Member Event: Count Models Accelerator

You’ll be excited to hear we’re doing another Statistics Skills Accelerator for our Statistically Speaking members: Count Models.

Stats Skills Accelerators are structured events focused on an important topic. They feature Stat’s Amore Trainings in a suggested order, as well as live Q&As specific to the Accelerator.

In August, our mentors will be running a new Accelerator.  The first Q&A is August 6, 2025 at 3 pm ET, hosted by Jeff Meyer.

Count models are used when the outcome variable in a model or group comparison is a discrete count:

• Number of eggs in a clutch
• Number of days in intensive care
• Number of aggressive incidents in detention

• Poisson Regression is the simplest and is the basis for all the other models, but its assumptions are rarely met with real data.
• Negative Binomial regression adds an extra parameter to a Poisson regression measure the extra variance that often occurs in real data.
• Truncated count models work when the lowest values (often just zero) cannot occur. This happens when a count has to occur in order to be part of the population of interest.
• Zero inflated count models are used when there are more zeros than expected. For this model, some zeros could have been something else and others couldn’t.
• Hurdle models also work when there are more zeros than expected, but the process of having a zero is different. In these models, there is an actual “hurdle” one has to pass in order to have a non-zero count.
• Logistic regression, when your count is out of of maximum number.

Just head over and sign up for Statistically Speaking.

You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.