Difference between revisions of "Manuals/calci/TTESTUNEQUALVARIANCES"

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*<math> alpha </math> is the significance level.
 
*<math> alpha </math> is the significance level.
 
*<math> lv </math> is the logical value.
 
*<math> lv </math> is the logical value.
 
  
 
==Description==
 
==Description==
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*1.the two sample sizes  are may are may not be equal;
 
*1.the two sample sizes  are may are may not be equal;
 
*2. The means and variances are distinct .
 
*2. The means and variances are distinct .
*In <math>TTESTTWOSAMPLESUNEQUALVARIANCES(ar1,ar2,md,alpha,lv), ar1</math> and <math> ar2 </math> are two arrays of sample values.
+
*In <math>TTESTTWOSAMPLESUNEQUALVARIANCES(ar1,ar2,md,alpha,lv)</math>, <math>ar1</math> and <math> ar2 </math> are two arrays of sample values.
*<math> md </math> is the Hypothesized Mean Difference .Suppose md = 0 which  indicates that sample means are hypothesized to be equal.
+
*<math> md </math> is the Hypothesized Mean Difference. Suppose md = 0 which  indicates that sample means are hypothesized to be equal.
 
*<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> lv </math> is the logical value like TRUE or FALSE.
 
*<math> lv </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 <math>lv</math> value it will consider the value as FALSE.
*The t statistic of this function calculated by:
+
*The t-statistic of this function calculated by:
<math> t=\frac{\bar{x_1}-\bar{x_2}}{s_{\bar{x_1}-\bar{x_2}}}</math> where <math>s_{\bar{x_1}-\bar{x_2}}= \sqrt{\frac{s_1^2}{n_1}+\frac{s_2^2}{n_2}} </math>
+
<math> t=\frac{\bar{x_1}-\bar{x_2}}{s_{\bar{x_1}-\bar{x_2}}}</math>
*Here <math> s_1^2</math> and <math> s_2^2</math> are unbiased estimators of the variances of two samples. <math> n_1</math> and <math> n_2</math> are the number of data points in two arrays . <math>s_{\bar{x_1}-\bar{x_2}} is not a pooled variance.
+
where <math>s_{\bar{x_1}-\bar{x_2}}= \sqrt{\frac{s_1^2}{n_1}+\frac{s_2^2}{n_2}} </math>
 +
*Here <math> s_1^2</math> and <math> s_2^2</math> are unbiased estimators of the variances of two samples. <math> n_1</math> and <math> n_2</math> are the number of data points in two arrays. <math>s_{\bar{x_1}-\bar{x_2}}</math> is not a pooled variance.
 
*This function will give the result as error when
 
*This function will give the result as error when
 
       1. any one of the argument is non-numeric.
 
       1. any one of the argument is non-numeric.
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#=TTESTSAMPLESEQUALVARIANCES(A1:F1,A2:F2,0.5)
+
#=TTESTTWOSAMPLESUNEQUALVARIANCES(A1:F1,A2:F2,3,0.5)
 +
{| class="wikitable"
 +
|+Result
 +
|-
 +
! !! Variable 1 !! Variable 2
 +
|-
 +
! Mean
 +
| 20.666666666666668 || 20.833333333333332
 +
|-
 +
! Variance
 +
| 105.06666666666665 || 196.56666666666666
 +
|-
 +
! Observations
 +
| 6 || 6
 +
|-
 +
! Hypothesized Mean Difference
 +
| 3
 +
|-
 +
! Degree Of Freedom
 +
| 9
 +
|-
 +
! T- Statistics
 +
| -0.4466201458140038
 +
|-
 +
! P(T<=t) One-tail
 +
| 0.3328511748583461
 +
|-
 +
! T Critical One-Tail
 +
| 0 
 +
|-
 +
! P(T<=t) Two-tail
 +
| 0.6657023497166922
 +
|-
 +
! T Critical Two-Tail
 +
| 0.7027221467691982
 +
|}
  
 +
==Related Videos==
  
 +
{{#ev:youtube|L-jfenou5hI|280|center|TTESTUNEQUALVARIANCES}}
  
 
==See Also==
 
==See Also==
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*[[Manuals/calci/TINV  | TINV ]]
 
*[[Manuals/calci/TINV  | TINV ]]
 
*[[Manuals/calci/TTESTEQUALVARIANCES  | TTESTEQUALVARIANCES ]]
 
*[[Manuals/calci/TTESTEQUALVARIANCES  | TTESTEQUALVARIANCES ]]
 
  
 
==References==
 
==References==
 +
*[http://en.wikipedia.org/wiki/Student%27s_t-test Student's t-test]

Latest revision as of 14:04, 2 July 2015

TTESTTWOSAMPLESUNEQUALVARIANCES(ar1,ar2,md,alpha,lv)


  • and are set of values.
  • is the Hypothesized Mean Difference.
  • is the significance level.
  • is the logical value.

Description

  • This function calculating the two Sample for unequal variances determines whether two sample means also distinct.
  • We can use this test when both:
  • 1.the two sample sizes are may are may not be equal;
  • 2. The means and variances are distinct .
  • In , and are two arrays of sample values.
  • is the Hypothesized Mean Difference. Suppose md = 0 which indicates that sample means are hypothesized to be equal.
  • 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 value it will consider the value as FALSE.
  • The t-statistic of this function calculated by:

where

  • Here and are unbiased estimators of the variances of two samples. and are the number of data points in two arrays. is not a pooled variance.
  • This function will give the result as error when
     1. any one of the argument is non-numeric.
     2.alpha>1

Examples

Spreadsheet
A B C D E F G
1 12 21 9 18 27 37 41
2 19 8 45 29 14 10 11


  1. =TTESTTWOSAMPLESUNEQUALVARIANCES(A1:F1,A2:F2,3,0.5)
Result
Variable 1 Variable 2
Mean 20.666666666666668 20.833333333333332
Variance 105.06666666666665 196.56666666666666
Observations 6 6
Hypothesized Mean Difference 3
Degree Of Freedom 9
T- Statistics -0.4466201458140038
P(T<=t) One-tail 0.3328511748583461
T Critical One-Tail 0
P(T<=t) Two-tail 0.6657023497166922
T Critical Two-Tail 0.7027221467691982

Related Videos

TTESTUNEQUALVARIANCES

See Also

References