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Introduction to Basic Statistics in R (Part 2)

February 18 @ 10:00 am - 12:00 pm

Registration link coming soon!
Description: This workshop explores basic, practical applied statistics using the R statistical programming language. On the first day we’ll focus on common procedures like assessing the distribution of your data and calculating differences between groups. In the second day we’ll focus on common linear models (linear regression, ANOVA, etc.) in R. We will also calculate the power of a simple study. This workshop is appropriate for learners with various data types, but will most emphasize continuous numerical data.
By the end of this 2-part workshop, learners should be able to:
  • Calculate sample summaries and estimate population parameters
  • Work with distributions: generate random numbers, calculate quantiles and p-values
  • Calculate confidence intervals
  • Bootstrap statistics
  • Compare data from two or more different groups
  • Estimate and interpret linear models
  • Identify common violations of regression assumptions
  • Power calculations

Prerequisites: Learners should be proficient at using R and have the latest versions of R, RStudio, and Zoom installed on their computers.

Instructor: Dr. Wesley Brooks is a research data scientist at DataLab. He holds a PhD in Statistics and an MS in Biostatistics from the University of Wisconsin-Madison, where he taught statistics as a lecturer before joining DataLab. He was a postdoc in the Ecostats lab at the University of New South Wales, Australia, studying point processes and ecological statistics. His interests span from statistical computing to spatial statistics, nonparametric regression, and multimodel inference.


February 18
10:00 am - 12:00 pm
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DataLab: Data Science and Informatics (DSI)