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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_rngnorm.wasp

Title produced by software

Random Number Generator - Normal Distribution

Date of computation

Wed, 05 Oct 2016 14:34:43 +0200

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Oct/05/t14756708901zc7a6s0s09h7h7.htm/, Retrieved Sun, 05 May 2024 12:42:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296556, Retrieved Sun, 05 May 2024 12:42:27 +0000

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Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Random Number Generator - Normal Distribution] [] [2016-10-05 12:34:43] [86c9a777e8dbb7ef3face68c75fc8376] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	Big 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296556&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]

2 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=296556&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296556&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 Output	view raw output of R engine
Computing time	2 seconds
R Server	Big Analytics Cloud Computing Center

Parameter	Value	Standard Deviation
# simulated values	100	-
true mean	0	-
true standard deviation	1	-
mean	0.134387160682372	0.102912916777244
standard deviation	1.02912916777244	0.0727704213248761

\begin{tabular}{lllllllll}
\hline
Parameter & Value & Standard Deviation \tabularnewline
# simulated values & 100 & - \tabularnewline
true mean & 0 & - \tabularnewline
true standard deviation & 1 & - \tabularnewline
mean & 0.134387160682372 & 0.102912916777244 \tabularnewline
standard deviation & 1.02912916777244 & 0.0727704213248761 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296556&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]# simulated values[/C][C]100[/C][C]-[/C][/ROW]
[ROW][C]true mean[/C][C]0[/C][C]-[/C][/ROW]
[ROW][C]true standard deviation[/C][C]1[/C][C]-[/C][/ROW]
[ROW][C]mean[/C][C]0.134387160682372[/C][C]0.102912916777244[/C][/ROW]
[ROW][C]standard deviation[/C][C]1.02912916777244[/C][C]0.0727704213248761[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296556&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296556&T=1

As an alternative you can also use a QR Code:

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

Parameter	Value	Standard Deviation
# simulated values	100	-
true mean	0	-
true standard deviation	1	-
mean	0.134387160682372	0.102912916777244
standard deviation	1.02912916777244	0.0727704213248761

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[-2.5,-2[	-2.25	1	0.01	0.01	0.02
[-2,-1.5[	-1.75	6	0.06	0.07	0.12
[-1.5,-1[	-1.25	8	0.08	0.15	0.16
[-1,-0.5[	-0.75	12	0.12	0.27	0.24
[-0.5,0[	-0.25	17	0.17	0.44	0.34
[0,0.5[	0.25	18	0.18	0.62	0.36
[0.5,1[	0.75	19	0.19	0.81	0.38
[1,1.5[	1.25	11	0.11	0.92	0.22
[1.5,2[	1.75	4	0.04	0.96	0.08
[2,2.5[	2.25	2	0.02	0.98	0.04
[2.5,3[	2.75	1	0.01	0.99	0.02
[3,3.5]	3.25	1	0.01	1	0.02

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[-2.5,-2[ & -2.25 & 1 & 0.01 & 0.01 & 0.02 \tabularnewline
[-2,-1.5[ & -1.75 & 6 & 0.06 & 0.07 & 0.12 \tabularnewline
[-1.5,-1[ & -1.25 & 8 & 0.08 & 0.15 & 0.16 \tabularnewline
[-1,-0.5[ & -0.75 & 12 & 0.12 & 0.27 & 0.24 \tabularnewline
[-0.5,0[ & -0.25 & 17 & 0.17 & 0.44 & 0.34 \tabularnewline
[0,0.5[ & 0.25 & 18 & 0.18 & 0.62 & 0.36 \tabularnewline
[0.5,1[ & 0.75 & 19 & 0.19 & 0.81 & 0.38 \tabularnewline
[1,1.5[ & 1.25 & 11 & 0.11 & 0.92 & 0.22 \tabularnewline
[1.5,2[ & 1.75 & 4 & 0.04 & 0.96 & 0.08 \tabularnewline
[2,2.5[ & 2.25 & 2 & 0.02 & 0.98 & 0.04 \tabularnewline
[2.5,3[ & 2.75 & 1 & 0.01 & 0.99 & 0.02 \tabularnewline
[3,3.5] & 3.25 & 1 & 0.01 & 1 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296556&T=2

[TABLE]
[ROW][C]Frequency Table (Histogram)[/C][/ROW]
[ROW][C]Bins[/C][C]Midpoint[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][C]Cumul. Rel. Freq.[/C][C]Density[/C][/ROW]
[ROW][C][-2.5,-2[[/C][C]-2.25[/C][C]1[/C][C]0.01[/C][C]0.01[/C][C]0.02[/C][/ROW]
[ROW][C][-2,-1.5[[/C][C]-1.75[/C][C]6[/C][C]0.06[/C][C]0.07[/C][C]0.12[/C][/ROW]
[ROW][C][-1.5,-1[[/C][C]-1.25[/C][C]8[/C][C]0.08[/C][C]0.15[/C][C]0.16[/C][/ROW]
[ROW][C][-1,-0.5[[/C][C]-0.75[/C][C]12[/C][C]0.12[/C][C]0.27[/C][C]0.24[/C][/ROW]
[ROW][C][-0.5,0[[/C][C]-0.25[/C][C]17[/C][C]0.17[/C][C]0.44[/C][C]0.34[/C][/ROW]
[ROW][C][0,0.5[[/C][C]0.25[/C][C]18[/C][C]0.18[/C][C]0.62[/C][C]0.36[/C][/ROW]
[ROW][C][0.5,1[[/C][C]0.75[/C][C]19[/C][C]0.19[/C][C]0.81[/C][C]0.38[/C][/ROW]
[ROW][C][1,1.5[[/C][C]1.25[/C][C]11[/C][C]0.11[/C][C]0.92[/C][C]0.22[/C][/ROW]
[ROW][C][1.5,2[[/C][C]1.75[/C][C]4[/C][C]0.04[/C][C]0.96[/C][C]0.08[/C][/ROW]
[ROW][C][2,2.5[[/C][C]2.25[/C][C]2[/C][C]0.02[/C][C]0.98[/C][C]0.04[/C][/ROW]
[ROW][C][2.5,3[[/C][C]2.75[/C][C]1[/C][C]0.01[/C][C]0.99[/C][C]0.02[/C][/ROW]
[ROW][C][3,3.5][/C][C]3.25[/C][C]1[/C][C]0.01[/C][C]1[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296556&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296556&T=2

As an alternative you can also use a QR Code:

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

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[-2.5,-2[	-2.25	1	0.01	0.01	0.02
[-2,-1.5[	-1.75	6	0.06	0.07	0.12
[-1.5,-1[	-1.25	8	0.08	0.15	0.16
[-1,-0.5[	-0.75	12	0.12	0.27	0.24
[-0.5,0[	-0.25	17	0.17	0.44	0.34
[0,0.5[	0.25	18	0.18	0.62	0.36
[0.5,1[	0.75	19	0.19	0.81	0.38
[1,1.5[	1.25	11	0.11	0.92	0.22
[1.5,2[	1.75	4	0.04	0.96	0.08
[2,2.5[	2.25	2	0.02	0.98	0.04
[2.5,3[	2.75	1	0.01	0.99	0.02
[3,3.5]	3.25	1	0.01	1	0.02

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 100 ; par2 = 0 ; par3 = 1 ; par4 = 2 ; par5 = N ; par6 = 0 ;

Parameters (R input):

par1 = 100 ; par2 = 0 ; par3 = 1 ; par4 = 2 ; par5 = N ; par6 = 0 ; 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$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Frequency Table (Histogram)',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bins',header=TRUE)
a<-table.element(a,'Midpoint',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)
a<-table.element(a,'Density',header=TRUE)
a<-table.row.end(a)
crf <- 0
mynumrows <- (length(myhist$breaks)-1)
for (i in 1:mynumrows) {
a<-table.row.start(a)
dum <- paste('[',myhist$breaks[i],sep='')
dum <- paste(dum,myhist$breaks[i+1],sep=',')
if (i==mynumrows)
dum <- paste(dum,']',sep='')
else
dum <- paste(dum,'[',sep='')
a<-table.element(a,dum,header=TRUE)
a<-table.element(a,myhist$mids[i])
a<-table.element(a,myhist$counts[i])
rf <- myhist$counts[i]/par1
crf <- crf + rf
a<-table.element(a,round(rf,6))
a<-table.element(a,round(crf,6))
a<-table.element(a,round(myhist$density[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable3.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code