## 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 computationSun, 24 Oct 2010 14:13:31 +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/24/t1287929578k2c2ytzyf38jak9.htm/, Retrieved Mon, 24 Jun 2024 14:32:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=87855, Retrieved Mon, 24 Jun 2024 14:32:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact268
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]
F   PD    [Testing Mean with unknown Variance - Critical Value] [task 4: academic ...] [2010-10-22 07:53:14] [18a20458ff88c9ba38344d123a9464bc]
F    D      [Testing Mean with unknown Variance - Critical Value] [task 5: academic ...] [2010-10-22 08:06:35] [18a20458ff88c9ba38344d123a9464bc]
- RMPD          [Minimum Sample Size - Testing Mean] [task 11: academic...] [2010-10-24 14:13:31] [1b6bbf3cf94635fe119752c144706ab0] [Current]
-                 [Minimum Sample Size - Testing Mean] [] [2010-10-26 20:38:37] [76e72a1b37cce9a27058d2e4927e5bf5]
- R               [Minimum Sample Size - Testing Mean] [] [2010-10-26 21:02:32] [5278e0a58c5de897b31ce79607e774d7]
- R P             [Minimum Sample Size - Testing Mean] [Academic Motivati...] [2010-10-27 00:08:20] [b20a509e36241371274681d9edf773da]
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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 1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87855&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87855&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87855&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 1 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24

 Minimum Sample Size Population Size 105 Margin of Error 0.5 Confidence 0.95 Power 0.5 Population Variance 0.13 z(alpha/2) + z(beta) 1.95996398454005 z(alpha) + z(beta) 1.64485362695147 Minimum Sample Size (2 sided test) 1.97875926961299 Minimum Sample Size (1 sided test) 1.40145186875144

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.5 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.5 \tabularnewline
Population Variance & 0.13 \tabularnewline
z(alpha/2) + z(beta) & 1.95996398454005 \tabularnewline
z(alpha) + z(beta) & 1.64485362695147 \tabularnewline
Minimum Sample Size (2 sided test) & 1.97875926961299 \tabularnewline
Minimum Sample Size (1 sided test) & 1.40145186875144 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87855&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]0.5[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.5[/C][/ROW]
[ROW][C]Population Variance[/C][C]0.13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]1.95996398454005[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]1.64485362695147[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]1.97875926961299[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]1.40145186875144[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87855&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87855&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 0.5 Confidence 0.95 Power 0.5 Population Variance 0.13 z(alpha/2) + z(beta) 1.95996398454005 z(alpha) + z(beta) 1.64485362695147 Minimum Sample Size (2 sided test) 1.97875926961299 Minimum Sample Size (1 sided test) 1.40145186875144

 Minimum Sample Size (for Infinite Populations) Population Size infinite Margin of Error 0.5 Confidence 0.95 Power 0.5 Population Variance 0.13 z(alpha/2) + z(beta) 1.95996398454005 z(alpha) + z(beta) 1.64485362695147 Minimum Sample Size (2 sided test) 1.99755858676094 Minimum Sample Size (1 sided test) 1.40688259612961

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (for Infinite Populations) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.5 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.5 \tabularnewline
Population Variance & 0.13 \tabularnewline
z(alpha/2) + z(beta) & 1.95996398454005 \tabularnewline
z(alpha) + z(beta) & 1.64485362695147 \tabularnewline
Minimum Sample Size (2 sided test) & 1.99755858676094 \tabularnewline
Minimum Sample Size (1 sided test) & 1.40688259612961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87855&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]0.5[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.5[/C][/ROW]
[ROW][C]Population Variance[/C][C]0.13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]1.95996398454005[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]1.64485362695147[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]1.99755858676094[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]1.40688259612961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87855&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87855&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 0.5 Confidence 0.95 Power 0.5 Population Variance 0.13 z(alpha/2) + z(beta) 1.95996398454005 z(alpha) + z(beta) 1.64485362695147 Minimum Sample Size (2 sided test) 1.99755858676094 Minimum Sample Size (1 sided test) 1.40688259612961

 Minimum Sample Size (Unknown Population Variance) Population Size 105 Margin of Error 0.5 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) NaN t(alpha) + t(beta) NaN Minimum Sample Size (2 sided test) NaN Minimum Sample Size (1 sided test) NaN

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (Unknown Population Variance) \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.5 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.5 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & NaN \tabularnewline
t(alpha) + t(beta) & NaN \tabularnewline
Minimum Sample Size (2 sided test) & NaN \tabularnewline
Minimum Sample Size (1 sided test) & NaN \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87855&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]0.5[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.5[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]NaN[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]NaN[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]NaN[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]NaN[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87855&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87855&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 0.5 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) NaN t(alpha) + t(beta) NaN Minimum Sample Size (2 sided test) NaN Minimum Sample Size (1 sided test) NaN

 Minimum Sample Size(Infinite Population, Unknown Population Variance) Population Size infinite Margin of Error 0.5 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) NaN t(alpha) + t(beta) NaN Minimum Sample Size (2 sided test) NaN Minimum Sample Size (1 sided test) NaN

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size(Infinite Population, Unknown Population Variance) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.5 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.5 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & NaN \tabularnewline
t(alpha) + t(beta) & NaN \tabularnewline
Minimum Sample Size (2 sided test) & NaN \tabularnewline
Minimum Sample Size (1 sided test) & NaN \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87855&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]0.5[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.5[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]NaN[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]NaN[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]NaN[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]NaN[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87855&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87855&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 0.5 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) NaN t(alpha) + t(beta) NaN Minimum Sample Size (2 sided test) NaN Minimum Sample Size (1 sided test) NaN

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')