element(a,'Value',1,TRUE)
a<-table.row.end(a)
for (i in 1:par1)
{
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
if ((par7 == -Inf) & (par8 == Inf)) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# simulated values',header=TRUE)
a<-table.element(a,par1)
a<-table.element(a,'-')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'true mean',header=TRUE)
a<-table.element(a,par2)
a<-table.element(a,'-')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'true standard deviation',header=TRUE)
a<-table.element(a,par3)
a<-table.element(a,'-')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,r$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')
}