Changes

*So, if the variances are equal, the ratio of the variances will be 1.

*So, if the variances are equal, the ratio of the variances will be 1.

*Let X1,...Xn and Y1...Ym be independent samples each have a Normal Distribution .  

*Let X1,...Xn and Y1...Ym be independent samples each have a Normal Distribution .  

*It's sample means: <math>\bar X=\frac{1}{n} \sum_{i=1}^n Xi</math> and  <math>\bar Y =\frac {1}{m} \sum_{i=1}^m Yi</math> .  

*It's sample means:  

<math>\bar X=\frac{1}{n} \sum_{i=1}^n Xi</math>

and   

:<math>\bar Y =\frac {1}{m} \sum_{i=1}^m Yi</math> .  

*The sample variances :

*The sample variances :

  <math>SX^2=\frac{1}{n-1} \sum_{i=1}^n (Xi-\bar X)^2</math>

  <math>SX^2=\frac{1}{n-1} \sum_{i=1}^n (Xi-\bar X)^2</math>