Jordan Boulger

Reliability is the key to achieving soundness in measurements that have potential for error. Not only will you learn about why reliability matters, but also the different types and how to apply them.

What is the difference between fixed and random factors in Mixed Models? Learn the criteria to decide which one you have.

Learn when you need to use Poisson or Negative Binomial Regression in your analysis, how to interpret the results, and how they differ from similar models.

"Listening to your webinars is a much easier way of brushing up than trying to reread through my grad school books.”

Kara Snoke, Biostatistician

Learn to run lengthy, repetitive tasks in Stata quickly and easily by setting up these two useful Stata tools in a do-file.

Do you want to know how to use SPSS syntax for data manipulation and analyses? You will witness all the advantages that come with using syntax, especially one that is already built-in.

Learn the different types of missing data and how they affect which approach to take in any situation.

“The webinars are a great way to learn or refresh on a particular topic area.”

Frances Aranda

Statistical software doesn't always give us the effect sizes we need. Learn some of the common effect size statistics and the ways to calculate them yourself.

This is a one-hour demonstration for new and intermediate Stata users on how to simplify your next analysis in Stata.

Are you analyzing data from a nationally representative survey? Learn about the different types of sampling techniques and their effects on data analysis.

Dan Lofald, Teacher Educator

Get beyond the frustration of learning odds ratios, logit link functions, and proportional odds assumptions on your own. See the incredible usefulness of logistic regression and categorical data analysis in this one-hour training.

Get the road map for your data analysis before you begin. Learn how to make any statistical modeling – ANOVA, Linear Regression, Poisson Regression, Multilevel Model – straightforward and more efficient.

Get started with the two building blocks of mixed models and see how understanding them makes these tough models much clearer.

Learn the approach for understanding coefficients in that regression as we walk through output of a model that includes numerical and categorical predictors and an interaction.

Ready to take your statistics proficiency to the next level? Learn all about Generalized Linear Mixed Models and when and how to apply it to your data analysis.

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