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ICPSR Summer Program Evening Workshop: Introduction to the R Programming Environment
August 16, 2016 @ 5:00 pm - 8:00 pm
An event every day that begins at 5:00pm, repeating until August 19, 2016
Introduction to R:
How to Use R for Data Management, Data Analysis, & Graphical Display
Dates and Time: August 15-19, 2016, 5-8 p.m.
Location: Mason/Angell Hall, University of Michigan, Ann Arbor, Michigan
Instructor: R. Joseph Waddington, University of Notre Dame
The “R” statistical software package has become widely used to conduct statistical analyses and produce graphical displays of data across the social, behavioral, health, and other sciences. R is an open-source, code-based program that combines the ability to easily conduct analyses with a convenient facility for programming. Through R’s comprehensive network (CRAN), there are thousands of “add-on” packages available for use with advanced quantitative analyses.
This course will introduce users to the R programming environment and its use as a data analysis package. Participants in the course will learn to use R for data management; conducting and interpreting descriptive analyses, basic hypothesis tests, and regression analyses; producing graphical displays; and other advanced topics as time permits.
The course will feature both a lecture and a lab component. During lecture, the instructor will demonstrate basic features and coding in R to manage data, conduct analyses, and produce graphical displays. During lab, the instructor will lead participants through guided examples with real social science data on topics and techniques that mirror the same ones covered in the day’s lecture. All data will be provided by the instructor.
Audience: Researchers, analysts, graduate students, and faculty who are seeking a brief and applied introduction to using R for quantitative data analysis in their own research or instruction.
Registration Fee: $600 (for U-M faculty, staff, students, and researchers)
ICPSR mailing address is:
Summer Program in Quantitative Methods of Social Research
P.O. Box 1248
Ann Arbor, MI 48106-1248
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