Difference between revisions of "Manuals/calci/FTESTANALYSIS"

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<math>\frac {Sx^2}{Sy^2}</math> has an F-distribution with <math>n−1</math> and <math>m−1</math> degrees of freedom.
 
<math>\frac {Sx^2}{Sy^2}</math> has an F-distribution with <math>n−1</math> and <math>m−1</math> degrees of freedom.
 
*Also <math>Sx^2 </math> is the sample variance of first set of values.
 
*Also <math>Sx^2 </math> is the sample variance of first set of values.
*And <math>Sy^2 </math> is the sample variance of first set of values.
+
*And <math>Sy^2 </math> is the sample variance of second set of values.
 
*If the f-value from the test is higher than the f-critical value then the null hypothesis should be rejected and the variances are unequal.
 
*If the f-value from the test is higher than the f-critical value then the null hypothesis should be rejected and the variances are unequal.
 
*So the following cases will occur:
 
*So the following cases will occur:

Revision as of 14:28, 2 June 2015

FTESTANALYSIS(ar1,ar2,alpha,newtableflag)


  • and are array of data.
  • is the significance level.
  • is the logical value.

Description

  • This function gives the analysis of variance.
  • This statistics used to determine the significant difference of three or more variables or multivariate collected from experimental

research.

  • So this analysis is depending on the hypothesis.
  • The hypotheses for this test are
  (null hypothesis, variances are equal)
  (alternative hypothesis, variances are not equal)
  • For example, the comparison of SCORES across GROUPS,where there are two groups.
  • The purpose is to determine if the mean SCORE on a test is different for the two groups tested (i.e., control and treatment groups)
  • In FTESTANALYSIS(ar1,ar2,alpha,newtableflag) where is the data of first array, is the data of second array.
  • is the significance level which ranges from 0 to 1.
  • is the logical value like TRUE or FALSE.
  • TRUE is indicating the result will display in new worksheet.Suppose we are omitted the lv value it will consider the value as FALSE.
  • The F statistic of this function calculated by:

has an F-distribution with Failed to parse (syntax error): {\displaystyle n−1} and Failed to parse (syntax error): {\displaystyle m−1} degrees of freedom.

  • Also is the sample variance of first set of values.
  • And is the sample variance of second set of values.
  • If the f-value from the test is higher than the f-critical value then the null hypothesis should be rejected and the variances are unequal.
  • So the following cases will occur:
  • If the variances are assumed to NOT be equal, proceed with the t-test that assumes non-equal variances.
  • If the variances are assumed to be equal, proceed with the t-test that assumes equal variances.
  • In this function 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
15 27 19 32
DATA2
21 12 30 11
=FTEST(B4:B8,C4:C8)=0.81524906747183

2.

DATA1
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
14
DATA1
45 65
=FTEST(B1,C2:C3)=NAN

See Also

References

F Test