## 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 13:48:17 +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/t1287755282e57s727bpfghhuy.htm/, Retrieved Sat, 25 May 2024 05:38:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=87498, Retrieved Sat, 25 May 2024 05:38:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202
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] [Vraag 4 - Intrins...] [2010-10-22 11:11:16] [6f0e7a2d1a07390e3505a2db8288f975]
- RM D      [Testing Mean with known Variance - Sample Size] [W4 Q9 - males] [2010-10-22 13:26:09] [6f0e7a2d1a07390e3505a2db8288f975]
- RM            [Minimum Sample Size - Testing Mean] [W4 Q11] [2010-10-22 13:48:17] [708f372e2a7a3c78ea31b4de2d1213f8] [Current]
F   P             [Minimum Sample Size - Testing Mean] [workshop 4 - taak 11] [2010-10-26 17:11:23] [956e8df26b41c50d9c6c2ec1b6a122a8]
Feedback Forum

Post a new message

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 5 seconds R Server 'George Udny Yule' @ 72.249.76.132

\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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87498&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87498&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87498&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 5 seconds R Server 'George Udny Yule' @ 72.249.76.132

 Minimum Sample Size Population Size 105 Margin of Error 0.05 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) 104.838644118997 Minimum Sample Size (1 sided test) 104.806311904276

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.05 \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) & 104.838644118997 \tabularnewline
Minimum Sample Size (1 sided test) & 104.806311904276 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87498&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]0.05[/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]104.838644118997[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]104.806311904276[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87498&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87498&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 0.05 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) 104.838644118997 Minimum Sample Size (1 sided test) 104.806311904276

 Minimum Sample Size (for Infinite Populations) Population Size infinite Margin of Error 0.05 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) 67572.4920630212 Minimum Sample Size (1 sided test) 56275.3038451845

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (for Infinite Populations) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.05 \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) & 67572.4920630212 \tabularnewline
Minimum Sample Size (1 sided test) & 56275.3038451845 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87498&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]0.05[/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]67572.4920630212[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]56275.3038451845[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87498&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87498&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 0.05 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) 67572.4920630212 Minimum Sample Size (1 sided test) 56275.3038451845

 Minimum Sample Size (Unknown Population Variance) Population Size 105 Margin of Error 0.05 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.64273441048846 t(alpha) + t(beta) 3.31933054000454 Minimum Sample Size (2 sided test) 104.841980677223 Minimum Sample Size (1 sided test) 104.809747371183

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (Unknown Population Variance) \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.05 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 3.64273441048846 \tabularnewline
t(alpha) + t(beta) & 3.31933054000454 \tabularnewline
Minimum Sample Size (2 sided test) & 104.841980677223 \tabularnewline
Minimum Sample Size (1 sided test) & 104.809747371183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87498&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]0.05[/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]3.64273441048846[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]3.31933054000454[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]104.841980677223[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]104.809747371183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87498&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87498&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 0.05 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.64273441048846 t(alpha) + t(beta) 3.31933054000454 Minimum Sample Size (2 sided test) 104.841980677223 Minimum Sample Size (1 sided test) 104.809747371183

 Minimum Sample Size(Infinite Population, Unknown Population Variance) Population Size infinite Margin of Error 0.05 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.60487527046942 t(alpha) + t(beta) 3.28976140985978 Minimum Sample Size (2 sided test) 67574.6537213382 Minimum Sample Size (1 sided test) 56277.1566957735

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size(Infinite Population, Unknown Population Variance) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.05 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 3.60487527046942 \tabularnewline
t(alpha) + t(beta) & 3.28976140985978 \tabularnewline
Minimum Sample Size (2 sided test) & 67574.6537213382 \tabularnewline
Minimum Sample Size (1 sided test) & 56277.1566957735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87498&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]0.05[/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]3.60487527046942[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]3.28976140985978[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]67574.6537213382[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]56277.1566957735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87498&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87498&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 0.05 Confidence 0.95 Power 0.95 Population Variance unknown t(alpha/2) + t(beta) 3.60487527046942 t(alpha) + t(beta) 3.28976140985978 Minimum Sample Size (2 sided test) 67574.6537213382 Minimum Sample Size (1 sided test) 56277.1566957735

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')