HYpothesis testing - Type l and II Errors

data_science

#1

Hi Experts,

How do we identify type l or type ll errors in regression problems and how do we solve them?

insights much appreciated.

Thanks,
Tony


#2

Hi tillutony,

Type 1 error means rejecting the null hypothesis when it’s actually true.
Type 2 error is accepting the null hypothesis when it’s actually false.

If you create a confusion matrix you can identify the errors as below.


#3

Hi disha sree,

How do we get this done in regression problems please let me know with piece of code or point me to some examples.

Thanks,
Tony


#4

It would be better of you let me know the exact problem you’re facing. In linear regression we don’t identify the errors using type 1 or type 2 error, we normally use root mean squared error.

While in case of logistic regression we might use accuracy matrix to identify the errors since we’re using it for classification purposes.

I would need more context to answer your question