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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hypothesismean3.wasp
Title produced by softwareTesting Mean with known Variance - Type II Error
Date of computationMon, 10 Nov 2008 03:28:44 -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/10/t1226312944su8e8r5qw7kw1j3.htm/, Retrieved Sun, 19 May 2024 08:50:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22910, Retrieved Sun, 19 May 2024 08:50:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

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 - Type II Error] [] [2008-11-10 10:28:44] [19ef54504342c1b076371d395a2ab19f] [Current]
F         [Testing Mean with known Variance - Type II Error] [] [2008-11-11 18:04:25] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-11-19 17:16:50 [Bob Leysen] [reply] 
De link is correct.

We moeten ervoor zorgen dat de waarschijnlijkheidsverdeling er anders gaat uitzien, de variantie moet dus kleiner worden door de spreiding van de steekproef te verkleinen -> meer metingen nemen want zo verbeter je de kansen.

=> type 1 fout en type 2 fout kleiner maken door steekproef te vergroten.
2008-11-21 14:22:39 [Hidde Van Kerckhoven] [reply] 
Inderdaad type 1 en type 2 hadden hier moeten verkleinen, dit konden we doen door de meettechniek te verbeteren of door de steekproef groter te maken
2008-11-22 17:32:35 [Olivier Uyttendaele] [reply] 
Je geeft hier een goed antwoord.

Je geeft een goed antwoord. De getuigenis van deze man geeft ons een soort van voorkennis. Je gaat de kans berekenen dat we de fraude niet ontdekken (type II Error).
Je kan deze Type II enkel berekenen als je de alternative hypothese kent. De kans om betrapt te worden is 6% wat het de leverancier zeer verleidelijk maakt om te frauderen.

Als je de Type II fout wilt verkleinen heb je 2mogelijkheden. Nl. 1) Je kan de meettechniek verbeteren. 2) je kan de steekproef vergroten.
2008-11-23 14:07:23 [Olivier Uyttendaele] [reply] 
Dit is de feedback die bij Q3 hoort, je diende een nieuw model te gebruiken, je baseert u op het foute model, net zoals bij Q2. Het model het model “testing mean with know variance – sample size” moest hier gebruikt worden. Daar zou je dan het aantal sample sizes dat we hieronder verkregen, te zien krijgen.

Als we de pakkans pakkans uitbreiden tot 95%, dan is er slechts een kans van 5% dat we de fraude niet ontdekken. Deze 5% wordt weergegeven in de type I- en type II fout. Als we een pakkans willen krijgen van 95% moet de steekproefgrootte verruimd worden met 32466.5214491449 steekproeven. Dit is in de praktijk onmogelijk om te realiseren.
2008-11-25 00:34:25 [Olivier Uyttendaele] [reply] 
vorige feedback is voor Q4 uit je document, excuses

Post a new message

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=22910&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=22910&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22910&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






Testing Mean with known Variance
sample size27
population variance0.012
sample mean0.1546
null hypothesis about mean0.15
type I error0.05
alternative hypothesis about mean0.152
Type II Error0.93942747750307

\begin{tabular}{lllllllll}
\hline
Testing Mean with known Variance \tabularnewline
sample size & 27 \tabularnewline
population variance & 0.012 \tabularnewline
sample mean & 0.1546 \tabularnewline
null hypothesis about mean & 0.15 \tabularnewline
type I error & 0.05 \tabularnewline
alternative hypothesis about mean & 0.152 \tabularnewline
Type II Error & 0.93942747750307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22910&T=1

[TABLE]
[ROW][C]Testing Mean with known Variance[/C][/ROW]
[ROW][C]sample size[/C][C]27[/C][/ROW]
[ROW][C]population variance[/C][C]0.012[/C][/ROW]
[ROW][C]sample mean[/C][C]0.1546[/C][/ROW]
[ROW][C]null hypothesis about mean[/C][C]0.15[/C][/ROW]
[ROW][C]type I error[/C][C]0.05[/C][/ROW]
[ROW][C]alternative hypothesis about mean[/C][C]0.152[/C][/ROW]
[ROW][C]Type II Error[/C][C]0.93942747750307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22910&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22910&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
sample size27
population variance0.012
sample mean0.1546
null hypothesis about mean0.15
type I error0.05
alternative hypothesis about mean0.152
Type II Error0.93942747750307


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 27 ; par2 = 0.012 ; par3 = 0.1546 ; par4 = 0.15 ; par5 = 0.05 ; par6 = 0.152 ;
Parameters (R input):
par1 = 27 ; par2 = 0.012 ; par3 = 0.1546 ; par4 = 0.15 ; par5 = 0.05 ; par6 = 0.152 ;
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)
par6<-as.numeric(par6)
c <- 'NA'
csn <- abs(qnorm(par5))
if (par3 == par4)
{
conclusion <- 'Error: the null hypothesis and sample mean must not be equal.'
}
if (par3 > par4)
{
c <- par4 + csn * sqrt(par2) / sqrt(par1)
}
if (par3 < par4)
{
c <- par4 - csn * sqrt(par2) / sqrt(par1)
}
p <- pnorm((c - par6) / (sqrt(par2/par1)))
p
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,'sample size',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'population variance',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'sample mean',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'null hypothesis about mean',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'type I error',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alternative hypothesis about mean',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_mean_knownvar.htm#ex3','Type II Error','example'),header=TRUE)
a<-table.element(a,p)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')