## Free Statistics

of Irreproducible Research!

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, 26 Oct 2010 17:29:25 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/26/t1288114092e27ieilgpqbr7w0.htm/, Retrieved Mon, 22 Apr 2024 22:00:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=89455, Retrieved Mon, 22 Apr 2024 22:00:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Factor Analysis] [Sleep in Mammals ...] [2010-03-21 11:39:53] [b98453cac15ba1066b407e146608df68]
- RMPD  [Testing Mean with unknown Variance - Critical Value] [Hypothesis Test a...] [2010-10-19 11:45:26] [b98453cac15ba1066b407e146608df68]
- RMPD    [Testing Variance - p-value (probability)] [Vraag 8] [2010-10-22 09:56:50] [2960375a246cc0628590c95c4038a43c]
-   P       [Testing Variance - p-value (probability)] [Vraag 8 Mannen] [2010-10-22 11:46:46] [2960375a246cc0628590c95c4038a43c]
-             [Testing Variance - p-value (probability)] [] [2010-10-26 17:07:31] [f3d662049ef6875ba0c96bb458434b66]
- RM            [Testing Mean with known Variance - Sample Size] [] [2010-10-26 17:19:59] [f3d662049ef6875ba0c96bb458434b66]
- RM                [Minimum Sample Size - Testing Mean] [] [2010-10-26 17:29:25] [a7dcbcc9dd9573c89c41df6a7f8b5a0d] [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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89455&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89455&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89455&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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24

 Minimum Sample Size Population Size 105 Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance 13 z(alpha/2) + z(beta) 3.60481761149153 z(alpha) + z(beta) 3.28970725390294 Minimum Sample Size (2 sided test) 64.9899212937402 Minimum Sample Size (1 sided test) 60.3717860543336

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & 13 \tabularnewline
z(alpha/2) + z(beta) & 3.60481761149153 \tabularnewline
z(alpha) + z(beta) & 3.28970725390294 \tabularnewline
Minimum Sample Size (2 sided test) & 64.9899212937402 \tabularnewline
Minimum Sample Size (1 sided test) & 60.3717860543336 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89455&T=1

[TABLE]
[ROW][C]Minimum Sample Size[/C][/ROW]
[ROW][C]Population Size[/C][C]105[/C][/ROW]
[ROW][C]Margin of Error[/C][C]1[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.95[/C][/ROW]
[ROW][C]Population Variance[/C][C]13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]3.60481761149153[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]3.28970725390294[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]64.9899212937402[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]60.3717860543336[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89455&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89455&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 Size 105 Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance 13 z(alpha/2) + z(beta) 3.60481761149153 z(alpha) + z(beta) 3.28970725390294 Minimum Sample Size (2 sided test) 64.9899212937402 Minimum Sample Size (1 sided test) 60.3717860543336

 Minimum Sample Size (for Infinite Populations) Population Size infinite Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance 13 z(alpha/2) + z(beta) 3.60481761149153 z(alpha) + z(beta) 3.28970725390294 Minimum Sample Size (2 sided test) 168.931230157553 Minimum Sample Size (1 sided test) 140.688259612961

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (for Infinite Populations) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & 13 \tabularnewline
z(alpha/2) + z(beta) & 3.60481761149153 \tabularnewline
z(alpha) + z(beta) & 3.28970725390294 \tabularnewline
Minimum Sample Size (2 sided test) & 168.931230157553 \tabularnewline
Minimum Sample Size (1 sided test) & 140.688259612961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89455&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]1[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.95[/C][/ROW]
[ROW][C]Population Variance[/C][C]13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]3.60481761149153[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]3.28970725390294[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]168.931230157553[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]140.688259612961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89455&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89455&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 Size infinite Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance 13 z(alpha/2) + z(beta) 3.60481761149153 z(alpha) + z(beta) 3.28970725390294 Minimum Sample Size (2 sided test) 168.931230157553 Minimum Sample Size (1 sided test) 140.688259612961

 Minimum Sample Size (Unknown Population Variance) Population Size 105 Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.66675260030667 t(alpha) + t(beta) 3.34185224422168 Minimum Sample Size (2 sided test) 65.8301666270624 Minimum Sample Size (1 sided test) 61.1769076976371

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (Unknown Population Variance) \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 3.66675260030667 \tabularnewline
t(alpha) + t(beta) & 3.34185224422168 \tabularnewline
Minimum Sample Size (2 sided test) & 65.8301666270624 \tabularnewline
Minimum Sample Size (1 sided test) & 61.1769076976371 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89455&T=3

[TABLE]
[ROW][C]Minimum Sample Size (Unknown Population Variance)[/C][/ROW]
[ROW][C]Population Size[/C][C]105[/C][/ROW]
[ROW][C]Margin of Error[/C][C]1[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.95[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]3.66675260030667[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]3.34185224422168[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]65.8301666270624[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]61.1769076976371[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89455&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89455&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 Size 105 Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.66675260030667 t(alpha) + t(beta) 3.34185224422168 Minimum Sample Size (2 sided test) 65.8301666270624 Minimum Sample Size (1 sided test) 61.1769076976371

 Minimum Sample Size(Infinite Population, Unknown Population Variance) Population Size infinite Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.62816902032638 t(alpha) + t(beta) 3.31167025401028 Minimum Sample Size (2 sided test) 171.126935720729 Minimum Sample Size (1 sided test) 142.573078326854

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size(Infinite Population, Unknown Population Variance) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 3.62816902032638 \tabularnewline
t(alpha) + t(beta) & 3.31167025401028 \tabularnewline
Minimum Sample Size (2 sided test) & 171.126935720729 \tabularnewline
Minimum Sample Size (1 sided test) & 142.573078326854 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89455&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]1[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.95[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]3.62816902032638[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]3.31167025401028[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]171.126935720729[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]142.573078326854[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89455&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89455&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 Size infinite Margin of Error 1 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.62816902032638 t(alpha) + t(beta) 3.31167025401028 Minimum Sample Size (2 sided test) 171.126935720729 Minimum Sample Size (1 sided test) 142.573078326854

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*zz2one <- z1*z1z24 <- z2 * par4z24one <- z2one * par4npop <- array(NA, 200)ppop <- array(NA, 200)for (i in 1:200){ppop[i] <- i * 100npop[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 * par2num <- par1 * z24denom <- z24 + (par1 - 1) * par2sq(n <- num/denom)num1 <- par1 * z24onedenom1 <- 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*zz2one <- z1*z1z24 <- z2 * par4z24one <- z2one * par4par2sq <- par2 * par2num <- par1 * z24denom <- z24 + (par1 - 1) * par2sq(n <- num/denom)num1 <- par1 * z24onedenom1 <- 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*zz2one <- z1*z1z24 <- z2 * par4z24one <- 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')