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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesisvariance1.wasp
Title produced by softwareTesting Variance - Critical Value (Region)
Date of computationWed, 12 Nov 2008 07:05:45 -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/t1226498892wm7fqbe7owjfg2a.htm/, Retrieved Sun, 19 May 2024 08:56:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24200, Retrieved Sun, 19 May 2024 08:56:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Testing Mean with known Variance - Sample Size] [Q4] [2008-11-11 11:59:17] [4300be8b33fd3dcdacd2aa9800ceba23]
-       [Testing Mean with known Variance - Sample Size] [Pork Quality Test Q4] [2008-11-11 18:45:08] [db72903d7941c8279d5ce0e4e873d517]
F RMP       [Testing Variance - Critical Value (Region)] [] [2008-11-12 14:05:45] [890f958132adb51f538eb267509d2e70] [Current]
Feedback Forum
2008-11-19 15:43:36 [Sam De Cuyper] [reply] 
Het klopt dat er geen klacht ingediend moet worden. Er wordt wel een verkeerde berekening gemaakt. Men test de variantie terwijl we het gemiddelde zouden moeten testen met gekende variantie. Je zou nog kunnen zeggen dat men een 2 zijdige test kan gebruiken omdat de waarde kan afwijken in 2 richringen (te weinig of te veel vet). Het berekende gemiddelde ligt perfect tussen sie grenzen. (1-zijdige test is ook mogelijk maar dan anders argumenteren)
2008-11-20 15:12:25 [074508d5a5a3592082de3e836d27af7d] [reply] 
Er moet inderdaad geen klacht worden ingediend maar dat kan je niet aflezen van de berekeningen die jij gemaakt hebt. Je moest namelijk de Testing Mean with known Variance gebruiken. Je moest dan ook vermelden dat we hier gebruik van een 2-sided test maken, want het vlees mag niet teveel of te weinig vet bevatten, dus de critical value moet tussen de 2 grenzen liggen. En moet men dus geen klacht indienen.
2008-11-24 09:42:46 [Anouk Greeve] [reply] 
Verkeerde berekening. We moeten de module 'Testing Mean with known Variance' gebruiken ipv 'Testing Variance - Critical value (region)'.
De critical value (0,18468) is groter dan de sample mean (0,1546= het steekproefgemiddelde). Hieruit kunnen we afleiden dat er sprake is van een toevallige afwijking tov het contractueel bepaalde vetgehalte (=15%).
We verwerpen de nulhypothese niet. We gebruiken de one-sided test omdat de leverancier enkel daar een economisch voordeel kan halen. We dienen inderdaad geen klacht in, omdat de contractueel afgesproken waardes niet overschreden worden.

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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 time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24200&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]0 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=24200&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24200&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Testing Variance - Critical value (region)
Sample size27
Sample variance0.012
Null hypothesis (H0)0.15
Type I error (alpha)0.05
Critical value0.0887259033649715
ConclusionReject the null hypothesis

\begin{tabular}{lllllllll}
\hline
Testing Variance - Critical value (region) \tabularnewline
Sample size & 27 \tabularnewline
Sample variance & 0.012 \tabularnewline
Null hypothesis (H0) & 0.15 \tabularnewline
Type I error (alpha) & 0.05 \tabularnewline
Critical value & 0.0887259033649715 \tabularnewline
Conclusion & Reject the null hypothesis \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24200&T=1

[TABLE]
[ROW][C]Testing Variance - Critical value (region)[/C][/ROW]
[ROW][C]Sample size[/C][C]27[/C][/ROW]
[ROW][C]Sample variance[/C][C]0.012[/C][/ROW]
[ROW][C]Null hypothesis (H0)[/C][C]0.15[/C][/ROW]
[ROW][C]Type I error (alpha)[/C][C]0.05[/C][/ROW]
[ROW][C]Critical value[/C][C]0.0887259033649715[/C][/ROW]
[ROW][C]Conclusion[/C][C]Reject the null hypothesis[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24200&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24200&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 Variance - Critical value (region)
Sample size27
Sample variance0.012
Null hypothesis (H0)0.15
Type I error (alpha)0.05
Critical value0.0887259033649715
ConclusionReject the null hypothesis


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 27 ; par2 = 0.012 ; par3 = 0.15 ; par4 = 0.05 ;
Parameters (R input):
par1 = 27 ; par2 = 0.012 ; par3 = 0.15 ; par4 = 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)
df <- par1 - 1
if (par2 > par3)
{
myc <- par3 / df * qchisq(1-par4,df)
} else {
myc <- par3 / df * qchisq(par4,df)
}
myc
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_variance.htm','Testing Variance - Critical value (region)','learn more about Statistical Hypothesis Testing about the Variance'),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,'Sample variance',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Null hypothesis (H0)',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error (alpha)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Critical value',header=TRUE)
a<-table.element(a,myc)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Conclusion',header=TRUE)
if (par2 > par3)
{
if (par2 < myc) a<-table.element(a,'There is no reason to reject the null hypothesis') else a<-table.element(a,'Reject the null hypothesis')
} else {
if (par2 > myc) a<-table.element(a,'There is no reason to reject the null hypothesis') else a<-table.element(a,'Reject the null hypothesis')
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')