Membership Webinars

Member Training: R for Menu Users Software Tutorial

December 30th, 2021 by

In this nearly 6-hour tutorial you will learn menu-based R libraries so you can use R without having to fuss with R code. These libraries don’t cover everything R can do, but they do quite a bit and can set you up to make running R much easier.

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Member Training: Difference in Differences

November 30th, 2021 by

The great majority of all regression modeling explores and tests the association between independent and dependent variables. We are not able to claim the independent variable(s) has a causal relationship with the dependent variable. There are five specific model types that allow us to test for causality. Difference in differences models are one of the five.

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Member Training: Classic Experimental Designs

October 29th, 2021 by

Stage 2Have you ever wondered why there are so many different types of experimental designs, and how a researcher would go about choosing among them to best address their research questions? (more…)


Member Training: ANOVA Post-hoc Tests: Practical Considerations

October 1st, 2021 by

Stage 2Post-hoc tests, pairwise or other linear contrasts, are typical in an analysis of variance (ANOVA) setting to understand which group means differ. They incorporate p-value adjustments to avoid concluding that group means differ when they actually do not. There are several adjustments that can be considered for conducting multiple post-hoc tests, including single-step and stepwise adjustments. (more…)


Member Training: Matrix Algebra for Data Analysts: A Primer

August 31st, 2021 by

If you’ve been doing data analysis for very long, you’ve certainly come across terms, concepts, and processes of matrix algebra.  Not just matrices, but:

  • Matrix addition and multiplication
  • Traces and determinants
  • Eigenvalues and Eigenvectors
  • Inverting and transposing
  • Positive and negative definite

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Member Training: Moving to a World Beyond p<0.05

August 2nd, 2021 by

Stage 1

For nearly a hundred years the concept of “statistical significance” has been fundamental to statistics and to science. And for nearly that long, it has been controversial and misused as well. (more…)