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Author's title

knowledge, attitude and practice in financial management among school child...

Author*Unverified author*
R Software Modulerwasp_sample.wasp
Title produced by softwareMinimum Sample Size - Testing Proportions
Date of computationSun, 11 May 2008 00:42:21 -0600
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/May/11/t1210488450y6anm8ybe75anzi.htm/, Retrieved Sun, 19 May 2024 21:35:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12248, Retrieved Sun, 19 May 2024 21:35:40 +0000
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Original text written by user:i am trying to corelate 2 states with no of college is 13300 and 8600 respectively. What will be my sample saiz and how will I analyse?
IsPrivate?No (this computation is public)
User-defined keywordsfinancial knowledge, financial attitude, financial practice and financial management
Estimated Impact233
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Minimum Sample Size - Testing Proportions] [knowledge, attitu...] [2008-05-11 06:42:21] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12248&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12248&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12248&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Minimum Sample Size
Population Size22000
Margin of Error0.05
Confidence0.95
Power0.8
Response Distribution (Proportion)0.4
z(alpha/2) + z(beta)2.80158521811297
z(alpha) + z(beta)2.48647486052439
Minimum Sample Size (2 sided test)728.572222673938
Minimum Sample Size (1 sided test)577.959328953073

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size \tabularnewline
Population Size & 22000 \tabularnewline
Margin of Error & 0.05 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.8 \tabularnewline
Response Distribution (Proportion) & 0.4 \tabularnewline
z(alpha/2) + z(beta) & 2.80158521811297 \tabularnewline
z(alpha) + z(beta) & 2.48647486052439 \tabularnewline
Minimum Sample Size (2 sided test) & 728.572222673938 \tabularnewline
Minimum Sample Size (1 sided test) & 577.959328953073 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12248&T=1

[TABLE]
[ROW][C]Minimum Sample Size[/C][/ROW]
[ROW][C]Population Size[/C][C]22000[/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]0.8[/C][/ROW]
[ROW][C]Response Distribution (Proportion)[/C][C]0.4[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]2.80158521811297[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]2.48647486052439[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]728.572222673938[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]577.959328953073[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12248&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12248&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 Size22000
Margin of Error0.05
Confidence0.95
Power0.8
Response Distribution (Proportion)0.4
z(alpha/2) + z(beta)2.80158521811297
z(alpha) + z(beta)2.48647486052439
Minimum Sample Size (2 sided test)728.572222673938
Minimum Sample Size (1 sided test)577.959328953073







Minimum Sample Size (infinite population)
Population Sizeinfinite
Margin of Error0.05
Confidence0.95
Power0.8
Response Distribution (Proportion)0.4
z(alpha/2) + z(beta)2.80158521811297
z(alpha) + z(beta)2.48647486052439
Minimum Sample Size (2 sided test)753.492454497512
Minimum Sample Size (1 sided test)593.525494273897

\begin{tabular}{lllllllll}
\hline
Minimum Sample Size (infinite population) \tabularnewline
Population Size & infinite \tabularnewline
Margin of Error & 0.05 \tabularnewline
Confidence & 0.95 \tabularnewline
Power & 0.8 \tabularnewline
Response Distribution (Proportion) & 0.4 \tabularnewline
z(alpha/2) + z(beta) & 2.80158521811297 \tabularnewline
z(alpha) + z(beta) & 2.48647486052439 \tabularnewline
Minimum Sample Size (2 sided test) & 753.492454497512 \tabularnewline
Minimum Sample Size (1 sided test) & 593.525494273897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12248&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]0.05[/C][/ROW]
[ROW][C]Confidence[/C][C]0.95[/C][/ROW]
[ROW][C]Power[/C][C]0.8[/C][/ROW]
[ROW][C]Response Distribution (Proportion)[/C][C]0.4[/C][/ROW]
[ROW][C]z(alpha/2) + z(beta)[/C][C]2.80158521811297[/C][/ROW]
[ROW][C]z(alpha) + z(beta)[/C][C]2.48647486052439[/C][/ROW]
[ROW][C]Minimum Sample Size (2 sided test)[/C][C]753.492454497512[/C][/ROW]
[ROW][C]Minimum Sample Size (1 sided test)[/C][C]593.525494273897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12248&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12248&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 (infinite population)
Population Sizeinfinite
Margin of Error0.05
Confidence0.95
Power0.8
Response Distribution (Proportion)0.4
z(alpha/2) + z(beta)2.80158521811297
z(alpha) + z(beta)2.48647486052439
Minimum Sample Size (2 sided test)753.492454497512
Minimum Sample Size (1 sided test)593.525494273897



Parameters (Session):
par1 = 22000 ; par2 = 0.05 ; par3 = 0.95 ; par4 = 0.40 ; par5 = 0.80 ;
Parameters (R input):
par1 = 22000 ; par2 = 0.05 ; par3 = 0.95 ; par4 = 0.40 ; par5 = 0.80 ;
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')