Category: Statistical Analysis
Keywords: R language | General linear model | Visualization
Presentation Type: AMASS
Level of Familiarity: Basic to moderate level of familiarity with the material
This seminar will provide an introduction to the R language and statistical software. No prior exposure to R or other language-based statistical programs is required. Attendees are expected to have a firm understanding of the general linear model – correlation and regression, primarily.
This AMASS session will teach participants how load data into R, carry out basic data maintenance and visualization tasks (e.g. recoding data, creating histograms, etc.), and carry out basic analyses.
We will cover Pearson’s correlations, bivariate and multiple regression, and logistic and Poisson regression. Time depending, we will also cover exploratory factor analysis and linear mixed-effect regression (aka multilevel modeling or hierarchical linear modeling). Some discussion will be given to the vast array of analyses and techniques available to users once they become familiar with R, including network analysis, LASSO regression, and other topics.
Earn 4 continuing education credits
Recommended Reading: An R Companion to Applied Regression, 2nd Edition. Fox & Weisberg.
An Introduction to Statistical Learning, with Applications in R. James, Witten, Hastie, & Tibshirani.
University of California, Berkeley
Thursday, November 16
8:30 AM – 12:30 PM
Saturday, November 18
1:45 PM – 3:15 PM
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