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Author's title

Random generator met meer getallen -> Duidelijk goede fit -> normaalverdeli...

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 14:37:39 +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/t1475671092n6jhsbn0bdvz3ey.htm/, Retrieved Sun, 05 May 2024 11:34:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296559, Retrieved Sun, 05 May 2024 11:34:01 +0000

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User-defined keywords

Estimated Impact

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

-       [Random Number Generator - Normal Distribution] [Random generator ...] [2016-10-05 12:37:39] [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	4 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 time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296559&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]

4 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=296559&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296559&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	4 seconds
R Server	Big Analytics Cloud Computing Center

Parameter	Value	Standard Deviation
# simulated values	10000	-
true mean	0	-
true standard deviation	1	-
mean	-0.010329390097002	0.0100389381427104
standard deviation	1.00389381427104	0.00709860123662279

\begin{tabular}{lllllllll}
\hline
Parameter & Value & Standard Deviation \tabularnewline
# simulated values & 10000 & - \tabularnewline
true mean & 0 & - \tabularnewline
true standard deviation & 1 & - \tabularnewline
mean & -0.010329390097002 & 0.0100389381427104 \tabularnewline
standard deviation & 1.00389381427104 & 0.00709860123662279 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296559&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]# simulated values[/C][C]10000[/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]-0.010329390097002[/C][C]0.0100389381427104[/C][/ROW]
[ROW][C]standard deviation[/C][C]1.00389381427104[/C][C]0.00709860123662279[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296559&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296559&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	10000	-
true mean	0	-
true standard deviation	1	-
mean	-0.010329390097002	0.0100389381427104
standard deviation	1.00389381427104	0.00709860123662279

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[-4,-3.5[	-3.75	1	1e-04	1e-04	2e-04
[-3.5,-3[	-3.25	15	0.0015	0.0016	0.003
[-3,-2.5[	-2.75	50	0.005	0.0066	0.01
[-2.5,-2[	-2.25	196	0.0196	0.0262	0.0392
[-2,-1.5[	-1.75	444	0.0444	0.0706	0.0888
[-1.5,-1[	-1.25	883	0.0883	0.1589	0.1766
[-1,-0.5[	-0.75	1491	0.1491	0.308	0.2982
[-0.5,0[	-0.25	1925	0.1925	0.5005	0.385
[0,0.5[	0.25	1977	0.1977	0.6982	0.3954
[0.5,1[	0.75	1430	0.143	0.8412	0.286
[1,1.5[	1.25	933	0.0933	0.9345	0.1866
[1.5,2[	1.75	416	0.0416	0.9761	0.0832
[2,2.5[	2.25	182	0.0182	0.9943	0.0364
[2.5,3[	2.75	40	0.004	0.9983	0.008
[3,3.5[	3.25	14	0.0014	0.9997	0.0028
[3.5,4[	3.75	2	2e-04	0.9999	4e-04
[4,4.5[	4.25	0	0	0.9999	0
[4.5,5]	4.75	1	1e-04	1	2e-04

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[-4,-3.5[ & -3.75 & 1 & 1e-04 & 1e-04 & 2e-04 \tabularnewline
[-3.5,-3[ & -3.25 & 15 & 0.0015 & 0.0016 & 0.003 \tabularnewline
[-3,-2.5[ & -2.75 & 50 & 0.005 & 0.0066 & 0.01 \tabularnewline
[-2.5,-2[ & -2.25 & 196 & 0.0196 & 0.0262 & 0.0392 \tabularnewline
[-2,-1.5[ & -1.75 & 444 & 0.0444 & 0.0706 & 0.0888 \tabularnewline
[-1.5,-1[ & -1.25 & 883 & 0.0883 & 0.1589 & 0.1766 \tabularnewline
[-1,-0.5[ & -0.75 & 1491 & 0.1491 & 0.308 & 0.2982 \tabularnewline
[-0.5,0[ & -0.25 & 1925 & 0.1925 & 0.5005 & 0.385 \tabularnewline
[0,0.5[ & 0.25 & 1977 & 0.1977 & 0.6982 & 0.3954 \tabularnewline
[0.5,1[ & 0.75 & 1430 & 0.143 & 0.8412 & 0.286 \tabularnewline
[1,1.5[ & 1.25 & 933 & 0.0933 & 0.9345 & 0.1866 \tabularnewline
[1.5,2[ & 1.75 & 416 & 0.0416 & 0.9761 & 0.0832 \tabularnewline
[2,2.5[ & 2.25 & 182 & 0.0182 & 0.9943 & 0.0364 \tabularnewline
[2.5,3[ & 2.75 & 40 & 0.004 & 0.9983 & 0.008 \tabularnewline
[3,3.5[ & 3.25 & 14 & 0.0014 & 0.9997 & 0.0028 \tabularnewline
[3.5,4[ & 3.75 & 2 & 2e-04 & 0.9999 & 4e-04 \tabularnewline
[4,4.5[ & 4.25 & 0 & 0 & 0.9999 & 0 \tabularnewline
[4.5,5] & 4.75 & 1 & 1e-04 & 1 & 2e-04 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296559&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][-4,-3.5[[/C][C]-3.75[/C][C]1[/C][C]1e-04[/C][C]1e-04[/C][C]2e-04[/C][/ROW]
[ROW][C][-3.5,-3[[/C][C]-3.25[/C][C]15[/C][C]0.0015[/C][C]0.0016[/C][C]0.003[/C][/ROW]
[ROW][C][-3,-2.5[[/C][C]-2.75[/C][C]50[/C][C]0.005[/C][C]0.0066[/C][C]0.01[/C][/ROW]
[ROW][C][-2.5,-2[[/C][C]-2.25[/C][C]196[/C][C]0.0196[/C][C]0.0262[/C][C]0.0392[/C][/ROW]
[ROW][C][-2,-1.5[[/C][C]-1.75[/C][C]444[/C][C]0.0444[/C][C]0.0706[/C][C]0.0888[/C][/ROW]
[ROW][C][-1.5,-1[[/C][C]-1.25[/C][C]883[/C][C]0.0883[/C][C]0.1589[/C][C]0.1766[/C][/ROW]
[ROW][C][-1,-0.5[[/C][C]-0.75[/C][C]1491[/C][C]0.1491[/C][C]0.308[/C][C]0.2982[/C][/ROW]
[ROW][C][-0.5,0[[/C][C]-0.25[/C][C]1925[/C][C]0.1925[/C][C]0.5005[/C][C]0.385[/C][/ROW]
[ROW][C][0,0.5[[/C][C]0.25[/C][C]1977[/C][C]0.1977[/C][C]0.6982[/C][C]0.3954[/C][/ROW]
[ROW][C][0.5,1[[/C][C]0.75[/C][C]1430[/C][C]0.143[/C][C]0.8412[/C][C]0.286[/C][/ROW]
[ROW][C][1,1.5[[/C][C]1.25[/C][C]933[/C][C]0.0933[/C][C]0.9345[/C][C]0.1866[/C][/ROW]
[ROW][C][1.5,2[[/C][C]1.75[/C][C]416[/C][C]0.0416[/C][C]0.9761[/C][C]0.0832[/C][/ROW]
[ROW][C][2,2.5[[/C][C]2.25[/C][C]182[/C][C]0.0182[/C][C]0.9943[/C][C]0.0364[/C][/ROW]
[ROW][C][2.5,3[[/C][C]2.75[/C][C]40[/C][C]0.004[/C][C]0.9983[/C][C]0.008[/C][/ROW]
[ROW][C][3,3.5[[/C][C]3.25[/C][C]14[/C][C]0.0014[/C][C]0.9997[/C][C]0.0028[/C][/ROW]
[ROW][C][3.5,4[[/C][C]3.75[/C][C]2[/C][C]2e-04[/C][C]0.9999[/C][C]4e-04[/C][/ROW]
[ROW][C][4,4.5[[/C][C]4.25[/C][C]0[/C][C]0[/C][C]0.9999[/C][C]0[/C][/ROW]
[ROW][C][4.5,5][/C][C]4.75[/C][C]1[/C][C]1e-04[/C][C]1[/C][C]2e-04[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296559&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296559&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
[-4,-3.5[	-3.75	1	1e-04	1e-04	2e-04
[-3.5,-3[	-3.25	15	0.0015	0.0016	0.003
[-3,-2.5[	-2.75	50	0.005	0.0066	0.01
[-2.5,-2[	-2.25	196	0.0196	0.0262	0.0392
[-2,-1.5[	-1.75	444	0.0444	0.0706	0.0888
[-1.5,-1[	-1.25	883	0.0883	0.1589	0.1766
[-1,-0.5[	-0.75	1491	0.1491	0.308	0.2982
[-0.5,0[	-0.25	1925	0.1925	0.5005	0.385
[0,0.5[	0.25	1977	0.1977	0.6982	0.3954
[0.5,1[	0.75	1430	0.143	0.8412	0.286
[1,1.5[	1.25	933	0.0933	0.9345	0.1866
[1.5,2[	1.75	416	0.0416	0.9761	0.0832
[2,2.5[	2.25	182	0.0182	0.9943	0.0364
[2.5,3[	2.75	40	0.004	0.9983	0.008
[3,3.5[	3.25	14	0.0014	0.9997	0.0028
[3.5,4[	3.75	2	2e-04	0.9999	4e-04
[4,4.5[	4.25	0	0	0.9999	0
[4.5,5]	4.75	1	1e-04	1	2e-04

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 10000 ; par2 = 0 ; par3 = 1 ; par4 = 2 ; par5 = N ; par6 = 0 ;

Parameters (R input):

par1 = 10000 ; 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

Random generator met meer getallen -> Duidelijk goede fit -> normaalverdeli...

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code