Membership Webinars

Member Event: Count Models Accelerator

July 30th, 2025 by

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 count modelslive 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
Count models come in a few types, and any of these can also be used for rates:
  • 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.
In this accelerator, learn about the different types of count models, how to understand their results, how to apply them to rates, and how to choose among them.

 


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and is a combination of watching recorded trainings and live events.

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Member Training: Cubic Splines

July 2nd, 2025 by

Splines provide a useful way to model relationships that are more complex than a simple linear function. They work with a variety of regression models.

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Member Training: Introduction to Data Analysis using R Tutorial

June 12th, 2025 by

This month we are featuring a 9-module software tutorial by Kim Love: An Introduction to Data Analysis using R.

It’s perfect for people who:

  • have never used R before
  • need to refresh their R skills after not using it for while
  • have figured out R on their own and would like a more systematic tutorial

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Member Training: Interpreting (Even Tricky) Regression Coefficients Workshop

April 1st, 2025 by

In April and May, we’re doing something new: including in membership the workshop Interpreting (Even Tricky) Regression Coefficients with Karen Grace-Martin. 

We’ll be releasing the first 3 of 6 modules in April and modules 4-6 in May and holding a special Q&A with Karen at the end of each month.

If you’ve ever wanted to know how to interpret your results or set up your model to get the information you needed, you’ll love this workshop.

Although it’s at Stage 2 and focuses entirely on linear models, everything applies to all sorts of regression models — logistic, multilevel, count models. All of them.

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Member Training: Confirmatory Factor Analysis

March 3rd, 2025 by

There are two main types of factor analysis: exploratory and confirmatory.

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Member Training: Exploratory Factor Analysis

February 1st, 2025 by

Many variables we want to measure just can’t be directly measured with a single variable. Instead you have to combine a set of variables into a single index.

But how do you determine which variables to combine and how best to combine them?

Exploratory Factor Analysis.

EFA is a method for finding a measurement for one or more unmeasurable (latent) variables from a set of related observed variables. It is especially useful for scale construction.

In this webinar, you will learn through three examples an overview of EFA, including:

  • The five steps to conducting an EFA
  • Key concepts like rotation
  • Factor scores
  • The importance of interpretability

Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

Not a Member? Join!

About the Instructor

Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.

She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.

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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.