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Description of Statistical Computation

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 18:54:34 +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/t12881192071txvyll6h6tusar.htm/, Retrieved Sun, 28 Apr 2024 00:21:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=89557, Retrieved Sun, 28 Apr 2024 00:21:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

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]
- RMPD    [Testing Mean with known Variance - Sample Size] [Sample Size] [2010-10-22 08:56:35] [2960375a246cc0628590c95c4038a43c]
F           [Testing Mean with known Variance - Sample Size] [question 9] [2010-10-24 11:29:22] [c1605865773cc027e55b238d879a644c]
-   P         [Testing Mean with known Variance - Sample Size] [vraag 10] [2010-10-26 18:38:36] [f4dc4aa51d65be851b8508203d9f6001]
- RM              [Minimum Sample Size - Testing Mean] [Minimum sample size] [2010-10-26 18:54:34] [7a87ed98a7b21a29d6a45388a9b7b229] [Current]
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Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89557&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89557&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89557&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Minimum Sample Size
Population Size120
Margin of Error1
Confidence0.9
Power0.95
Population Variance13
z(alpha/2) + z(beta)3.28970725390294
z(alpha) + z(beta)2.92640519249607
Minimum Sample Size (2 sided test)65.0109911734829
Minimum Sample Size (1 sided test)58.0020013224819

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 120 \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.9 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & 13 \tabularnewline
z(alpha/2) + z(beta) & 3.28970725390294 \tabularnewline
z(alpha) + z(beta) & 2.92640519249607 \tabularnewline
Minimum Sample Size (2 sided test) & 65.0109911734829 \tabularnewline
Minimum Sample Size (1 sided test) & 58.0020013224819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89557&T=1

[TABLE]
[ROW][C]Minimum Sample Size[/C][/ROW]
[ROW][C]Population Size[/C][C]120[/C][/ROW]
[ROW][C]Margin of Error[/C][C]1[/C][/ROW]
[ROW][C]Confidence[/C][C]0.9[/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]3.28970725390294[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]2.92640519249607[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]65.0109911734829[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]58.0020013224819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89557&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89557&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 Size120
Margin of Error1
Confidence0.9
Power0.95
Population Variance13
z(alpha/2) + z(beta)3.28970725390294
z(alpha) + z(beta)2.92640519249607
Minimum Sample Size (2 sided test)65.0109911734829
Minimum Sample Size (1 sided test)58.0020013224819






Minimum Sample Size (for Infinite Populations)
Population Sizeinfinite
Margin of Error1
Confidence0.9
Power0.95
Population Variance13
z(alpha/2) + z(beta)3.28970725390294
z(alpha) + z(beta)2.92640519249607
Minimum Sample Size (2 sided test)140.688259612961
Minimum Sample Size (1 sided test)111.330015558684

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (for Infinite Populations) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.9 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & 13 \tabularnewline
z(alpha/2) + z(beta) & 3.28970725390294 \tabularnewline
z(alpha) + z(beta) & 2.92640519249607 \tabularnewline
Minimum Sample Size (2 sided test) & 140.688259612961 \tabularnewline
Minimum Sample Size (1 sided test) & 111.330015558684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89557&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]0.9[/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]3.28970725390294[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]2.92640519249607[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]140.688259612961[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]111.330015558684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89557&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89557&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 Error1
Confidence0.9
Power0.95
Population Variance13
z(alpha/2) + z(beta)3.28970725390294
z(alpha) + z(beta)2.92640519249607
Minimum Sample Size (2 sided test)140.688259612961
Minimum Sample Size (1 sided test)111.330015558684






Minimum Sample Size (Unknown Population Variance)
Population Size120
Margin of Error1
Confidence0.9
Power0.95
Population Varianceunknown
t(alpha/2) + t(beta)3.33801763169042
t(alpha) + t(beta)2.96860842847345
Minimum Sample Size (2 sided test)65.8784840075178
Minimum Sample Size (1 sided test)58.8605109805349

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (Unknown Population Variance) \tabularnewline
Population Size & 120 \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.9 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 3.33801763169042 \tabularnewline
t(alpha) + t(beta) & 2.96860842847345 \tabularnewline
Minimum Sample Size (2 sided test) & 65.8784840075178 \tabularnewline
Minimum Sample Size (1 sided test) & 58.8605109805349 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89557&T=3

[TABLE]
[ROW][C]Minimum Sample Size (Unknown Population Variance)[/C][/ROW]
[ROW][C]Population Size[/C][C]120[/C][/ROW]
[ROW][C]Margin of Error[/C][C]1[/C][/ROW]
[ROW][C]Confidence[/C][C]0.9[/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]3.33801763169042[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]2.96860842847345[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]65.8784840075178[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]58.8605109805349[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89557&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89557&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 Size120
Margin of Error1
Confidence0.9
Power0.95
Population Varianceunknown
t(alpha/2) + t(beta)3.33801763169042
t(alpha) + t(beta)2.96860842847345
Minimum Sample Size (2 sided test)65.8784840075178
Minimum Sample Size (1 sided test)58.8605109805349






Minimum Sample Size(Infinite Population, Unknown Population Variance)
Population Sizeinfinite
Margin of Error1
Confidence0.9
Power0.95
Population Varianceunknown
t(alpha/2) + t(beta)3.31167025401028
t(alpha) + t(beta)2.9480539067487
Minimum Sample Size (2 sided test)142.573078326854
Minimum Sample Size (1 sided test)112.983283882252

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size(Infinite Population, Unknown Population Variance) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 1 \tabularnewline
Confidence & 0.9 \tabularnewline
Power & 0.95 \tabularnewline
Population Variance & unknown \tabularnewline
t(alpha/2) + t(beta) & 3.31167025401028 \tabularnewline
t(alpha) + t(beta) & 2.9480539067487 \tabularnewline
Minimum Sample Size (2 sided test) & 142.573078326854 \tabularnewline
Minimum Sample Size (1 sided test) & 112.983283882252 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89557&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]0.9[/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]3.31167025401028[/C][/ROW]
[ROW][C]t(alpha) + t(beta)[/C][C]2.9480539067487[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]142.573078326854[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]112.983283882252[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89557&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89557&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 Error1
Confidence0.9
Power0.95
Population Varianceunknown
t(alpha/2) + t(beta)3.31167025401028
t(alpha) + t(beta)2.9480539067487
Minimum Sample Size (2 sided test)142.573078326854
Minimum Sample Size (1 sided test)112.983283882252


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.95 ; par2 = 0.1714 ;
Parameters (R input):
par1 = 120 ; par2 = 1 ; par3 = 0.90 ; par4 = 13 ; par5 = 0.95 ;
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')