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R Software Modulerwasp_hypothesismean5.wasp
Title produced by softwareTesting Population Mean with known Variance - Confidence Interval
Date of computationThu, 13 Nov 2008 11:31:05 -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/t1226601195ucrjks5hhp5l7kd.htm/, Retrieved Sun, 19 May 2024 10:45:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24755, Retrieved Sun, 19 May 2024 10:45:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Testing Population Mean with known Variance - Confidence Interval] [Stefan Temmerman] [2008-11-13 18:31:05] [7866e091edc3e3e9f6a037e9d19fcaa2] [Current]
Feedback Forum
2008-11-18 15:08:50 [Stefan Temmerman] [reply
Er is hier naar de verkeerde waarden gekeken voor het interval.
Het betrouwbaarheidsinterval ligt hier tussen 0.1107 & 0.1933.
Aan het right one sided confidential interval zien we dat we H0 niet moeten verwerpen. De kritische waarde bedraagt hier 0.187, het bekomen gemiddelde is kleiner.
2008-11-23 09:56:01 [Carole Thielens] [reply
Het antwoord op deze vraag is incorrect, hoewel de berekeningen juist uitgevoerd zijn.
We gebruiken hier een one-sided confidence interval omdat deze nauwkeuriger is. Wanneer we een two-sided test gebruiken, wordt de 5% foutmarge verdeeld over de linkse en rechtse staart. Dit maakt de resultaten extremer.
Aangezien we er vanuit moeten gaan dat het werkelijke vetgehalte 15.2% is, zullen we deze veronderstelling dus moeten beschouwen als de nieuwe nulhypothese.
Het nieuwe betrouwbaarheidsinterval bedraagt nu 0.186 en de sample mean van 0.1546 valt zeer duidelijk binnen dit betrouwbaarheidsinterval. We kunnen dus besluiten dat het gemiddelde van 15.46% consistent is met het vetpercentage van 15.2%.

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Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24755&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24755&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24755&T=0

As an alternative you can also use a 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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Testing Population Mean with known Variance
Population variance0.012
Sample size27
Sample mean0.152
Confidence interval0.95
Type of IntervalLeft tailRight tail
Two-sided confidence interval at 0.950.1106803311796960.193319668820304
Left one-sided confidence interval at 0.950.117323440808296+inf
Right one-sided confidence interval at 0.95-inf0.186676559191704
more information about confidence interval

\begin{tabular}{lllllllll}
\hline
Testing Population Mean with known Variance \tabularnewline
Population variance & 0.012 \tabularnewline
Sample size & 27 \tabularnewline
Sample mean & 0.152 \tabularnewline
Confidence interval & 0.95 \tabularnewline
Type of Interval & Left tail & Right tail \tabularnewline
Two-sided confidence interval at  0.95 & 0.110680331179696 & 0.193319668820304 \tabularnewline
Left one-sided confidence interval at  0.95 & 0.117323440808296 & +inf \tabularnewline
Right one-sided confidence interval at  0.95 & -inf & 0.186676559191704 \tabularnewline
more information about confidence interval \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24755&T=1

[TABLE]
[ROW][C]Testing Population Mean with known Variance[/C][/ROW]
[ROW][C]Population variance[/C][C]0.012[/C][/ROW]
[ROW][C]Sample size[/C][C]27[/C][/ROW]
[ROW][C]Sample mean[/C][C]0.152[/C][/ROW]
[ROW][C]Confidence interval[/C][C]0.95[/C][/ROW]
[ROW][C]Type of Interval[/C][C]Left tail[/C][C]Right tail[/C][/ROW]
[ROW][C]Two-sided confidence interval at  0.95[/C][C]0.110680331179696[/C][C]0.193319668820304[/C][/ROW]
[ROW][C]Left one-sided confidence interval at  0.95[/C][C]0.117323440808296[/C][C]+inf[/C][/ROW]
[ROW][C]Right one-sided confidence interval at  0.95[/C][C]-inf[/C][C]0.186676559191704[/C][/ROW]
[ROW][C]more information about confidence interval[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24755&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24755&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Testing Population Mean with known Variance
Population variance0.012
Sample size27
Sample mean0.152
Confidence interval0.95
Type of IntervalLeft tailRight tail
Two-sided confidence interval at 0.950.1106803311796960.193319668820304
Left one-sided confidence interval at 0.950.117323440808296+inf
Right one-sided confidence interval at 0.95-inf0.186676559191704
more information about confidence interval



Parameters (Session):
par1 = 0.012 ; par2 = 27 ; par3 = 0.152 ; par4 = 0.95 ;
Parameters (R input):
par1 = 0.012 ; par2 = 27 ; par3 = 0.152 ; par4 = 0.95 ;
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)
sigma <- sqrt(par1)
sqrtn <- sqrt(par2)
ua <- par3 - abs(qnorm((1-par4)/2))* sigma / sqrtn
ub <- par3 + abs(qnorm((1-par4)/2))* sigma / sqrtn
ua
ub
ul <- par3 - qnorm(par4) * sigma / sqrtn
ul
ur <- par3 + qnorm(par4) * sigma / sqrtn
ur
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_mean_knownvar.htm','Testing Population Mean with known Variance','learn more about Statistical Hypothesis Testing about the Mean when the Variance is known'),3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Population variance',header=TRUE)
a<-table.element(a,par1,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Sample size',header=TRUE)
a<-table.element(a,par2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Sample mean',header=TRUE)
a<-table.element(a,par3,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Confidence interval',header=TRUE)
a<-table.element(a,par4,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type of Interval',header=TRUE)
a<-table.element(a,'Left tail',header=TRUE)
a<-table.element(a,'Right tail',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('Two-sided confidence interval at ',par4), header=TRUE)
a<-table.element(a,ua)
a<-table.element(a,ub)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('Left one-sided confidence interval at ',par4), header=TRUE)
a<-table.element(a,ul)
a<-table.element(a,'+inf')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('Right one-sided confidence interval at ',par4), header=TRUE)
a<-table.element(a,'-inf')
a<-table.element(a,ur)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, hyperlink('ht_mean_knownvar.htm#ex5', 'more information about confidence interval','example'),3,TRUE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')