Introduction to the R Statistical Programming Language & Environment | Brown School at Washington University in St. Louis
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Introduction to the R Statistical Programming Language & Environment

 
Registration deadline: June 5th

This workshop will be conducted via a virtual Zoom meeting online format and Canvas. Access to a computer/laptop with internet access is required. Please contact Professional Development with any questions.

15 CEUs/CPH units - (5 live, 10 self-paced)

Todd Combs, PhD
Research Assistant Professor, Brown School

This course will introduce students to the fundamentals of the R language and RStudio environment. The course will begin with how to obtain and install R and RStudio, import data, create descriptive statistics, and plot simple graphics. Next, we will delve into data structures and classes, data manipulation and management, and common data analyses (t-tests, ANOVAs, correlations, regressions, etc.). During the final sessions, students will explore R's graphics capabilities and use some of the publishing tools built into RStudio in order to learn how to generate reproducible research.

Note: This class presupposes a working knowledge of statistics and previous experience working with a statistical software package. Students should have passed a basic statistics class and previous experience with SAS, SPSS, Stata, or otherwise using basic quantitative statistics skills within the last 5 years.

Workshop will consist of daily live Zoom webinars from 1:00 - 2:00 p.m. and pre-recorded course material in Canvas, including online help and individual consultations from 2:15 - 3:15 p.m., daily.

Class size is limited to 25.

$650 General admission
$450 Non-profit/government employees (1st Summer Institute class)
$400 Non-profit/government employees (Additional Summer Institute classes)

This class will include both degree-seeking graduate students and practicing professionals. Individuals registering through Professional Development will receive continuing education units - but not academic credit - for the class.

Recommended purchase of R Data for Science is optional; a free digital version of the text is available online. 
For more information on classwork and reading expectations, please click here.

Important Notice:  A recent Chrome update is causing some registrations completed with Chrome to post in our software with missing data. For the present, we recommend using an alternative browser (such as Firefox, Explorer, Edge or Safari). Chrome users may experience a delay with registration confirmations.

About the Instructor:

Todd Combs is a Research Assistant Professor at the Brown School, having for many years served as a data analyst with the School's Center for Public Health Systems Science.  His projects include ASPiRE (Advancing Science and Policy in the Retail Environment), which assesses retail tobacco policy activity in the US and Tobacco Town Minnesota, which uses agent-based modeling to test the potential impact of retail tobacco policies in Minnesota. Todd has consulted for various local non-profit organizations performing data analysis and program evaluation. He has also taught courses in transdisciplinary tobacco control approaches and quantitative analysis.  Todd holds a PhD in political science from the University of Missouri - St. Louis.

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