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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesismean2.wasp
Title produced by softwareTesting Mean with known Variance - p-value
Date of computationWed, 12 Nov 2008 06:39:40 -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/t1226497273n5i8tkrziusur4k.htm/, Retrieved Tue, 28 May 2024 07:01:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24178, Retrieved Tue, 28 May 2024 07:01:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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 - p-value] [] [2008-11-12 13:39:40] [0655940460a4fd80d3d4d54548b75d49] [Current]
Feedback Forum
2008-11-16 18:35:16 [Lana Van Wesemael] [reply] 
Hier heeft de student de verkeerde type test gebruikt, bij deze vraag was het de bedoeling om de testing mean with known variance – type II error file te gebruiken. Ik vermoed dat de student testing mean with known variance- p-value file gebruikt heeft. Hier vind je een link naar de juiste tabel:
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226399908pl2ixe8vkqhpfjm.htm
De vraagstelling wijst er duidelijk op dat men op zoek moet gaan naar een type II error, namelijk de kans dat we een schuldige hebben laten lopen of te vet varkensvlees goedgekeurd hebben. Vandaar dat men de test testing mean with known variance – type II moet gebruiken.
Uit de juiste tabel blijkt dan dat de type II error gelijk is aan 0.93942747750307. De kans dat men de fraude nooit ontdekt heeft bedraagt dus 93%.
2008-11-20 20:35:27 [Toon Wouters] [reply] 
Verkeerde berekening gebruikt, dus ook verkeerde conclusie en ook verkeerd de percentages gebruikt. Voor de juiste berekening zie http://www.freestatistics.org/blog/date/2008/Nov/11/t1226413322chhp1z348vawhhy.htm.Daar kunnen we zien dat de type 2 error ongeveer 94% is, dit wil zeggen dat er maar 6% kans is dat de fraude toch ontdekt wordt. Dit maakt het heel aantrekkelijk voor de fabrikant, want hij loopt nauwelijks risico om gepakt te worden.
2008-11-24 18:41:50 [Yannick Van Schil] [reply] 
alweer foute gegevens gebruikt. De type 2 fout geeft aan dat er 94% kans is dat de fraude van de leverancier niet kan worden gedetecteerd. Dus pakkans is 6% wat leverancier in verleiding brengt te frauderen

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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=24178&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=24178&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24178&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
sample size27
population variance1.2
sample mean15.2
null hypothesis about mean15
type I error0.05
Z-value0.94868329805051
p-value (one-tailed)0.171390855573957
p-value (two-tailed)0.342781711147913
conclusion for one-tailed test
Do not reject the null hypothesis.
conclusion for two-tailed test
Do not reject the null hypothesis

\begin{tabular}{lllllllll}
\hline
Testing Mean with known Variance \tabularnewline
sample size & 27 \tabularnewline
population variance & 1.2 \tabularnewline
sample mean & 15.2 \tabularnewline
null hypothesis about mean & 15 \tabularnewline
type I error & 0.05 \tabularnewline
Z-value & 0.94868329805051 \tabularnewline
p-value (one-tailed) & 0.171390855573957 \tabularnewline
p-value (two-tailed) & 0.342781711147913 \tabularnewline
conclusion for one-tailed test \tabularnewline
Do not reject the null hypothesis. \tabularnewline
conclusion for two-tailed test \tabularnewline
Do not reject the null hypothesis \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24178&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]15.2[/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]Z-value[/C][C]0.94868329805051[/C][/ROW]
[ROW][C]p-value (one-tailed)[/C][C]0.171390855573957[/C][/ROW]
[ROW][C]p-value (two-tailed)[/C][C]0.342781711147913[/C][/ROW]
[ROW][C]conclusion for one-tailed test[/C][/ROW]
[ROW][C]Do not reject the null hypothesis.[/C][/ROW]
[ROW][C]conclusion for two-tailed test[/C][/ROW]
[ROW][C]Do not reject the null hypothesis[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24178&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24178&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 mean15.2
null hypothesis about mean15
type I error0.05
Z-value0.94868329805051
p-value (one-tailed)0.171390855573957
p-value (two-tailed)0.342781711147913
conclusion for one-tailed test
Do not reject the null hypothesis.
conclusion for two-tailed test
Do not reject the null hypothesis


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 27 ; par2 = 1.2 ; par3 = 15.2 ; par4 = 15 ; par5 = 0.05 ;
Parameters (R input):
par1 = 27 ; par2 = 1.2 ; par3 = 15.2 ; par4 = 15 ; par5 = 0.05 ;
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))
csn2 <- abs(qnorm(par5/2))
z <- (par3 - par4) / (sqrt(par2/par1))
p <- 1-pnorm(z)
if (par3 == par4)
{
conclusion <- 'Error: the null hypothesis and sample mean must not be equal.'
conclusion2 <- conclusion
} else {
if (p < par5/2)
{
conclusion2 <- 'Reject the null hypothesis'
} else {
conclusion2 <- 'Do not reject the null hypothesis'
}
}
if (p < par5)
{
conclusion <- 'Reject the null hypothesis.'
} else {
conclusion <- 'Do not reject the null hypothesis.'
}
p
conclusion
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,'Z-value',header=TRUE)
a<-table.element(a,z)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (one-tailed)',header=TRUE)
a<-table.element(a,p)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (two-tailed)',header=TRUE)
a<-table.element(a,p*2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'conclusion for one-tailed test',2,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,conclusion,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'conclusion for two-tailed test',2,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,conclusion2,2)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')