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November Member Training: Preparing to Use (and Interpret) a Linear Regression Model

by TAF Support

You think a linear regression might be an appropriate statistical analysis for your data, but you’re not entirely sure. What should you check before running your model to find out?

In this webinar, Kim Love shows some descriptive statistics and graphics that you can produce before running a model to help with that decision.

She also discusses additional descriptive statistics and graphics that you should check before interpreting the results of a linear regression model (yes, checking model assumptions).

Techniques included in this training are univariate and bivariate descriptive statistics, histograms, normal QQ plots, and scatterplots, which will be applied to variables in the model as well as residuals and predicted values.


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

Kim is a workshop instructor for The Analysis Factor and owner/lead consultant at K.R. Love Quantitative Consulting and Collaboration.

She has worked as a statistical consultant and collaborator in multiple professional roles, most recently as the associate director of the University of Georgia Statistical Consulting Center.

Kim has more than a decade of professional and academic experience in the fields of regression and linear models, categorical data, generalized linear models, mixed effects models, nonlinear models, repeated measures, and experimental design. She has a B.A. in mathematics from the University of Virginia, and an M.S. and PhD in statistics from Virginia Tech.

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 and 85+ other stats trainings — plus the expert guidance you need to progress with live Q&A sessions and an ask-a-mentor forum.

Tagged With: Bivariate Statistics, histogram, interpreting regression coefficients, linear regression, Multiple Regression, scatterplot, Univariate statistics

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  • The General Linear Model, Analysis of Covariance, and How ANOVA and Linear Regression Really are the Same Model Wearing Different Clothes
  • Interpreting Lower Order Coefficients When the Model Contains an Interaction

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