## 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 computationFri, 22 Oct 2010 09:18:45 +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/22/t12877391791qtq5n5dv8e1g4p.htm/, Retrieved Mon, 15 Apr 2024 14:56:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=87346, Retrieved Mon, 15 Apr 2024 14:56:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172
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]
-   PD    [Testing Mean with unknown Variance - Critical Value] [WS4: vraag 7] [2010-10-22 08:43:56] [1fd136673b2a4fecb5c545b9b4a05d64]
- RMPD        [Minimum Sample Size - Testing Mean] [WS4: vraag 11 A] [2010-10-22 09:18:45] [380f6bceef280be3d93cc6fafd18141e] [Current]
-   P           [Minimum Sample Size - Testing Mean] [ws4.1.11 A] [2010-10-25 19:49:30] [e4076051fbfb461c886b1e223cd7862f]
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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 'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87346&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87346&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87346&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 'RServer@AstonUniversity' @ vre.aston.ac.uk

 Minimum Sample Size Population Size 105 Margin of Error 0.01 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) 102.857940020772 Minimum Sample Size (1 sided test) 101.984430457313

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.01 \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) & 102.857940020772 \tabularnewline
Minimum Sample Size (1 sided test) & 101.984430457313 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87346&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]0.01[/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]102.857940020772[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]101.984430457313[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87346&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87346&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 0.01 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) 102.857940020772 Minimum Sample Size (1 sided test) 101.984430457313

 Minimum Sample Size (for Infinite Populations) Population Size infinite Margin of Error 0.01 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) 4993.89646690236 Minimum Sample Size (1 sided test) 3517.20649032404

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (for Infinite Populations) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.01 \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) & 4993.89646690236 \tabularnewline
Minimum Sample Size (1 sided test) & 3517.20649032404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87346&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]0.01[/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]4993.89646690236[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]3517.20649032404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87346&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87346&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 0.01 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) 4993.89646690236 Minimum Sample Size (1 sided test) 3517.20649032404

 Minimum Sample Size (Unknown Population Variance) Population Size 105 Margin of Error 0.01 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) 1.98352846301897 t(alpha) + t(beta) 1.66008299983989 Minimum Sample Size (2 sided test) 102.907525148271 Minimum Sample Size (1 sided test) 102.03795184117

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (Unknown Population Variance) \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.01 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.5 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 1.98352846301897 \tabularnewline
t(alpha) + t(beta) & 1.66008299983989 \tabularnewline
Minimum Sample Size (2 sided test) & 102.907525148271 \tabularnewline
Minimum Sample Size (1 sided test) & 102.03795184117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87346&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]0.01[/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]1.98352846301897[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]1.66008299983989[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]102.907525148271[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]102.03795184117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87346&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87346&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 0.01 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) 1.98352846301897 t(alpha) + t(beta) 1.66008299983989 Minimum Sample Size (2 sided test) 102.907525148271 Minimum Sample Size (1 sided test) 102.03795184117

 Minimum Sample Size(Infinite Population, Unknown Population Variance) Population Size infinite Margin of Error 0.01 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) 1.96043922704737 t(alpha) + t(beta) 1.64528709783361 Minimum Sample Size (2 sided test) 4996.3185518299 Minimum Sample Size (1 sided test) 3519.06052458706

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size(Infinite Population, Unknown Population Variance) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.01 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.5 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 1.96043922704737 \tabularnewline
t(alpha) + t(beta) & 1.64528709783361 \tabularnewline
Minimum Sample Size (2 sided test) & 4996.3185518299 \tabularnewline
Minimum Sample Size (1 sided test) & 3519.06052458706 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87346&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]0.01[/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]1.96043922704737[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]1.64528709783361[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]4996.3185518299[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]3519.06052458706[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87346&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87346&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 0.01 Confidence 0.95 Power 0.5 Population Variance unknown t(alpha/2) + t(beta) 1.96043922704737 t(alpha) + t(beta) 1.64528709783361 Minimum Sample Size (2 sided test) 4996.3185518299 Minimum Sample Size (1 sided test) 3519.06052458706

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')