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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesismean4.wasp
Title produced by softwareTesting Mean with known Variance - Sample Size
Date of computationTue, 26 Oct 2010 18:09:06 +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/t12881164521y77bgplbipyha6.htm/, Retrieved Sat, 27 Apr 2024 20:01:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=89499, Retrieved Sat, 27 Apr 2024 20:01:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsDMA
Estimated Impact104

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]
F RMPD    [Testing Mean with known Variance - Sample Size] [Workshop 4 - Ques...] [2010-10-26 18:05:42] [74be16979710d4c4e7c6647856088456]
F   P         [Testing Mean with known Variance - Sample Size] [Workshop 4 - Ques...] [2010-10-26 18:09:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2010-10-31 16:49:02 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
Opnieuw werd de waarde bij population variance fout ingevuld, de variantie die we hier veronderstellen is namelijk 13. Een correcte uitvoering is hier terug te vinden: http://www.freestatistics.org/blog/date/2010/Oct/26/t128804417712kobyzof3vdbjb.htm/

We zien hier dat voor deze gegevens de minimale steekproef gelijk is aan 93. De conclusie die we hier moeten trekken houdt dan ook verband met deze steekproef en niet met de variantie. We kunnen wel stellen dat de minimale steekproef omlaag gaat wanneer de type 2 fout stijgt. We moeten in het geval van onze waarnemingen (steekproef van 98) dus kiezen voor een β- fout gelegen tussen 5% (minimale steekproef van 141) en 15% (minimale steekproef van 93).

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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'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=89499&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=89499&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89499&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'Gwilym Jenkins' @ 72.249.127.135






Testing Mean with known Variance
population variance0.13
null hypothesis about mean20
alternative hypothesis about mean21
type I error0.05
type II error0.15
sample size0.934609008392543

\begin{tabular}{lllllllll}
\hline
Testing Mean with known Variance \tabularnewline
population variance & 0.13 \tabularnewline
null hypothesis about mean & 20 \tabularnewline
alternative hypothesis about mean & 21 \tabularnewline
type I error & 0.05 \tabularnewline
type II error & 0.15 \tabularnewline
sample size & 0.934609008392543 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=89499&T=1

[TABLE]
[ROW][C]Testing Mean with known Variance[/C][/ROW]
[ROW][C]population variance[/C][C]0.13[/C][/ROW]
[ROW][C]null hypothesis about mean[/C][C]20[/C][/ROW]
[ROW][C]alternative hypothesis about mean[/C][C]21[/C][/ROW]
[ROW][C]type I error[/C][C]0.05[/C][/ROW]
[ROW][C]type II error[/C][C]0.15[/C][/ROW]
[ROW][C]sample size[/C][C]0.934609008392543[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=89499&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=89499&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:

Testing Mean with known Variance
population variance0.13
null hypothesis about mean20
alternative hypothesis about mean21
type I error0.05
type II error0.15
sample size0.934609008392543


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.13 ; par2 = 20 ; par3 = 21 ; par4 = 0.05 ; par5 = 0.15 ;
Parameters (R input):
par1 = 0.13 ; par2 = 20 ; par3 = 21 ; par4 = 0.05 ; par5 = 0.15 ;
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)
c <- 'NA'
csn <- abs(qnorm(par5))
if (par2 == par3)
{
conclusion <- 'Error: the null hypothesis and alternative hypothesis must not be equal.'
}
ua <- abs(qnorm(par4))
ub <- qnorm(par5)
c <- (par2+ua/ub*(-par3))/(1-(ua/ub))
sqrtn <- ua*sqrt(par1)/(c - par2)
samplesize <- sqrtn * sqrtn
ua
ub
c
sqrtn
samplesize
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_mean_knownvar.htm','Testing Mean with known Variance','learn more about Statistical Hypothesis Testing about the Mean when the Variance is known'),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'population variance',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'null hypothesis about mean',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alternative hypothesis about mean',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'type I error',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'type II error',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_mean_knownvar.htm#ex4','sample size','example'),header=TRUE)
a<-table.element(a,samplesize)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')