What is the difference between f-test and t-test?

Hello Everybody;

Hope you are all doing well...

Can anybody explain the main difference between f-test and t-test?,

where i want to use it as method to identify the effective features among a list 60 features extracted out of two types of data (i.e, data 1 composed of 30 image for each image 60 features are extracted/ data 2 composed of 40 images for each image 60 features are extracted), i do search but i still misunderstand the difference..

Note that: the matlab equations for t- test is (h = ttest2(x,y)) and f-test is (H = vartest2(X,Y))

Thanks Alot;

Answer 1

[Shashank Prasanna]

t-test is used to test if two sample have the same mean. The assumptions are that they are samples from normal distribution.

f-test is used to test if two sample have the same variance. Same assumptions hold.

I have little to no experience in image processing to comment on if these tests make sense to your application. A little more info of the problem you are trying to solve will be useful.

If you are however solving a classification problem (categorizing your images) You can use stepwise logistic regression with F-statistics criterion to reduce your predictor dimension:

http://www.mathworks.com/help/stats/generalizedlinearmodel.stepwise.html

Alternatively you could use PCA as Image Analyst suggested which does not take into account the response when reducing the dimensionality.

[Mariam Sheha]

Thanks for Replaying...

i am not on the classification phase, just trying to judge the extracted features that i did extract from an image to be quit effective to insert it as an input data for my classifier...

anyway, i will try all the proposed suggestions to get the best results..

Thanks A lot;

Answer 2

[Image Analyst]

Were the Wikipedia explanations not understandable? Anyway, I'm no statistician but I think you'd want Principal Components Analysis, rather than t-test of F-test, if you want to figure out which of 60 features are the most important.

[Mariam Sheha]

Thanks a lot for replaying....

I don't say that 'i don't understand it,but the difference between using t-test or f-test upon my data as listed above was my question!

Anyway, i had partially get the answer, which specify that using t-test may be much more effective for my data than F-test, also using PCA to figure out the most effective features is a good idea...

Thanks a lot

[Image Analyst]

OK, whatever...I have no idea how you'd use either the t-test or F-test with 60 features to "judge the features", but if you do, then that's all that counts.