Recent innovations in data science raise troubling questions about discrimination and loss of privacy. 
In this training, you will see how statistics are not cold, hard numbers, but reflections of the perspectives and biases of those collecting the data.
We’ll discuss several case studies that show how real the harms can be. You’ll learn about some of these ethical problems and some possible solutions.
Webinar Date & Time: May 19, 2026 at 3pm US ET.
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.
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Mediation analysis is a model of the causal pathway between an independent variable, X, and a dependent variable, Y, through a mediating variable, M.
In this training, you’ll learn the right way to test mediation and the design issues that allow a causal interpretation.
We’ll discuss a number of issues in testing mediation, new and old. These include the Baron & Kenny 4-step approach, the difference between mediation and moderation, and Sobel and bootstrap tests for indirect effects.
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.
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.
Not a Member Yet?
It’s never too early to set yourself up for successful analysis with support and training from expert statisticians.
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.
Regression models, such as linear, logistic, time to event, and mixed models, measure the strength of the association between the dependent variable and the independent variables.
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When you’re working with many correlated variables, they get too unwieldy to use individually.
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Cross-over trials provide a very powerful approach for comparing two treatment conditions. Research subjects get both treatment conditions, which we will label arbitrarily as A and B.
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Estimated marginal means (EMMs)—sometimes called least-squares means—are a powerful way to interpret and visualize results from linear and mixed-effects models. Yet many researchers struggle to extract, understand, and plot them.
In this 60-minute hands-on tutorial, participants will learn how to compute, interpret, and visualize EMMs using only base R functions together with the emmeans, car, and lme4 packages. We will start with simple linear models and progress to mixed models with random effects, highlighting how to obtain EMMs, confidence intervals, pairwise contrasts, and publication-ready base R plots. The session emphasizes conceptual understanding and practical code you can adapt immediately to your own analyses.
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.
About the Instructor
Manolo Romero Escobar is a seasoned statistical consultant and psychometrician with a passion for helping researchers.
Throughout his career, Manolo has worked extensively as a research and statistical consultant. He has served a diverse range of clients including health researchers, educational institutions, and government agencies. With a focus on linear mixed effects modeling, latent variable modeling, and scale development, Manolo brings a wealth of knowledge and experience to every project he undertakes.
Manolo is also proficient in statistical programming languages such as R, SPSS, and Mplus, and has experience with Python and SQL. He is passionate about leveraging technology as an educational and training tool, and he continuously enhances his skills to stay at the forefront of his field.
He holds a B.A. and Licentiate degree in Psychology from Universidad del Valle de Guatemala and a M.A. in Psychology (Area: Developmental and Cognitive Processes) from York University.
Not a Member Yet?
It’s never too early to set yourself up for successful analysis with support and training from expert statisticians.
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.
