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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesismean3.wasp
Title produced by softwareTesting Mean with known Variance - Type II Error
Date of computationThu, 13 Nov 2008 02:18:46 -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/13/t1226567993avhbgdohailewp4.htm/, Retrieved Sun, 19 May 2024 11:10:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24508, Retrieved Sun, 19 May 2024 11:10:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183

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] [the pork quality ...] [2008-11-13 09:18:46] [0cebda6bbc99948f606f5db2560512ab] [Current]
-   P     [Testing Mean with known Variance - Type II Error] [correctie Q3 pork...] [2008-11-24 20:49:24] [b1bd16d1f47bfe13feacf1c27a0abba5]
Feedback Forum
2008-11-24 09:27:23 [Anouk Greeve] [reply] 
Berekeningen kloppen niet helemaal. verklaring is onduidelijk.
De type II error geeft aan dat er 94% kans is dat de fraude van de leverancier niet kan worden gedetecteerd, met als gevolg dat er slechts een pakkans van 6% is. De verleiding voor de leverancier om te frauderen is dus zeer groot.
2008-11-24 21:31:03 [Jasmine Hendrikx] [reply] 
Evaluatie Q3:
De juiste methode is gebruikt. Het gaat hier om het type 2 error. Vandaar dat we ook gebruik maken van de module Testing mean with known variance – type 2 error. De type 2 fout kun je alleen berekenen als je de alternatieve hypothese ook opstelt. Deze is in dit geval dan 15.2%. De berekening is hier echter ook niet goed uitgevoerd. Bij population variance moet er 0.012 ingevuld worden en bij sample mean 0.1546 en bij nulhypothese 0.15. Bij de alternatieve hypothese moet er 0.152 ingevuld worden. Hieronder de URL met de juiste berekeningen:
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/24/t122755980486zk4p2njh42ctk.htm
Aangezien de berekening niet klopt, is ook de bespreking verkeerd. De waarschijnlijkheid dat we de fraude niet ontdekken is 93.94%. Er is dus een grote kans dat de ‘schuldige’ ontsnapt en de fraude niet wordt ontdekt.

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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 time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24508&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]2 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=24508&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24508&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Testing Mean with known Variance
sample size27
population variance1.2
sample mean15.46
null hypothesis about mean15
type I error0.05
alternative hypothesis about mean15.2
Type II Error0.756838916536164

\begin{tabular}{lllllllll}
\hline
Testing Mean with known Variance \tabularnewline
sample size & 27 \tabularnewline
population variance & 1.2 \tabularnewline
sample mean & 15.46 \tabularnewline
null hypothesis about mean & 15 \tabularnewline
type I error & 0.05 \tabularnewline
alternative hypothesis about mean & 15.2 \tabularnewline
Type II Error & 0.756838916536164 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24508&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]1.2[/C][/ROW]
[ROW][C]sample mean[/C][C]15.46[/C][/ROW]
[ROW][C]null hypothesis about mean[/C][C]15[/C][/ROW]
[ROW][C]type I error[/C][C]0.05[/C][/ROW]
[ROW][C]alternative hypothesis about mean[/C][C]15.2[/C][/ROW]
[ROW][C]Type II Error[/C][C]0.756838916536164[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24508&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24508&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 variance1.2
sample mean15.46
null hypothesis about mean15
type I error0.05
alternative hypothesis about mean15.2
Type II Error0.756838916536164


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 27 ; par2 = 1.2 ; par3 = 15.46 ; par4 = 15 ; par5 = 0.05 ; par6 = 15.2 ;
Parameters (R input):
par1 = 27 ; par2 = 1.2 ; par3 = 15.46 ; par4 = 15 ; par5 = 0.05 ; par6 = 15.2 ;
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')