Difference between revisions of "User:Regina/MYDrafts3"

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=== Details ===
 
=== Details ===
Semantics: Let X1, X2, …,Xn be the numbers in the sequence X and Y1, Y2, …,Ym be the numbers in the sequence Y. Then and  . Moreover let
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The Student's test is related to the t-distribution. Its density function is
, and
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 +
<math>
 +
f(x,df)=\cfrac {\operatorname{\Gamma} \left ( \frac {df+1}{2} \right )}
 +
{ \sqrt{\pi df} \, \Gamma \left ( \frac {df} {2} \right )} \,
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\left ( 1 + \frac {x^2} {df} \right )^{-\left ( \frac {df+1}{2} \right )}
 +
</math>
 +
 
 +
where <math>\Gamma</math> is the Gamma function and <math>df</math> the parameter ''degree of freedom''.
  
where Γ is the Gamma function.
 
 
==== Paired Samples ====
 
==== Paired Samples ====
If type=1, a paired Student's test is calculated. It uses the differences of the pairs. So in this case the data X and Y should have the same count n.
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If type=1, TTEST calculates the p-value for paired samples. It uses the differences of the pairs. So in this case the data X and Y should have the same count n.
<math>\overline{X} = \frac{1}{n}\ \sum_{i=1}^n\, X_i</math>
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<math>\overline{Y} = \frac{1}{n}\ \sum_{i=1}^n\, Y_i</math>
+
  
TTEST calculates the p-value for a paired-sample comparison of means test. Note that in this case due to the above constraints n=m. With
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<math>\overline{X} = \frac{1}{n}\ \sum_{i=1}^n\, X_i \qquad
 +
\overline{Y} = \frac{1}{n}\ \sum_{i=1}^n\, Y_i</math>
  
and
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<math>s_{X-Y}^2 = \frac 1 {n-1} \sum_{i=1}^n \left ( (X_i -Y_i) - (\overline X - \overline Y ) \right )^2</math>
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TTEST returns.
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<math>t = \frac {\left | \overline X - \overline Y \right |}
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{\sqrt { \frac {s_{X-Y}^2} n} }</math>
 +
 
 +
TTEST returns <math> tails \cdot \int_t^\infty f(x,n-1) \, dx </math>
  
 
==== Unpaired Samples, Equal Variance ====
 
==== Unpaired Samples, Equal Variance ====
  
(2)If type = 2, TTEST calculates the p-value of a comparison of means for independent samples from populations with equal variance. With
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If type = 2, TTEST calculates the p-value of a comparison of means for independent samples from populations with equal variance. Besides
 +
 
 +
<math>{s_X}^2=\tfrac 1 {n-1} \sum_{i=1}^n \left (X_i - \overline X \right )^2 \qquad
 +
{s_Y}^2=\tfrac 1 {m-1} \sum_{i=1}^m \left (Y_i - \overline Y \right )^2
 +
</math>
 +
 
 +
it uses the pooled variance
 +
 
 +
<math>{s_P}^2 = \frac {(n-1) {s_X}^2 + (m-1) {s_Y}^2} {n-1+m-1} </math>
  
 
and
 
and
  
==== Unpaired Samples, Not Necessarily Equal Variances
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<math>t = \frac {\left | \overline X - \overline Y \right |}{\sqrt { {s_P}^2(\frac 1 n + \frac 1 m)}}</math>
 +
 
 +
TTEST returns <math> tails \cdot \int_t^\infty f(x,n+m-2) \, dx </math>
 +
 
 +
 
 +
==== Unpaired Samples, Unequal Variances ====
 
   
 
   
TTEST returns .
+
If type = 3, TTEST calculates the p-value of a comparison of means for independent samples from populations with not necessarily equal variances.
(3)If type = 3, TTEST calculates the p-value of a comparison of means for independent samples from populations with not necessarily equal variances. With
+
  
and
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<math>t = \frac {\left | \overline X - \overline Y \right |}{\sqrt { \cfrac {{s_X}^2} n + \cfrac {{s_Y}^2} m}}
 +
\qquad
 +
\nu = \cfrac {\left ( \cfrac {{s_X}^2} n + \cfrac {{s_Y}^2} m \right )^2}
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{\cfrac {\left (\cfrac {{s_X}^2} n \right )^2}{n-1} + \cfrac {\left ( \cfrac {{s_Y}^2} m \right)^2}{m-1}}
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</math>
 +
 
 +
TTEST returns <math>\, tails \cdot \int_t^\infty f(x,\nu) \, dx </math> .
 +
 
 +
 
 +
 
 +
OpenOffice.org uses internally the regularized incomplete beta function to calculate the integral.
  
TTEST returns .
+
An empty element or an element of type ''string'' is ignored and in case paired samples its corresponding element in the other sample too. In contrast to other spreadsheet applications OpenOffice.org has no type ''boolean'' but treats ''false'' as 0 and ''true'' as 1.
For an empty element or an element of type Text or Boolean in X the element at the corresponding position of Y is ignored, and vice versa.
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Latest revision as of 22:35, 31 March 2010

Details

The Student's test is related to the t-distribution. Its density function is

where is the Gamma function and the parameter degree of freedom.

Paired Samples

If type=1, TTEST calculates the p-value for paired samples. It uses the differences of the pairs. So in this case the data X and Y should have the same count n.

TTEST returns

Unpaired Samples, Equal Variance

If type = 2, TTEST calculates the p-value of a comparison of means for independent samples from populations with equal variance. Besides

it uses the pooled variance

and

TTEST returns


Unpaired Samples, Unequal Variances

If type = 3, TTEST calculates the p-value of a comparison of means for independent samples from populations with not necessarily equal variances.

TTEST returns .


OpenOffice.org uses internally the regularized incomplete beta function to calculate the integral.

An empty element or an element of type string is ignored and in case paired samples its corresponding element in the other sample too. In contrast to other spreadsheet applications OpenOffice.org has no type boolean but treats false as 0 and true as 1.

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