Difference between revisions of "Manuals/calci/FTEST"

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*The F-test is designed to test if two population variances are equal.  
 
*The F-test is designed to test if two population variances are equal.  
 
*It does this by comparing the ratio of two variances.  
 
*It does this by comparing the ratio of two variances.  
*So, if the variances are equal, the ratio of the variances will be 1.Let X1, ..., Xn and Y1, ..., Ym be independent samples each have a normal distribution .  
+
*So, if the variances are equal, the ratio of the variances will be 1.
*It's sample means: X(bar)=1/n summation(i=1 to n)Xi and  Y(bar)=1/m summation(i=1 to m)Yi .  
+
*Let X1,...Xn and Y1...Ym be independent samples each have a Normal Distribution .  
*The sample variances : Sx^2=1/n-1 summation(i=1 to n)(Xi-X(bar))^2.and SY^2=1/m-1 summation(i=1 to m)(Yi-Y(bar))^2.  
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*It's sample means: <math>\bar X=\frac{1}{n} \sum_(i=1)^n Xi</math> and  <math>\bar Y =\frac {1}{m} \sum_{i=1}^m Yi</math> .  
*Then the test statistic= Sx^2/Sy^2   has an F-distribution with n − 1 and m − 1 degrees of freedom.
+
*The sample variances :
*In FTEST(ar1,ar2) where ar1 is the data of  first array,ar2 is the data of second array.  
+
<math>SX^2=\frac{1}{n-1} \sum_{i=1}^n (Xi-\bar X))^2</math>
*The array may be any numbers, names, or refernces that contains numbers.  
+
and :
*Suppose the array contains any text, logical values or empty cells like that values are not considered.  
+
<math>SY^2=\frac{1}{m-1} \sum_{i=1}^m (Yi-\bar Y)^2.  
When the ar or ar2 is less than 2 or the variance of the array value is zero then this function will return the result as error.
+
*Then the Test Statistic = <math>\frac {Sx^2}{Sy^2}<math> has an F-distribution with <math>n−1</math> and <math>m − 1</math> degrees of freedom.
 +
*In FTEST(ar1,ar2) where <math>ar1</math> is the data of  first array, <math>ar2</math> is the data of second array.  
 +
*The array may be any numbers, names, or references that contains numbers.  
 +
*values are not considered if the array contains any text, logical values or empty cells.  
 +
When the <math>ar1</math> or <math>ar2</math> is less than 2 or the variance of the array value is zero, then this function will return the result as error.
 +
 
 
==Examples==
 
==Examples==
  

Revision as of 04:23, 10 December 2013

FTEST(ar1,ar2)


  • and are array of data.

Description

  • This function gives the result of F-test.
  • The F-test is designed to test if two population variances are equal.
  • It does this by comparing the ratio of two variances.
  • So, if the variances are equal, the ratio of the variances will be 1.
  • Let X1,...Xn and Y1...Ym be independent samples each have a Normal Distribution .
  • It's sample means: and .
  • The sample variances :

and :
Failed to parse (syntax error): {\displaystyle SY^2=\frac{1}{m-1} \sum_{i=1}^m (Yi-\bar Y)^2.  *Then the Test Statistic = <math>\frac {Sx^2}{Sy^2}<math> has an F-distribution with <math>n−1}
 and Failed to parse (syntax error): {\displaystyle m − 1}
 degrees of freedom.
  • In FTEST(ar1,ar2) where is the data of first array, is the data of second array.
  • The array may be any numbers, names, or references that contains numbers.
  • values are not considered if the array contains any text, logical values or empty cells.

When the or is less than 2 or the variance of the array value is zero, then this function will return the result as error.

Examples

1.DATA1 DATA2

 15                   21
  27                  12
  19                  30
 32                    11

FTEST(B4:B8,C4:C8)=0.81524906747183 2.DATA 1={5,8,12,45,23}; DATA2={10,20,30,40,50}

FTEST(A1:A5,C1:C5)=0.9583035732212274  

3. DATA1={14,26,37};DATA2={45,82,21,17} FTEST(B1:B3,C1:C4}=0.26412211240525474 4.DATA1={25},DATA2={45,65} FTEST(B1,C2:C3)=NAN

See Also


References

Correlation