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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 computationWed, 12 Nov 2008 03:45:04 -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/12/t12264868820hwnp4t7fvljg8t.htm/, Retrieved Sun, 19 May 2024 12:15:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24090, Retrieved Sun, 19 May 2024 12:15:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact205

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Testing Mean with known Variance - Sample Size] [Q4 pork] [2008-11-12 10:45:04] [b09437381d488816ab9f5cf07e347c02] [Current]
-   P     [Testing Mean with known Variance - Sample Size] [pork quality q4] [2008-11-19 16:31:55] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-11-19 16:33:47 [Ken Wright] [reply] 
fout besluit(juiste link:http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/19/t1227112353hmlp1b74usxpjyn.htm) , dus om de pakkans te vergrote zullen we een veel grotere sample size moeten nemen, van zelfs 32466 worsten, dus dit zou veel te veel tijd en geld kosten
2008-11-23 17:02:24 [Aurélie Van Impe] [reply] 
Je besluit is niet correct. Als je de proef nauwkeuriger wil maken, en dus de pakkans groter, dan moet de variantie verkleind worden. Om dit te bereiken moet de steekproefgrootte (sample size) verhoogd worden naar 32466.5 worsten. Dit kost echter veel geld en tijd, en bijgevolg is een steekproef van deze omvang economisch niet realistisch en dus niet haalbaar.
2008-11-23 18:24:44 [c97d2ae59c98cf77a04815c1edffab5a] [reply] 
de student heeft de foute gegevens ingevoerd en hierdoor ook een foute conclusie geformuleerd. ipv een type-II error van 95% moet er een type-II error van 5% worden ingevuld, omdat je 95% van de schuldigen wil detecteren. de student had berekend dat je 95% van de fraudeurs NIET kan detecteren, wat dus fout is.
de juiste link: http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/12/t12264867437r9kz9uvyom8ojh.htm
om de pakkans dus te vergroten tot 95% moeten we 32466 stukken vlees onderzoeken (=n) en de proef nauwkeuriger maken. Doordat we meer samples nemen gaan de observaties steeds minder afwijken van het gemiddelde, waardoor de variantie zal verkleinen. Het type-I error en type-II error zullen hierdoor verkleinen ALS de kritische waarde hetzelfde blijft. Gaat deze kritische waarde ook verkleinen? Dan zal type-I error en type-II error ook weer mee vergroten. Dit zal verder onderzocht moeten worden. Praktisch probleem bij sample vergroting:
-om dit te verwezenlijken is dat we over zoveel stukken moeten beschikken. ( te weten dat er bij de opgave staat dat er random 27 stukken vlees werden onderzocht)
-te omslachtig
-te duur
-niet realistisch
2008-11-24 18:08:05 [Ellen Van den Broeck] [reply] 
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/24/t1227549950tchdz3hvrt31p6x.htm
De student had de niet de juiste methode gebruikt. Hij moest de 'testing mean wirh known variance - sample size' gebruiken.
Dan vinden we dat de steekproef 32466 moet zijn. Want men gaat de steekproef vergroten om de variantie te verkleinen.
Maar dit is niet realistisch.

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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 time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24090&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]3 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=24090&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24090&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Testing Mean with known Variance
population variance0.012
null hypothesis about mean0.15
alternative hypothesis about mean0.152
type I error0.05
type II error0.95
sample size3.60162696090228e-27

\begin{tabular}{lllllllll}
\hline
Testing Mean with known Variance \tabularnewline
population variance & 0.012 \tabularnewline
null hypothesis about mean & 0.15 \tabularnewline
alternative hypothesis about mean & 0.152 \tabularnewline
type I error & 0.05 \tabularnewline
type II error & 0.95 \tabularnewline
sample size & 3.60162696090228e-27 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24090&T=1

[TABLE]
[ROW][C]Testing Mean with known Variance[/C][/ROW]
[ROW][C]population variance[/C][C]0.012[/C][/ROW]
[ROW][C]null hypothesis about mean[/C][C]0.15[/C][/ROW]
[ROW][C]alternative hypothesis about mean[/C][C]0.152[/C][/ROW]
[ROW][C]type I error[/C][C]0.05[/C][/ROW]
[ROW][C]type II error[/C][C]0.95[/C][/ROW]
[ROW][C]sample size[/C][C]3.60162696090228e-27[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24090&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24090&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 variance0.012
null hypothesis about mean0.15
alternative hypothesis about mean0.152
type I error0.05
type II error0.95
sample size3.60162696090228e-27


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.012 ; par2 = 0.15 ; par3 = 0.152 ; par4 = 0.05 ; par5 = 0.95 ;
Parameters (R input):
par1 = 0.012 ; par2 = 0.15 ; par3 = 0.152 ; par4 = 0.05 ; 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)
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')