Difference between revisions of "Manuals/calci/TTESTEQUALVARIANCES"

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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.
−
*In <math>TTESTTWOSAMPLESEQUALVARIANCES(ar1,ar2,md,alpha,lv), ar1 </math> and <math> ar2 </math> are two arrays of sample values. <math> md </math> is the Hypothesized Mean Difference .
+
*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 .
 
*Suppose md=0 which  indicates that sample means are hypothesized to be equal.
 
*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.
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*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>
−
where <math>s_{x1}.s_{x2} = \sqrt{\frac{1}{2}(s_{x1}^2+s_{x2}^2)}</math>
+
where <math>s_{x1}.s_{x2} = \sqrt{\frac{1}{2}(s_{x1}^2+s_{x2}^2)}</math>
−
*Here <math>s_x_1</math> and <math>s_x_2</math> are unbiased estimators of the variances of two samples.<math>s_x_1.s_x_2</math> is the grand standard deviation data 1 and data2 and n is the data points of two data set.   
+
*Here <math>s_x_1</math> and <math>s_x_2</math> are unbiased estimators of the variances of two samples.<math>s_{x1}.s_{x2}</math> 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  
 
*This function will give the result as error when  
−
   1.any one of the argument is nonnumeric.
+
   1.any one of the argument is non-numeric.
 
   2.alpha>1
 
   2.alpha>1
−
   3.ar1 and ar2 are having different number of data points.
+
   3.<math>ar1 </math> and <math> ar2 </math> are having different number of data points.
  
 
==Examples==
 
==Examples==

Revision as of 00:15, 4 February 2014

TTESTTWOSAMPLESEQUALVARIANCES(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 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 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 lv value it will consider the value as FALSE.
  • The t statistic of this function calculated by:

where

  • Here Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle s_{x}_{1}} and Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle s_{x}_{2}} 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.

Examples

Spreadsheet
A B C D E F
1 10 15 18 27 12 34
2 17 20 25 39 9 14


  1. =TTESTSAMPLESEQUALVARIANCES(A1:F1,A2:F2,2,0.5)


See Also


References

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