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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 computationThu, 13 Nov 2008 07:20:41 -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/t1226586059y30xfxhfekizoiz.htm/, Retrieved Sun, 19 May 2024 03:41:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24621, Retrieved Sun, 19 May 2024 03:41:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

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] [] [2008-11-13 14:20:41] [ffe1355fa7fe5626118ee2c4cacbba88] [Current]
Feedback Forum
2008-11-14 16:11:10 [Nathalie Van Gestel] [reply] 
Hier wordt geen correct antwoord gegeven.

We gebruiken voor deze vaag op te lossen dezelfde werkwijze als in vraag 5. Ook hier is de rechter staart is nauwkeuriger, omdat de volledige 5% (foutmarge) toegewezen wordt aan de rechterkant.
(bij de two-sided wordt de 5% verdeeld over de linkse en rechtse tail, wat maakt dat de resultaten voor de two-sided extremer zijn.)
Ook als de nulhypothese hier wordt verhoogd dan nog ligt de sample mean van 0.1546 lager dan de 0.186676559191704 dus binnen het betrouwbaarheidinterval van 95%.
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/14/t1226667421wbb2si8r9pzvrlj.htm
2008-11-15 10:44:19 [a7d9990a66ef13b6ce566dbfd4dc5418] [reply] 
Dezelfde oplossing als in vraag 5.
Bovendien ligt de sample mean nog steeds lager dan de 0.186676559191704 als we de nulhypothese verhogen, en dus ook nog steeds binnen het betrouwbaarheidsinteval van 95%.
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/14/t1226667421wbb2si8r9pzvrlj.htm
2008-11-24 14:57:27 [Sofie Sergoynne] [reply] 
Zelfde foute output werd gegeven zoals in Q5. opnieuw geen interpretatie van de gevonden output. We moeten dezelfde mthode gebruiken als in vraag 5. We merken dat ook hier de rechterstaart nauwkeuriger is omdat de volledige 5% (foutmarge) toegewezen wordt aan de rechterkant. We gebruien hierdoor de two-sided test. bovendien ligt de sample mean nog steeds lager als de de 0.186676559191704 als we de nulhypothese verhogen, en dus ook nog steeds binnen het betrouwbaarheidsinteval van 95%.

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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'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24621&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24621&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24621&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'George Udny Yule' @ 72.249.76.132






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=24621&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=24621&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24621&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 = 15,45 ; 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')