Difference between revisions of "Manuals/calci/TTESTTWOSAMPLESEQUALVARIANCES"

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TTESTTWOSAMPLESEQUALVARIANCES (Array1,Array2,HypothesizedMeanDifference,Alpha,NewTableFlag)
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<div style="font-size:30px">'''TTESTTWOSAMPLESEQUALVARIANCES(ar1,ar2,md,alpha,lv)'''</div><br/>
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<div style="font-size:30px">'''TTESTTWOSAMPLESEQUALVARIANCES (Array1,Array2,HypothesizedMeanDifference,Alpha,NewTableFlag)'''</div><br/>
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*<math>ar1 </math> and <math> ar2 </math>  are set of values.
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*<math>Array1 </math> and <math> Array2 </math>  are set of values.
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*<math>md </math> is the  Hypothesized Mean Difference.
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*<math>HypothesizedMeanDifference </math> is the  Hypothesized Mean Difference.
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*<math> alpha </math> is the significance level.
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*<math> Alpha </math> is the significance level.
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*<math> lv </math> is the logical value.
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*<math> NewTableFlag </math> is either 0 or 1.
  
 
==Description==
 
==Description==
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*1.The two sample sizes  are equal;
 
*1.The two sample sizes  are equal;
 
*2.It can be assumed that the two distributions have the same variance.
 
*2.It can be assumed that the two distributions have the same variance.
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*In <math>TTESTTWOSAMPLESEQUALVARIANCES(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 .
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*In <math>TTESTTWOSAMPLESEQUALVARIANCES (Array1,Array2,HypothesizedMeanDifference,Alpha,NewTableFlag)</math>, <math>Array1 </math> and <math> Array2 </math> are two arrays of sample values. <math> HypothesizedMeanDifference </math> is the Hypothesized Mean Difference .
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*Suppose md=0 which  indicates that sample means are hypothesized to be equal.
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*Suppose HypothesizedMeanDifference=0 which  indicates that sample means are hypothesized to be equal.
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*<math> alpha </math> is the significance level which ranges from 0 to 1.
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*<math> Alpha </math> is the significance level which ranges from 0 to 1.
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*<math> lv </math> is the logical value like TRUE or FALSE.
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*<math> NewTableFlag </math> is either 0 or 1.
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*TRUE is indicating the result will display in new worksheet.Suppose we are omitted the lv value it will consider the value as FALSE.
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*"1" is indicating the result will display in new worksheet.Suppose we are omitted the NewTableFlag value it will consider the value as "0".
 
*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_{x1}.s_{x2}.\sqrt{\frac{2}{n}}}</math>
 
  <math>t = \frac{\bar{x_1}-\bar{x_2}}{s_{x1}.s_{x2}.\sqrt{\frac{2}{n}}}</math>
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*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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   2.alpha>1
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   2.Alpha>1
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   3.<math>ar1 </math> and <math> ar2 </math> are having different number of data points.
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   3.<math>Array1 </math> and <math> Array2 </math> are having different number of data points.

Revision as of 16:30, 20 December 2016

TTESTTWOSAMPLESEQUALVARIANCES (Array1,Array2,HypothesizedMeanDifference,Alpha,NewTableFlag)


  • and are set of values.
  • is the Hypothesized Mean Difference.
  • is the significance level.
  • is either 0 or 1.

Description

  • This function calculating the two Sample for equal variances determines whether two sample means are equal.
  • We can use this test when both:
  • 1.The two sample sizes are equal;
  • 2.It can be assumed that the two distributions have the same variance.
  • In , and are two arrays of sample values. is the Hypothesized Mean Difference .
  • Suppose HypothesizedMeanDifference=0 which indicates that sample means are hypothesized to be equal.
  • is the significance level which ranges from 0 to 1.
  • is either 0 or 1.
  • "1" is indicating the result will display in new worksheet.Suppose we are omitted the NewTableFlag value it will consider the value as "0".
  • The t statistic of this function calculated by:

where

  • Here and are unbiased estimators of the variances of two samples. is the grand standard deviation data 1 and data2 and n is the data points of two data set.
  • This function will give the result as error when
  1.any one of the argument is non-numeric.
  2.Alpha>1
  3. and  are having different number of data points.
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