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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_sample.wasp
Title produced by softwareMinimum Sample Size - Testing Proportions
Date of computationSun, 09 Nov 2008 13:51:51 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/09/t1226264024e45b16acac6gadh.htm/, Retrieved Tue, 14 May 2024 03:38:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22873, Retrieved Tue, 14 May 2024 03:38:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Testing Population Proportion - Critical Value] [vraag 1] [2008-11-09 20:15:31] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM      [Minimum Sample Size - Testing Proportions] [vraag 4] [2008-11-09 20:51:51] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
F           [Minimum Sample Size - Testing Proportions] [vraag 4] [2008-11-09 20:55:06] [c45c87b96bbf32ffc2144fc37d767b2e]
F RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:10:08] [c45c87b96bbf32ffc2144fc37d767b2e]
F RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:12:27] [c45c87b96bbf32ffc2144fc37d767b2e]
- RMPD        [Partial Correlation] [vraag 1] [2008-11-24 20:29:41] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:14:06] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:16:55] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:19:51] [c45c87b96bbf32ffc2144fc37d767b2e]
F RM D      [Hierarchical Clustering] [vraag 2] [2008-11-09 21:30:22] [c45c87b96bbf32ffc2144fc37d767b2e]
-   PD        [Hierarchical Clustering] [dendrogram] [2008-12-21 14:09:41] [c45c87b96bbf32ffc2144fc37d767b2e]
- RMPD          [Histogram] [Histogram groep 1] [2008-12-21 16:48:39] [c45c87b96bbf32ffc2144fc37d767b2e]
-  M D          [Hierarchical Clustering] [] [2009-12-30 13:17:52] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   PD            [Hierarchical Clustering] [] [2009-12-30 14:13:32] [d2d412c7f4d35ffbf5ee5ee89db327d4]
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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=22873&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=22873&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22873&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 Size20000
Margin of Error0.07
Confidence0.95
Power0.95
Response Distribution (Proportion)0.5
z(alpha/2) + z(beta)3.60481761149153
z(alpha) + z(beta)3.28970725390294
Minimum Sample Size (2 sided test)641.75351476443
Minimum Sample Size (1 sided test)537.343826472914

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 20000 \tabularnewline
Margin of Error & 0.07 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Response Distribution (Proportion) & 0.5 \tabularnewline
z(alpha/2) + z(beta) & 3.60481761149153 \tabularnewline
z(alpha) + z(beta) & 3.28970725390294 \tabularnewline
Minimum Sample Size (2 sided test) & 641.75351476443 \tabularnewline
Minimum Sample Size (1 sided test) & 537.343826472914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22873&T=1

[TABLE]
[ROW][C]Minimum Sample Size[/C][/ROW]
[ROW][C]Population Size[/C][C]20000[/C][/ROW]
[ROW][C]Margin of Error[/C][C]0.07[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.95[/C][/ROW]
[ROW][C]Response Distribution (Proportion)[/C][C]0.5[/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]641.75351476443[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]537.343826472914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22873&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22873&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 Size20000
Margin of Error0.07
Confidence0.95
Power0.95
Response Distribution (Proportion)0.5
z(alpha/2) + z(beta)3.60481761149153
z(alpha) + z(beta)3.28970725390294
Minimum Sample Size (2 sided test)641.75351476443
Minimum Sample Size (1 sided test)537.343826472914






Minimum Sample Size (infinite population)
Population Sizeinfinite
Margin of Error0.07
Confidence0.95
Power0.95
Response Distribution (Proportion)0.5
z(alpha/2) + z(beta)3.60481761149153
z(alpha) + z(beta)3.28970725390294
Minimum Sample Size (2 sided test)662.995408781605
Minimum Sample Size (1 sided test)552.151725325594

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (infinite population) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.07 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.95 \tabularnewline
Response Distribution (Proportion) & 0.5 \tabularnewline
z(alpha/2) + z(beta) & 3.60481761149153 \tabularnewline
z(alpha) + z(beta) & 3.28970725390294 \tabularnewline
Minimum Sample Size (2 sided test) & 662.995408781605 \tabularnewline
Minimum Sample Size (1 sided test) & 552.151725325594 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22873&T=2

[TABLE]
[ROW][C]Minimum Sample Size (infinite population)[/C][/ROW]
[ROW][C]Population Size[/C][C]infinite[/C][/ROW]
[ROW][C]Margin of Error[/C][C]0.07[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.95[/C][/ROW]
[ROW][C]Response Distribution (Proportion)[/C][C]0.5[/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]662.995408781605[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]552.151725325594[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22873&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22873&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 (infinite population)
Population Sizeinfinite
Margin of Error0.07
Confidence0.95
Power0.95
Response Distribution (Proportion)0.5
z(alpha/2) + z(beta)3.60481761149153
z(alpha) + z(beta)3.28970725390294
Minimum Sample Size (2 sided test)662.995408781605
Minimum Sample Size (1 sided test)552.151725325594


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 98 ; par2 = 0.8571 ; par3 = 0.69 ; par4 = 0.05 ;
Parameters (R input):
par1 = 20000 ; par2 = 0.07 ; par3 = 0.95 ; par4 = 0.50 ; 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)))
dum <- z*z * par4*(1-par4)
dum1 <- z1*z1 * par4*(1-par4)
par22 <- par2*par2
npop <- array(NA, 200)
ppop <- array(NA, 200)
for (i in 1:200)
{
ppop[i] <- i * 100
npop[i] <- ppop[i] * dum / (dum + (ppop[i]-1)*par22)
}
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,' Response Rate = ')
dumtext <- paste(dumtext, par4)
mtext(dumtext)
grid()
dev.off()
(n <- par1 * dum / (dum + (par1-1)*par22))
(n1 <- par1 * dum1 / (dum1 + (par1-1)*par22))
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,'Response Distribution (Proportion)',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')
(n <- dum / par22)
(n1 <- dum1 / par22)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Minimum Sample Size (infinite population)',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,'Response Distribution (Proportion)',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')