Difference between revisions of "Manuals/calci/FTESTANALYSIS"

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<div style="font-size:30px">'''FTESTANALYSIS(ar1,ar2,alpha,newtableflag)'''</div><br/>
+
<div style="font-size:30px">'''FTESTANALYSIS (Array1,Array2,Alpha,NewTableFlag)'''</div><br/>
*<math>ar1</math> and <math>ar2 </math> are array of data.
+
*<math>Array1</math> and <math>Array2 </math> are array of data.
*<math>alpha</math>  is the significance level.
+
*<math>Alpha</math>  is the significance level.
*<math>newtableflag</math>  is the logical value.
+
*<math>Newtableflag</math>  is the logical value.
 +
**FTESTANALYSIS(), compares the variances between two group of data.
  
 
==Description==
 
==Description==
Line 14: Line 15:
 
*For example, the comparison of SCORES across GROUPS,where there are two groups.
 
*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)
 
*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 <math>ar1</math> is the data of  first array, <math>ar2</math> is the data of second array.
+
*In FTESTANALYSIS (Array1,Array2,Alpha,NewTableFlag) where <math>Array1</math> is the data of  first array, <math>Array2</math> is the data of second array.
*<math> alpha </math> is the significance level which ranges from 0 to 1.
+
*<math> Alpha </math> is the significance level which ranges from 0 to 1.
*<math> newtableflag </math> is the logical value like TRUE or FALSE.
+
*<math> Newtableflag </math> 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.
 
*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:
 
*The F statistic of this function calculated by:
<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 n−1 and m−1 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 second set of values.
 
*And <math>Sy^2 </math> is the sample variance of second set of values.
Line 28: Line 29:
 
*In this function the array may be any numbers, names, or references that contains numbers.  
 
*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.  
 
*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.
+
When the <math>Array1</math> or <math>Array2</math> is less than 2 or the variance of the array value is zero, then this function will return the result as error.
 +
 
 +
==ZOS==
 +
*The syntax is to use this function in ZOS is <math>FTESTANALYSIS (Array1,Array2,Alpha,NewTableFlag)</math>
 +
**<math>Array1</math> and <math>Array2 </math> are array of data.
 +
**<math>Alpha</math>  is the significance level.
 +
**<math>Newtableflag</math>  is the logical value.
 +
*For e.g.,FTESTANALYSIS([17,22,26,31,49],[50,47,45,13,24],0.4,true)
 +
*FTESTANALYSIS([24..30],[45..51],0.4,true)
  
 
==Examples==
 
==Examples==
 
1.
 
1.
{| class="wikitable"  
+
{| class="wikitable"
|+ DATA1
+
|+Spreadsheet
|-  
+
|-
| 15
+
! !! A !! B
| 27
+
|-
| 19
+
! 1
| 32
+
|15 || 21
 +
|-
 +
! 2
 +
|27 || 12
 +
|-
 +
! 3
 +
|19 || 30
 +
|-
 +
! 4
 +
|32 || 11
 
|}
 
|}
 +
=FTESTANALYSIS(A1:A4,B1:B4,0.5,TRUE)
  
 
{| class="wikitable"  
 
{| class="wikitable"  
|+ DATA2
+
|+Result
|-  
+
|-  
| 21
+
! !!Variable1 !! Variable2
| 12
+
|-
| 30
+
! Mean
| 11
+
| 23.25 || 18.5
 +
|-
 +
! Variance
 +
| 58.916666666666664 || 79
 +
|-
 +
! Observations
 +
| 4 || 4
 +
|-
 +
! Degree Of Freedom
 +
| 3 || 3
 +
|-
 +
! F-Value
 +
| 0.7457805907172995 ||
 +
|-
 +
! P(F<=f) one-tail
 +
| 0.407624533735915 ||
 +
|-
 +
! F Critical one-tail
 +
| 1 ||
 
|}
 
|}
 
+
   
  =FTEST(B4:B8,C4:C8)=0.81524906747183
 
  
 
2.
 
2.
{| class="wikitable"  
+
{| class="wikitable"
|+ DATA1
+
|+Spreadsheet
|-  
+
|-
| 5
+
! !! A !! B
| 8
+
|-
| 12
+
! 1
| 45
+
|5 || 10
| 23
+
|-
 +
! 2
 +
|8 || 20
 +
|-
 +
! 3
 +
|12 || 30
 +
|-
 +
! 4
 +
|45 || 40
 +
|-
 +
! 5
 +
|23 || 50
 
|}
 
|}
  
 +
=FTEST(A1:A5,B1:B5,0.30,false)
 
{| class="wikitable"  
 
{| class="wikitable"  
|+ DATA2
+
|+Result
|-  
+
|-  
| 10
+
! !!Variable1 !! Variable2
| 20
+
|-
| 30
+
! Mean
| 40
+
| 18.6 || 30
| 50
+
|-
|}
+
! Variance
=FTEST(A1:A5,C1:C5)=0.9583035732212274 
+
| 264.29999999999995 || 250
3.
+
|-
{| class="wikitable"
+
! Observations
|+ DATA1
+
| 5 || 5
|-  
+
|-
| 14
+
! Degree Of Freedom
| 26
+
| 4 || 4
| 37
+
|-
 +
! F-Value
 +
| 1.0572 ||
 +
|-
 +
! P(F<=f) one-tail
 +
| 0.4791517866106137 ||
 +
|-
 +
! F Critical one-tail
 +
| 1.7528541706121352 ||
 
|}
 
|}
  
{| class="wikitable"
+
==Related Videos==
|+ DATA2
 
|-
 
| 45
 
| 82
 
| 21
 
|17
 
|}
 
FTEST(B1:B3,C1:C4} = 0.26412211240525474
 
  
4.
+
{{#ev:youtube|G_RDxAZJ-ug|280|center|F Distribution}}
{| class="wikitable"
 
|+ DATA1
 
|-
 
| 14
 
|}
 
{| class="wikitable"
 
|+ DATA1
 
|-  
 
| 45
 
| 65
 
|}
 
=FTEST(B1,C2:C3)=NAN
 
  
 
==See Also==
 
==See Also==
 +
*[[Manuals/calci/FTEST  | FTEST ]]
 
*[[Manuals/calci/FDIST  | FDIST ]]
 
*[[Manuals/calci/FDIST  | FDIST ]]
 
*[[Manuals/calci/FINV  | FINV ]]
 
*[[Manuals/calci/FINV  | FINV ]]
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==References==
 
==References==
 
[http://en.wikipedia.org/wiki/F-test  F Test]
 
[http://en.wikipedia.org/wiki/F-test  F Test]
 +
 +
 +
 +
*[[Z_API_Functions | List of Main Z Functions]]
 +
 +
*[[ Z3 |  Z3 home ]]

Latest revision as of 17:07, 7 August 2018

FTESTANALYSIS (Array1,Array2,Alpha,NewTableFlag)


  • and are array of data.
  • is the significance level.
  • is the logical value.
    • FTESTANALYSIS(), compares the variances between two group of data.

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 (Array1,Array2,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 n−1 and 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.

ZOS

  • The syntax is to use this function in ZOS is
    • and are array of data.
    • is the significance level.
    • is the logical value.
  • For e.g.,FTESTANALYSIS([17,22,26,31,49],[50,47,45,13,24],0.4,true)
  • FTESTANALYSIS([24..30],[45..51],0.4,true)

Examples

1.

Spreadsheet
A B
1 15 21
2 27 12
3 19 30
4 32 11

=FTESTANALYSIS(A1:A4,B1:B4,0.5,TRUE)

Result
Variable1 Variable2
Mean 23.25 18.5
Variance 58.916666666666664 79
Observations 4 4
Degree Of Freedom 3 3
F-Value 0.7457805907172995
P(F<=f) one-tail 0.407624533735915
F Critical one-tail 1


2.

Spreadsheet
A B
1 5 10
2 8 20
3 12 30
4 45 40
5 23 50

=FTEST(A1:A5,B1:B5,0.30,false)

Result
Variable1 Variable2
Mean 18.6 30
Variance 264.29999999999995 250
Observations 5 5
Degree Of Freedom 4 4
F-Value 1.0572
P(F<=f) one-tail 0.4791517866106137
F Critical one-tail 1.7528541706121352

Related Videos

F Distribution

See Also

References

F Test