Feature selection using F-Test

I am trying to rank features given in following feature vectors, samples from three different class are given. I want to ask if it possible to rank them based on the F-Test score. I am new here and have gaps in understanding. I tried using anovan but I am not sure is it applicable here. I seek your guaidance and help with come simple example. I would appriciate is some example of feature ranking on IRIS dataset is possible.

class1 = [1.8779,2.651,2.2211,2.1688]';
class2 = [1.301,2.2902,2.3023,2.1251]';
class3 = [1.9504,2.4366,3.0451,2.9937]';

[Image Analyst]

So you have some large data set, like an image or batch of measurements or something. Then you make 4 measurements of features on those samples, like feature 1 = mean value, feature 2 = median, feature 3 = average diameter, feature 4 = area fraction, or whatever they might really be.

So you have some vectors that define maybe the means of the measurements for class 1 and class 2. Or maybe those are sample vectors for collections of samples from class 1, and two collections of samples taken from what is known to be class 2 things. Or is the last one supposed to be class 3? Why is there no class 3 shown?

I think I need a bit more info before I can answer. How would you compute the F-test from each class vector that you showed?

[Saifullah Khalid]

Sorry, it was a typing error, now I have corrected. I have samples from three classes. Each element of sample represent a feature like you wrote.