# Statistical tests for count data with many zeros

I have to compare three groups (each group is a customer to a subscription box company).

We count the total number of boxes sold in each group (i.e. we are modelling count data)

I want to compare the mean number of boxes in group A and B vs the control (to see if the uplift is greater)

For this data ~2% of Group A got a box, ~2.1% of Group B got a box, and ~1.1% of Group C got a box.

What tests could we run to compare the means or the difference in uplift vs control for Group A and Group B?

I don't think a t-test or a Mann-Whitney test is appropriate here (though I am willing to be proven wrong!)

• Run a zero inflated negative binomial model using group c as the reference. Commented Oct 28, 2019 at 22:34
• Why isn't the outcome binary here if the data is at user level? Can users purchase more than one subscription box? Commented Oct 28, 2019 at 23:39
• Why do you think this is zero inflated data as opposed to just data with zeroes in it? Commented Oct 29, 2019 at 1:58
• @DimitriyV.Masterov users can buy a box a week, and we look at how many boxes they bought in a 20-week window. The outcome would be binary if it was just conversions after 20 weeks. Commented Oct 29, 2019 at 8:47
• @jbowman I'm not sure of the distinction, I'm afraid. Commented Oct 29, 2019 at 8:48