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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesismean1.wasp
Title produced by softwareTesting Mean with known Variance - Critical Value
Date of computationWed, 12 Nov 2008 06:01:09 -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/t1226494981pincqqvi8j9hyp7.htm/, Retrieved Sun, 19 May 2024 10:20:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24158, Retrieved Sun, 19 May 2024 10:20:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

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 - Critical Value] [] [2008-11-12 13:01:09] [0655940460a4fd80d3d4d54548b75d49] [Current]
Feedback Forum
2008-11-16 18:33:37 [Lana Van Wesemael] [reply] 
Hier heeft de student de variance, sample mean en null hypothesis about mean verkeerd ingetypt. Via deze link kan je zien hoe de tabel er wel uit zou moeten zien.
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226398904orn15elgvw4v4jx.htm
Doordat in de tabel van de student een paar foutjes zitten is de conclusie jammer genoeg verkeerd. Het is in dit geval niet de bedoeling dat men een klacht indient omdat de grenswaarden niet overschreden worden.
Men kan in deze opdracht kiezen tussen de one-tailed of de two-tailed test. Indien men de one-tailed test verkiest moet men dit wel voldoende argumenteren. De student heeft in dit geval voor de one-tailed test gekozen met als verantwoording dat enkel het teveel aan vet belangrijk is, niet de minimale hoeveelheid. Dit klopt niet geheel, als er te weinig vet zit in het varkensvlees dan gaat de smaak erop achteruit. De verantwoording had wel correct geweest indien de student had vermeld dat de leverancier er een economisch voordeel bij heeft om te veel vet in het vlees te verwerken. Want de prijs van vet is kleiner dan de prijs van vlees.
2008-11-20 20:02:14 [] [reply] 
De berekening is verkeerd uitgevoerd door de procenten verkeerd te gebruiken. Via deze link krijg je de juiste berekening : http://www.freestatistics.org/blog/date/2008/Nov/11/t12264116378chz03jamwk4orm.htm. En klinkt de conclusie als volgt : je moet kijken naar het confidence interval 2-tailed want er kan ofwel te veel vet zijn of te weinig. Het steekproefgemiddelde (0.1546) valt in dit interval dus er is geen fraude. Er is een toevallige afwijking. We verwerpen de nul hypthese niet. We mogen geen klacht indienen.
2008-11-20 20:02:53 [Toon Wouters] [reply] 
De berekening is verkeerd uitgevoerd door de procenten verkeerd te gebruiken. Via deze link krijg je de juiste berekening : http://www.freestatistics.org/blog/date/2008/Nov/11/t12264116378chz03jamwk4orm.htm. En klinkt de conclusie als volgt : je moet kijken naar het confidence interval 2-tailed want er kan ofwel te veel vet zijn of te weinig. Het steekproefgemiddelde (0.1546) valt in dit interval dus er is geen fraude. Er is een toevallige afwijking. We verwerpen de nul hypthese niet. We mogen geen klacht indienen.
2008-11-24 18:35:47 [Yannick Van Schil] [reply] 
Verkeerde berekening, ik had juiste berekening deze kan je terug vinden via search archive. Conclusie zou hier moeten zijn dat de critical value groter is dan de sample mean en hieruit kan men afleiden dat er sprake is van een toevaligge afwijking ten opzichten van het contractueel bepaalde vetgehalte, 0 hypothese wordt niet verworpen

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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=24158&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=24158&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24158&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 mean15.46
null hypothesis about mean15
type I error0.05
critical value (one-tailed)15.3467655919170
confidence interval (two-tailed)(sample mean)[ 15.0468033117970 , 15.8731966882030 ]
conclusion for one-tailed test
Reject the null hypothesis.
conclusion for two-tailed test
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 & 15.46 \tabularnewline
null hypothesis about mean & 15 \tabularnewline
type I error & 0.05 \tabularnewline
critical value (one-tailed) & 15.3467655919170 \tabularnewline
confidence interval (two-tailed)(sample mean) & [ 15.0468033117970 ,  15.8731966882030 ] \tabularnewline
conclusion for one-tailed test \tabularnewline
Reject the null hypothesis. \tabularnewline
conclusion for two-tailed test \tabularnewline
Reject the null hypothesis \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24158&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]critical value (one-tailed)[/C][C]15.3467655919170[/C][/ROW]
[ROW][C]confidence interval (two-tailed)(sample mean)[/C][C][ 15.0468033117970 ,  15.8731966882030 ][/C][/ROW]
[ROW][C]conclusion for one-tailed test[/C][/ROW]
[ROW][C]Reject the null hypothesis.[/C][/ROW]
[ROW][C]conclusion for two-tailed test[/C][/ROW]
[ROW][C]Reject the null hypothesis[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24158&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24158&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
critical value (one-tailed)15.3467655919170
confidence interval (two-tailed)(sample mean)[ 15.0468033117970 , 15.8731966882030 ]
conclusion for one-tailed test
Reject the null hypothesis.
conclusion for two-tailed test
Reject the null hypothesis


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 27 ; par2 = 1.2 ; par3 = 15.46 ; par4 = 15 ; par5 = 0.05 ;
Parameters (R input):
par1 = 27 ; par2 = 1.2 ; par3 = 15.46 ; 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))
if (par3 == par4)
{
conclusion <- 'Error: the null hypothesis and sample mean must not be equal.'
conclusion2 <- conclusion
} else {
cleft <- par3 - csn2 * sqrt(par2) / sqrt(par1)
cright <- par3 + csn2 * sqrt(par2) / sqrt(par1)
c2 <- paste('[',cleft)
c2 <- paste(c2,', ')
c2 <- paste(c2,cright)
c2 <- paste(c2,']')
if ((par4 < cleft) | (par4 > cright))
{
conclusion2 <- 'Reject the null hypothesis'
} else {
conclusion2 <- 'Do not reject the null hypothesis'
}
}
if (par3 > par4)
{
c <- par4 + csn * sqrt(par2) / sqrt(par1)
if (par3 < c)
{
conclusion <- 'Do not reject the null hypothesis.'
} else {
conclusion <- 'Reject the null hypothesis.'
}
}
if (par3 < par4)
{
c <- par4 - csn * sqrt(par2) / sqrt(par1)
if (par3 > c)
{
conclusion <- 'Do not reject the null hypothesis.'
} else {
conclusion <- 'Reject the null hypothesis.'
}
}
c
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,hyperlink('ht_mean_knownvar.htm#overview','critical value (one-tailed)','about the critical value'),header=TRUE)
a<-table.element(a,c)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'confidence interval (two-tailed)
(sample mean)',header=TRUE)
a<-table.element(a,c2)
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')