Ttest2u: Difference between revisions

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===Purpose===
===Purpose===


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===Synopsis===
===Synopsis===


:result = ttest2u(x,y,''test,dfapp'')
:result = ttest2u(x,y);
:result = ttest2u(x,y,''test,dfapp'');


===Description===
===Description===
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Calculates a two sample t-test for samples (x) and (y) assuming unequal variance.
Calculates a two sample t-test for samples (x) and (y) assuming unequal variance.


====INPUTS====
====Inputs====
 
* '''x''' = matrix (column vector) in which the sample data is stored.
 
* '''y''' = matrix (column vector) in which the sample data is stored.
 
* '''ttest''' = [-1,{0},1] indicates what ttest is for:
 
*  '''-1''' - lower tail  H0: mean(x) <= mean(y)
 
*    '''0''' - wo-tail    H0: mean(x) \~= mean(y) {default}
 
*    '''1''' - upper tail  H0: mean(x) >= mean(y)
 
* '''dfapp''' = [{-1}, 1] indicates which degree of freedom calculation to use.
 
*  '''-1''' - indicates Welch's approximate degrees of freedom {default}
 
*  '''1'''  - indicates Satterthwaite's approximate degrees of freedom
 
====OUTPUTS====
 
The output (result) a structure with the following fields:
 
* '''t''' = test statistic.
 
* '''p''' = probability value
 
* '''mean1''' = mean of x
 
* '''mean2''' = mean of y
 
* '''var1''' = variance of x
 
* '''var2''' = variance of y
 
* '''n1''' =  length of x
 
* '''n2''' =  length of y
 
* '''pse''' = pooled standard error
 
* '''df''' = degress of freedom


* '''app''' = 'Satterthwaite' or 'Welch'
* '''x''' = matrix (or column vector) of data for the first sample.
* '''y''' = matrix (or column vector) of data for the second sample.


* '''hyp''' =  hypothesis being tested
====Optional Inputs====
* '''ttest''' = [-1, {0} ,1] indicates what type of t-test to perform:
::  '''-1''': lower tail  H0: mean(x) <= mean(y),
::    ''' 0''': two-tail    H0: mean(x) ~mean(y) {default},
::    ''' 1''': upper tail  H0: mean(x) >= mean(y).


===Examples===
* '''dfapp''' = [ {-1} , 1] governs the algorithm for calculating degrees of freedom:
::  '''-1''': Welch's approximate degrees of freedom {default},
::  ''' 1''': Satterthwaite's approximate degrees of freedom.


result = ttest2u(x,y);
====Outputs====


result = ttest2u(x,y,test);
* '''result''' = a structure with the following fields:
 
:* '''t''': test statistic,
result = ttest2e(x,y,test,dfapp);
:* '''p''': probability value,
:* '''mean1''': mean of x,
:* '''mean2''': mean of y,
:* '''var1''': variance of x,
:* '''var2''': variance of y,
:* '''n1''':  length of x,
:* '''n2''':  length of y,
:* '''pse''': pooled standard error,
:* '''df''': degress of freedom,
:* '''app''': 'Satterthwaite' or 'Welch',
:* '''hyp''':  hypothesis being tested.


===See Also===
===See Also===


[[ttest1]], [[ttest2u]], [[ttest2p]]
[[ttest1]], [[ttest2e]], [[ttest2p]]
 
*''''''''' '''

Latest revision as of 09:42, 24 October 2013

Purpose

Two sample t-test (assuming unequal variance).

Synopsis

result = ttest2u(x,y);
result = ttest2u(x,y,test,dfapp);

Description

Calculates a two sample t-test for samples (x) and (y) assuming unequal variance.

Inputs

  • x = matrix (or column vector) of data for the first sample.
  • y = matrix (or column vector) of data for the second sample.

Optional Inputs

  • ttest = [-1, {0} ,1] indicates what type of t-test to perform:
-1: lower tail H0: mean(x) <= mean(y),
0: two-tail H0: mean(x) ~= mean(y) {default},
1: upper tail H0: mean(x) >= mean(y).
  • dfapp = [ {-1} , 1] governs the algorithm for calculating degrees of freedom:
-1: Welch's approximate degrees of freedom {default},
1: Satterthwaite's approximate degrees of freedom.

Outputs

  • result = a structure with the following fields:
  • t: test statistic,
  • p: probability value,
  • mean1: mean of x,
  • mean2: mean of y,
  • var1: variance of x,
  • var2: variance of y,
  • n1: length of x,
  • n2: length of y,
  • pse: pooled standard error,
  • df: degress of freedom,
  • app: 'Satterthwaite' or 'Welch',
  • hyp: hypothesis being tested.

See Also

ttest1, ttest2e, ttest2p