Whether fresh out of school or a seasoned scientist, this year’s R workshop should have a training session that can help you take your science to the next level. We will have 13 micro-trainings talks that will help guide attendees through a range of topics from data exploration to non-linear regression. Each micro-training will include a 15-minute talk guiding attendees through a specific data analysis step or method followed by a short question and answer period. Each micro-training will also include an IEP-based dataset to analyze, an R script that attendees can use to replicate the presented analysis, and a document that is a companion text to the talk. The users can download these for future reference and to serve as a foundation for future analyses.
The first session, titled “Basic Statistics in R”, will include five micro-trainings to help guide the pre-analysis process and introduce users to several univariate and multivariate approaches to analyze categorical data. The second session, titled “Regression in R”, will have five micro-talks that introduce users to numerous regression approaches from simple linear regression to handling zero-inflated catch data. The final session, titled “Advanced Analytical Topics in R”, will cover mixed-effects regression and introduce users to regression in a Bayesian framework. We encourage attendees to stick around after the last talk for an open Q&A period.
Overall, we hope this workshop will provide tools that can help attendees promote to the next level, increase the impact of their next publication, or even just provide a baseline understanding of a suite of commonly used analytical approaches. We look forward to seeing you all at our micro-trainings on March 23, 2022.
- Overview: Workshop plan, a general modeling approach, and a framework for univariate analyses
- Instructor: Jereme Gaeta (IEP & CDFW)
- Data Exploration - recorded presentation
- Instructor: Catarina Pien (DWR)
- Categorical Predictors: ANOVA and Kruskal-Wallis with multiple comparison tests - recorded presentation
- Instructor: Emily Ryznar (DSC)
- Categorical Response: Classification Trees - recorded presentation
- Instructor: Trinh Nguyen (IEP, CDFW)
- Multivariate statistics: an introduction to ordination - recorded presentation
- Instructor: Timothy Malinich (CDFW)
- Simple linear regression - recorded presentation
- Instructor: Braden Elliot (SWRCB)
- Logistic regression - recorded presentation
- Instructor: Tyler Pilger (FishBio)
- Discrete catch data: Negative binomial regression - recorded presentation
- Instructor: Rosie Hartman (DWR)
- Zero-inflated negative binomial regression - recorded presentation
- Instructor: Rosie Hartman (DWR)
- Non-linear data: generalized additive models - recorded presentation
- Instructor: Jereme Gaeta (IEP & CDFW)
- Mixed effects/hierarchical models Part I: theory - recorded presentation
- Instructor: Jereme Gaeta (IEP & CDFW)
- Mixed effects/hierarchical models Part II: analyses - recorded presentation
- Instructor: Jereme Gaeta (IEP & CDFW)
- An introduction to regression in a Bayesian framework - recorded presentation
- Instructor: Sam Bashevkin (DSC)