Hypothesis testing for contact center Our contact center offers digital marketing solutions. Our client has asked to test the hypothesis that if the first call to a customer is longer (than a specific time) then the customer will most likely not answer the follow-up calls i.e the second and/or the third call.
Can this be really tested? What kind of data should I look at? I am new to stats, please help me understand the technique and solve this problem.

There are a bunch of more sophisticated ways to do this, but the quick solution is to be quite literal.
You have a binary predictor: if the call lasts longer than some amount of time.
You have a binary outcome: if the customer answer follow-up calls.
This is a classic situation for something called the chi-squared test. There are four outcomes.

*

*Short call, follow-up answered


*Short call, follow-up ignored


*Long call, follow-up answered


*Long call, follow-up ignored
Arrange these in a grid as references for the chi-squared test describe (I recall liking the Wikipedia article). The test then tests if the proportions of follow-up calls answered vs ignored differs between the long-call and short-call groups, exactly what you want to know.
