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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_samplenorm.wasp
Title produced by softwareMinimum Sample Size - Testing Mean
Date of computationTue, 29 Oct 2013 18:01:12 -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/2013/Oct/29/t1383084091klv4qk9xbg15c72.htm/, Retrieved Mon, 29 Apr 2024 17:36:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=220827, Retrieved Mon, 29 Apr 2024 17:36:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Testing Mean with unknown Variance - Critical Value] [WS 4: Vraag 3 Sof...] [2013-10-29 17:31:19] [d1ad2890024735eb49a4f5b5ae8e3b4b]
- RMPD  [Testing Variance - p-value (probability)] [Vraag 9: Female] [2013-10-29 21:27:31] [d1ad2890024735eb49a4f5b5ae8e3b4b]
- RM      [Testing Variance - Critical Value (Region)] [WS4: Vraag 9 Male] [2013-10-29 21:32:32] [d1ad2890024735eb49a4f5b5ae8e3b4b]
- RM        [Minimum Sample Size - Testing Mean] [WS4: Vraag 9 Male] [2013-10-29 21:49:31] [d1ad2890024735eb49a4f5b5ae8e3b4b]
- R           [Minimum Sample Size - Testing Mean] [Vraag 9: Male 20] [2013-10-29 21:53:10] [d1ad2890024735eb49a4f5b5ae8e3b4b]
-                 [Minimum Sample Size - Testing Mean] [WS4: Vraag 10 ] [2013-10-29 22:01:12] [0d4b5c001fcd12491258e86d922016e4] [Current]
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Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=220827&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]2 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=220827&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=220827&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Minimum Sample Size
Population Size98
Margin of Error0.15
Confidence0.85
Power0.2
Population Variance0.13
z(alpha/2) + z(beta)2.28115270451137
z(alpha) + z(beta)1.8780546230667
Minimum Sample Size (2 sided test)23.1882360301546
Minimum Sample Size (1 sided test)17.0142933064114

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 98 \tabularnewline
Margin of Error & 0.15 \tabularnewline
Confidence & 0.85 \tabularnewline
Power & 0.2 \tabularnewline
Population Variance & 0.13 \tabularnewline
z(alpha/2) + z(beta) & 2.28115270451137 \tabularnewline
z(alpha) + z(beta) & 1.8780546230667 \tabularnewline
Minimum Sample Size (2 sided test) & 23.1882360301546 \tabularnewline
Minimum Sample Size (1 sided test) & 17.0142933064114 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=220827&T=1

[TABLE]
[ROW][C]Minimum Sample Size[/C][/ROW]
[ROW][C]Population Size[/C][C]98[/C][/ROW]
[ROW][C]Margin of Error[/C][C]0.15[/C][/ROW]
[ROW][C]Confidence[/C][C]0.85[/C][/ROW]
[ROW][C]Power[/C][C]0.2[/C][/ROW]
[ROW][C]Population Variance[/C][C]0.13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]2.28115270451137[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]1.8780546230667[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]23.1882360301546[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]17.0142933064114[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=220827&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=220827&T=1

As an alternative you can also use a QR Code:  

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

Minimum Sample Size
Population Size98
Margin of Error0.15
Confidence0.85
Power0.2
Population Variance0.13
z(alpha/2) + z(beta)2.28115270451137
z(alpha) + z(beta)1.8780546230667
Minimum Sample Size (2 sided test)23.1882360301546
Minimum Sample Size (1 sided test)17.0142933064114







Minimum Sample Size (for Infinite Populations)
Population Sizeinfinite
Margin of Error0.15
Confidence0.85
Power0.2
Population Variance0.13
z(alpha/2) + z(beta)2.28115270451137
z(alpha) + z(beta)1.8780546230667
Minimum Sample Size (2 sided test)30.0655775986196
Minimum Sample Size (1 sided test)20.3787374106173

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (for Infinite Populations) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.15 \tabularnewline
Confidence & 0.85 \tabularnewline
Power & 0.2 \tabularnewline
Population Variance & 0.13 \tabularnewline
z(alpha/2) + z(beta) & 2.28115270451137 \tabularnewline
z(alpha) + z(beta) & 1.8780546230667 \tabularnewline
Minimum Sample Size (2 sided test) & 30.0655775986196 \tabularnewline
Minimum Sample Size (1 sided test) & 20.3787374106173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=220827&T=2

[TABLE]
[ROW][C]Minimum Sample Size (for Infinite Populations)[/C][/ROW]
[ROW][C]Population Size[/C][C]infinite[/C][/ROW]
[ROW][C]Margin of Error[/C][C]0.15[/C][/ROW]
[ROW][C]Confidence[/C][C]0.85[/C][/ROW]
[ROW][C]Power[/C][C]0.2[/C][/ROW]
[ROW][C]Population Variance[/C][C]0.13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]2.28115270451137[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]1.8780546230667[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]30.0655775986196[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]20.3787374106173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=220827&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=220827&T=2

As an alternative you can also use a QR Code:  

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

Minimum Sample Size (for Infinite Populations)
Population Sizeinfinite
Margin of Error0.15
Confidence0.85
Power0.2
Population Variance0.13
z(alpha/2) + z(beta)2.28115270451137
z(alpha) + z(beta)1.8780546230667
Minimum Sample Size (2 sided test)30.0655775986196
Minimum Sample Size (1 sided test)20.3787374106173







Minimum Sample Size (Unknown Population Variance)
Population Size98
Margin of Error0.15
Confidence0.85
Power0.2
Population Varianceunknown
t(alpha/2) + t(beta)2.34928417652502
t(alpha) + t(beta)1.93575109019662
Minimum Sample Size (2 sided test)24.2462388675298
Minimum Sample Size (1 sided test)17.8820718281853

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (Unknown Population Variance) \tabularnewline
Population Size & 98 \tabularnewline
Margin of Error & 0.15 \tabularnewline
Confidence & 0.85 \tabularnewline
Power & 0.2 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 2.34928417652502 \tabularnewline
t(alpha) + t(beta) & 1.93575109019662 \tabularnewline
Minimum Sample Size (2 sided test) & 24.2462388675298 \tabularnewline
Minimum Sample Size (1 sided test) & 17.8820718281853 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=220827&T=3

[TABLE]
[ROW][C]Minimum Sample Size (Unknown Population Variance)[/C][/ROW]
[ROW][C]Population Size[/C][C]98[/C][/ROW]
[ROW][C]Margin of Error[/C][C]0.15[/C][/ROW]
[ROW][C]Confidence[/C][C]0.85[/C][/ROW]
[ROW][C]Power[/C][C]0.2[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]2.34928417652502[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]1.93575109019662[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]24.2462388675298[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]17.8820718281853[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=220827&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=220827&T=3

As an alternative you can also use a QR Code:  

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

Minimum Sample Size (Unknown Population Variance)
Population Size98
Margin of Error0.15
Confidence0.85
Power0.2
Population Varianceunknown
t(alpha/2) + t(beta)2.34928417652502
t(alpha) + t(beta)1.93575109019662
Minimum Sample Size (2 sided test)24.2462388675298
Minimum Sample Size (1 sided test)17.8820718281853







Minimum Sample Size(Infinite Population, Unknown Population Variance)
Population Sizeinfinite
Margin of Error0.15
Confidence0.85
Power0.2
Population Varianceunknown
t(alpha/2) + t(beta)2.33277726097669
t(alpha) + t(beta)1.92548872281847
Minimum Sample Size (2 sided test)31.441798551684
Minimum Sample Size (1 sided test)21.4211505253841

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size(Infinite Population, Unknown Population Variance) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.15 \tabularnewline
Confidence & 0.85 \tabularnewline
Power & 0.2 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 2.33277726097669 \tabularnewline
t(alpha) + t(beta) & 1.92548872281847 \tabularnewline
Minimum Sample Size (2 sided test) & 31.441798551684 \tabularnewline
Minimum Sample Size (1 sided test) & 21.4211505253841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=220827&T=4

[TABLE]
[ROW][C]Minimum Sample Size(Infinite Population, Unknown Population Variance)[/C][/ROW]
[ROW][C]Population Size[/C][C]infinite[/C][/ROW]
[ROW][C]Margin of Error[/C][C]0.15[/C][/ROW]
[ROW][C]Confidence[/C][C]0.85[/C][/ROW]
[ROW][C]Power[/C][C]0.2[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]2.33277726097669[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]1.92548872281847[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]31.441798551684[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]21.4211505253841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=220827&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=220827&T=4

As an alternative you can also use a QR Code:  

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

Minimum Sample Size(Infinite Population, Unknown Population Variance)
Population Sizeinfinite
Margin of Error0.15
Confidence0.85
Power0.2
Population Varianceunknown
t(alpha/2) + t(beta)2.33277726097669
t(alpha) + t(beta)1.92548872281847
Minimum Sample Size (2 sided test)31.441798551684
Minimum Sample Size (1 sided test)21.4211505253841



Parameters (Session):
par1 = 0.95 ; par2 = 0 ;
Parameters (R input):
par1 = 98 ; par2 = 0.15 ; par3 = 0.85 ; par4 = 0.13 ; par5 = 0.20 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
(z <- abs(qnorm((1-par3)/2)) + abs(qnorm(1-par5)))
(z1 <- abs(qnorm(1-par3)) + abs(qnorm(1-par5)))
z2 <- z*z
z2one <- z1*z1
z24 <- z2 * par4
z24one <- z2one * par4
npop <- array(NA, 200)
ppop <- array(NA, 200)
for (i in 1:200)
{
ppop[i] <- i * 100
npop[i] <- ppop[i] * z24 / (z24 + (ppop[i] - 1) * par2*par2)
}
bitmap(file='pic1.png')
plot(ppop,npop, xlab='population size', ylab='sample size (2 sided test)', main = paste('Confidence',par3))
dumtext <- paste('Margin of error = ',par2)
dumtext <- paste(dumtext,' Population Var. = ')
dumtext <- paste(dumtext, par4)
mtext(dumtext)
grid()
dev.off()
par2sq <- par2 * par2
num <- par1 * z24
denom <- z24 + (par1 - 1) * par2sq
(n <- num/denom)
num1 <- par1 * z24one
denom1 <- z24one + (par1 - 1) * par2sq
(n1 <- num1/denom1)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Size',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Margin of Error',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Confidence',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Power',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Variance',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'z(alpha/2) + z(beta)',header=TRUE)
a<-table.element(a,z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'z(alpha) + z(beta)',header=TRUE)
a<-table.element(a,z1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (2 sided test)',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (1 sided test)',header=TRUE)
a<-table.element(a,n1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
(ni <- z24 / (par2sq))
(ni1 <- z24one / (par2sq))
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (for Infinite Populations)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Size',header=TRUE)
a<-table.element(a,'infinite')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Margin of Error',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Confidence',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Power',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Variance',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'z(alpha/2) + z(beta)',header=TRUE)
a<-table.element(a,z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'z(alpha) + z(beta)',header=TRUE)
a<-table.element(a,z1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (2 sided test)',header=TRUE)
a<-table.element(a,ni)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (1 sided test)',header=TRUE)
a<-table.element(a,ni1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
(z <- abs(qt((1-par3)/2,n-1)) + abs(qt(1-par5,n-1)))
(z1 <- abs(qt(1-par3,n1-1)) + abs(qt(1-par5,n1-1)))
z2 <- z*z
z2one <- z1*z1
z24 <- z2 * par4
z24one <- z2one * par4
par2sq <- par2 * par2
num <- par1 * z24
denom <- z24 + (par1 - 1) * par2sq
(n <- num/denom)
num1 <- par1 * z24one
denom1 <- z24one + (par1 - 1) * par2sq
(n1 <- num1/denom1)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (Unknown Population Variance)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Size',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Margin of Error',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Confidence',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Power',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Variance',header=TRUE)
a<-table.element(a,'unknown')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t(alpha/2) + t(beta)',header=TRUE)
a<-table.element(a,z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t(alpha) + t(beta)',header=TRUE)
a<-table.element(a,z1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (2 sided test)',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (1 sided test)',header=TRUE)
a<-table.element(a,n1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
(z <- abs(qt((1-par3)/2,ni-1)) + abs(qt(1-par5,ni-1)))
(z1 <- abs(qt(1-par3,ni1-1)) + abs(qt(1-par5,ni1-1)))
z2 <- z*z
z2one <- z1*z1
z24 <- z2 * par4
z24one <- z2one * par4
(ni <- z24 / (par2sq))
(ni1 <- z24one / (par2sq))
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size
(Infinite Population, Unknown Population Variance)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Size',header=TRUE)
a<-table.element(a,'infinite')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Margin of Error',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Confidence',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Power',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population Variance',header=TRUE)
a<-table.element(a,'unknown')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t(alpha/2) + t(beta)',header=TRUE)
a<-table.element(a,z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t(alpha) + t(beta)',header=TRUE)
a<-table.element(a,z1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (2 sided test)',header=TRUE)
a<-table.element(a,ni)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (1 sided test)',header=TRUE)
a<-table.element(a,ni1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')