FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_samplenorm.wasp
Title produced by softwareMinimum Sample Size - Testing Mean
Date of computationTue, 23 Oct 2012 13:08:38 -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/2012/Oct/23/t1351012134gxdifuz6najxwt0.htm/, Retrieved Fri, 09 May 2025 18:44:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=183126, Retrieved Fri, 09 May 2025 18:44:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

Tree of Dependent Computations

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: Male ] [2010-10-22 09:14:17] [74deae64b71f9d77c839af86f7c687b5]
- RMPD      [Testing Mean with known Variance - Sample Size] [Vraag 9: Minimum ...] [2010-10-22 12:33:36] [74deae64b71f9d77c839af86f7c687b5]
F RMP         [Minimum Sample Size - Testing Mean] [WS4 Q11] [2010-10-24 11:23:12] [afe9379cca749d06b3d6872e02cc47ed]
- R P             [Minimum Sample Size - Testing Mean] [Q11] [2012-10-23 17:08:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RMPD              [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q1] [2012-10-29 21:27:39] [77d02b0cf2cecd023ffa9a06f056f18d]
- R  D                [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q2] [2012-10-29 21:32:29] [77d02b0cf2cecd023ffa9a06f056f18d]
-    D                  [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q3] [2012-10-29 21:36:10] [77d02b0cf2cecd023ffa9a06f056f18d]
- RMPD                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q6] [2012-10-29 21:53:23] [77d02b0cf2cecd023ffa9a06f056f18d]
- R P                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q6 - deel 2] [2012-10-29 22:00:33] [77d02b0cf2cecd023ffa9a06f056f18d]
-    D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q7 deel 1] [2012-10-29 22:07:14] [77d02b0cf2cecd023ffa9a06f056f18d]
-                             [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [WS5 Q7 deel 2] [2012-10-29 22:10:21] [77d02b0cf2cecd023ffa9a06f056f18d]
-   P                           [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 7b] [2012-10-31 02:13:22] [3ae574fa1d645ef9b19cadb6c0dbd022]
- RM D                        [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q5 deel 1] [2012-10-29 22:16:21] [77d02b0cf2cecd023ffa9a06f056f18d]
- R  D                          [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q5 deel 2] [2012-10-29 22:18:34] [77d02b0cf2cecd023ffa9a06f056f18d]
-    D                            [Paired and Unpaired Two Samples Tests about the Mean] [WS5 Q5 deel 3] [2012-10-29 22:22:19] [77d02b0cf2cecd023ffa9a06f056f18d]
- RM D                            [Two-Way ANOVA] [WS5 Q8] [2012-10-29 22:30:47] [77d02b0cf2cecd023ffa9a06f056f18d]
- R P                               [Two-Way ANOVA] [W5 - Vraag 8] [2012-10-31 00:35:54] [3ae574fa1d645ef9b19cadb6c0dbd022]
- R P                       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6d] [2012-10-31 00:26:50] [3ae574fa1d645ef9b19cadb6c0dbd022]
- R P                       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6e] [2012-10-31 00:27:57] [3ae574fa1d645ef9b19cadb6c0dbd022]
- R  D                        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 7] [2012-10-31 00:33:26] [3ae574fa1d645ef9b19cadb6c0dbd022]
-   P                       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6f] [2012-10-31 02:04:14] [3ae574fa1d645ef9b19cadb6c0dbd022]
-   P                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6b] [2012-10-31 00:23:02] [3ae574fa1d645ef9b19cadb6c0dbd022]
-   P                     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6c] [2012-10-31 00:24:13] [3ae574fa1d645ef9b19cadb6c0dbd022]
-                     [Paired and Unpaired Two Samples Tests about the Mean] [W5 - Vraag 1] [2012-10-30 23:48:02] [3ae574fa1d645ef9b19cadb6c0dbd022]
- R  D                  [Paired and Unpaired Two Samples Tests about the Mean] [W5 - Vraag 2] [2012-10-30 23:54:26] [3ae574fa1d645ef9b19cadb6c0dbd022]
-    D                    [Paired and Unpaired Two Samples Tests about the Mean] [W5 - Vraag 3] [2012-10-30 23:55:59] [3ae574fa1d645ef9b19cadb6c0dbd022]
-    D                      [Paired and Unpaired Two Samples Tests about the Mean] [W5 - Vraag 5a] [2012-10-31 00:01:30] [3ae574fa1d645ef9b19cadb6c0dbd022]
-    D                        [Paired and Unpaired Two Samples Tests about the Mean] [W5 - Vraag 5b] [2012-10-31 00:03:43] [3ae574fa1d645ef9b19cadb6c0dbd022]
-    D                          [Paired and Unpaired Two Samples Tests about the Mean] [W5 - Vraag 5c] [2012-10-31 00:06:31] [3ae574fa1d645ef9b19cadb6c0dbd022]
- RM D                            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6a] [2012-10-31 00:09:29] [3ae574fa1d645ef9b19cadb6c0dbd022]
- RM                                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [W5 - Vraag 6a] [2012-10-31 00:10:53] [3ae574fa1d645ef9b19cadb6c0dbd022]
Feedback Forum

Post a new message

Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183126&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183126&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183126&T=0

As an alternative you can also use a QR Code:  
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'Sir Maurice George Kendall' @ kendall.wessa.net






Minimum Sample Size
Population Size105
Margin of Error0.05
Confidence0.95
Power0.98
Population Variance0.13
z(alpha/2) + z(beta)4.01371289517188
z(alpha) + z(beta)3.69860253758329
Minimum Sample Size (2 sided test)93.4041269147139
Minimum Sample Size (1 sided test)91.6068530689202

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 105 \tabularnewline
Margin of Error & 0.05 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.98 \tabularnewline
Population Variance & 0.13 \tabularnewline
z(alpha/2) + z(beta) & 4.01371289517188 \tabularnewline
z(alpha) + z(beta) & 3.69860253758329 \tabularnewline
Minimum Sample Size (2 sided test) & 93.4041269147139 \tabularnewline
Minimum Sample Size (1 sided test) & 91.6068530689202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183126&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]0.98[/C][/ROW]
[ROW][C]Population Variance[/C][C]0.13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]4.01371289517188[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]3.69860253758329[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]93.4041269147139[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]91.6068530689202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183126&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183126&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Minimum Sample Size
Population Size105
Margin of Error0.05
Confidence0.95
Power0.98
Population Variance0.13
z(alpha/2) + z(beta)4.01371289517188
z(alpha) + z(beta)3.69860253758329
Minimum Sample Size (2 sided test)93.4041269147139
Minimum Sample Size (1 sided test)91.6068530689202






Minimum Sample Size (for Infinite Populations)
Population Sizeinfinite
Margin of Error0.05
Confidence0.95
Power0.98
Population Variance0.13
z(alpha/2) + z(beta)4.01371289517188
z(alpha) + z(beta)3.69860253758329
Minimum Sample Size (2 sided test)837.714342653188
Minimum Sample Size (1 sided test)711.342358012914

\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 & 0.98 \tabularnewline
Population Variance & 0.13 \tabularnewline
z(alpha/2) + z(beta) & 4.01371289517188 \tabularnewline
z(alpha) + z(beta) & 3.69860253758329 \tabularnewline
Minimum Sample Size (2 sided test) & 837.714342653188 \tabularnewline
Minimum Sample Size (1 sided test) & 711.342358012914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183126&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]0.98[/C][/ROW]
[ROW][C]Population Variance[/C][C]0.13[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]4.01371289517188[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]3.69860253758329[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]837.714342653188[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]711.342358012914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183126&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183126&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Minimum Sample Size (for Infinite Populations)
Population Sizeinfinite
Margin of Error0.05
Confidence0.95
Power0.98
Population Variance0.13
z(alpha/2) + z(beta)4.01371289517188
z(alpha) + z(beta)3.69860253758329
Minimum Sample Size (2 sided test)837.714342653188
Minimum Sample Size (1 sided test)711.342358012914






Minimum Sample Size (Unknown Population Variance)
Population Size105
Margin of Error0.05
Confidence0.95
Power0.98
Population Varianceunknown
t(alpha/2) + t(beta)4.06911602697858
t(alpha) + t(beta)3.74558211896858
Minimum Sample Size (2 sided test)93.6839457102765
Minimum Sample Size (1 sided test)91.8990610288892

\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 & 0.98 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 4.06911602697858 \tabularnewline
t(alpha) + t(beta) & 3.74558211896858 \tabularnewline
Minimum Sample Size (2 sided test) & 93.6839457102765 \tabularnewline
Minimum Sample Size (1 sided test) & 91.8990610288892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183126&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]0.98[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]4.06911602697858[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]3.74558211896858[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]93.6839457102765[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]91.8990610288892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183126&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183126&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Minimum Sample Size (Unknown Population Variance)
Population Size105
Margin of Error0.05
Confidence0.95
Power0.98
Population Varianceunknown
t(alpha/2) + t(beta)4.06911602697858
t(alpha) + t(beta)3.74558211896858
Minimum Sample Size (2 sided test)93.6839457102765
Minimum Sample Size (1 sided test)91.8990610288892






Minimum Sample Size(Infinite Population, Unknown Population Variance)
Population Sizeinfinite
Margin of Error0.05
Confidence0.95
Power0.98
Population Varianceunknown
t(alpha/2) + t(beta)4.01975890804405
t(alpha) + t(beta)3.70452874334793
Minimum Sample Size (2 sided test)840.240007297573
Minimum Sample Size (1 sided test)713.623726935132

\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 & 0.98 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 4.01975890804405 \tabularnewline
t(alpha) + t(beta) & 3.70452874334793 \tabularnewline
Minimum Sample Size (2 sided test) & 840.240007297573 \tabularnewline
Minimum Sample Size (1 sided test) & 713.623726935132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=183126&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]0.98[/C][/ROW]
[ROW][C]Population Variance[/C][C]unknown[/C][/ROW]
[ROW][C]t(alpha/2) + t(beta)[/C][C]4.01975890804405[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]3.70452874334793[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]840.240007297573[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]713.623726935132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=183126&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=183126&T=4

As an alternative you can also use a QR Code:  
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 Error0.05
Confidence0.95
Power0.98
Population Varianceunknown
t(alpha/2) + t(beta)4.01975890804405
t(alpha) + t(beta)3.70452874334793
Minimum Sample Size (2 sided test)840.240007297573
Minimum Sample Size (1 sided test)713.623726935132


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 105 ; par2 = 0.05 ; par3 = 0.95 ; par4 = 0.13 ; par5 = 0.98 ;
Parameters (R input):
par1 = 105 ; par2 = 0.05 ; par3 = 0.95 ; par4 = 0.13 ; par5 = 0.98 ;
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')