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Author*The author of this computation has been verified*
R Software Modulerwasp_hypothesismeanu.wasp
Title produced by softwareTesting Mean with unknown Variance - Critical Value
Date of computationFri, 22 Oct 2010 16:15:41 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/22/t12877640606l3mcwd4q9dkmdk.htm/, Retrieved Mon, 24 Jun 2024 12:47:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=87525, Retrieved Mon, 24 Jun 2024 12:47:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Factor Analysis] [Sleep in Mammals ...] [2010-03-21 11:39:53] [b98453cac15ba1066b407e146608df68]
- RMPD  [Testing Mean with unknown Variance - Critical Value] [Hypothesis Test a...] [2010-10-19 11:45:26] [b98453cac15ba1066b407e146608df68]
F   PD      [Testing Mean with unknown Variance - Critical Value] [] [2010-10-22 16:15:41] [1d094c42a82a95b45a19e32ad4bfff5f] [Current]
Feedback Forum
2010-11-02 15:37:18 [4d4f7d38b8a37a3fb90a9939352fc7e6] [reply
De standaarddeviatie en steekproefgrootte is berekend in de spreadsheet (cellen Z2: AA3).
De berekening voor mannen is triviaal, omdat H0 = steekproefvariantie. We concluderen dat er geen behoefte is
om de hypothese te berekenen voor mannen (de steekproef schatting is niet verschillend van H0).
De berekening voor vrouwen blijkt dat de kritische waarde 13.775 is. We concluderen dat de vrouwelijke I1
variantie aanzienlijk groter is dan 13 (bij de 35% type I error level) Let op: dit betekent niet noodzakelijkerwijs
dat de variantie groter is de I1 variantie van mannen. Waarom?
http://www.freestatistics.org/blog/date/2010/Oct/25/t1288043532phj41g2mwbpfvum.htm/
De bovenstaande oplossing gaat ervan uit dat we gebruik maken van een eenzijdige test .
Bij een tweezijdige test moeten we de 65% betrouwbaarheidsintervallen berekenen zoals aangegeven
in de volgende berekeningen:
http://www.freestatistics.org/blog/date/2010/Oct/25/t1288043645wt7valwo96c7ppn.htm/
http://www.freestatistics.org/blog/date/2010/Oct/25/t1288043889djfatwi1jb1runt.htm/
De conclusie is dat de vrouwelijke I1 variantie niet significant verschillend is van 13, maar het is
aanzienlijk groter zijn dan 13.

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Dataseries X:
26
20
19

20
25

22
26
22


19
24
26

13


22

21
7

17
25
25
19

23

22
21



18


22
18
23
20


15


21

18
19
22
16

18
20
24


24
18
21

17



22
16
21


24
24
16
16




18

20


24
17
19
20
15

22
23
16
19

19


21

24
22

18

24
24
22
23
22
20
18
25

16
20

15
19
19
16
17
28

25
20


16




23
21


23
18
20
9

25
20




21
22
27



18
16
22
20

20




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=87525&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=87525&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87525&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Hypothesis Test about the Mean - Confidence Interval
Sample size98
Sample standard deviation3.60983764663337
Confidence0.65
Null hypothesis13
Sample Mean20.2857142857143
2-sided Confidence Interval[ 19.9432641491045 , 20.6281644223241 ]
Left-sided Confidence Interval[ 20.1447909456657 , +inf ]
Right-sided Confidence Interval[ -inf, 20.4266376257629 ]

\begin{tabular}{lllllllll}
\hline
Hypothesis Test about the Mean - Confidence Interval \tabularnewline
Sample size & 98 \tabularnewline
Sample standard deviation & 3.60983764663337 \tabularnewline
Confidence & 0.65 \tabularnewline
Null hypothesis & 13 \tabularnewline
Sample Mean & 20.2857142857143 \tabularnewline
2-sided Confidence Interval & [ 19.9432641491045 , 20.6281644223241 ] \tabularnewline
Left-sided Confidence Interval & [ 20.1447909456657 , +inf ] \tabularnewline
Right-sided Confidence Interval & [ -inf,  20.4266376257629 ] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87525&T=1

[TABLE]
[ROW][C]Hypothesis Test about the Mean - Confidence Interval[/C][/ROW]
[ROW][C]Sample size[/C][C]98[/C][/ROW]
[ROW][C]Sample standard deviation[/C][C]3.60983764663337[/C][/ROW]
[ROW][C]Confidence[/C][C]0.65[/C][/ROW]
[ROW][C]Null hypothesis[/C][C]13[/C][/ROW]
[ROW][C]Sample Mean[/C][C]20.2857142857143[/C][/ROW]
[ROW][C]2-sided Confidence Interval[/C][C][ 19.9432641491045 , 20.6281644223241 ][/C][/ROW]
[ROW][C]Left-sided Confidence Interval[/C][C][ 20.1447909456657 , +inf ][/C][/ROW]
[ROW][C]Right-sided Confidence Interval[/C][C][ -inf,  20.4266376257629 ][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87525&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87525&T=1

As an alternative you can also use a QR Code:  

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

Hypothesis Test about the Mean - Confidence Interval
Sample size98
Sample standard deviation3.60983764663337
Confidence0.65
Null hypothesis13
Sample Mean20.2857142857143
2-sided Confidence Interval[ 19.9432641491045 , 20.6281644223241 ]
Left-sided Confidence Interval[ 20.1447909456657 , +inf ]
Right-sided Confidence Interval[ -inf, 20.4266376257629 ]



Parameters (Session):
par1 = 0.65 ; par2 = 13 ;
Parameters (R input):
par1 = 0.65 ; par2 = 13 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
len <- length(x)
df <- len - 1
sd <- sd(x)
mx <- mean(x)
load(file='createtable')
delta2 <- abs(qt((1-par1)/2,df)) * sd / sqrt(len)
delta1 <- abs(qt((1-par1),df)) * sd / sqrt(len)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Hypothesis Test about the Mean - Confidence Interval',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Sample size',header=TRUE)
a<-table.element(a,len)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Sample standard deviation',header=TRUE)
a<-table.element(a,sd)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Confidence',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Null hypothesis',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,mx)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'2-sided Confidence Interval',header=TRUE)
dum <- paste('[',mx-delta2)
dum <- paste(dum,',')
dum <- paste(dum,mx+delta2)
dum <- paste(dum,']')
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Left-sided Confidence Interval',header=TRUE)
dum <- paste('[',mx-delta1)
dum <- paste(dum,', +inf ]')
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Right-sided Confidence Interval',header=TRUE)
dum <- paste('[ -inf, ',mx+delta1)
dum <- paste(dum,']')
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')