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Wednesday 1 April 2015

Oregon State University (OSU) || Data Exploration and Visualization OSU

Oregon State University (OSU) || Data Exploration and Visualization OSU

Data Exploration and Visualization



Throughout your academic career, and most likely your professional career, you will be required to gather, analyze and share vast amounts of research data. Gathering data is usually the easy part. Making sense of that data, drawing valid conclusions and clearly presenting findings to your peers is the challenge. Whether you're an undergrad or a graduate student, a computer science, biology, physics or statistics major, you will benefit from knowing the concepts of manipulation, processing and exploration of quantitative data and programming.

These integrated, two-credit courses will introduce you to the R programming language, which is commonly used for scientific data analysis. And you will acquire the skills to critique and improve visualizations of statistical data as well as create them in R.
Data Programming in R

74315/74312 ST 499/599
Learn basic data types (e.g., integer, numeric, vectors, lists, matrices, data frames). Import/export data sets; manipulate and summarize them with efficient vectorized and boolean operations. Understand programming control flow, including loops, conditionals and especially, functions. Explore selected topics in functional programming and object orientation. Learn to write clear, reusable, and readable R code for your own projects
Topics in Data Visualization

74310/74311 ST 499/599
Learn the principles of graphical perception and the visual encoding of quantitative information. Learn how to use these principles to evaluate an effective visualization. Explore what makes graphical representations of data successful or unsuccessful and gain an appreciation of the different goals of visualization. Create and critique your own visualizations. Learn ggplot2 and dplyr.
Faculty

Shawn O'Neil
Shawn earned his Ph.D. in computer science at the University of Notre Dame, studying the algorithmic challenges of DNA sequencing from diverse individuals. He currently works at the Center for Genome Research and Biocomputing, facilitating bioinformatics education and research needs at OSU.

Charlotte Wickham
Charlotte earned her Ph.D. in statistics at the University of California, Berkeley. Her interests lie in spatiotemporal data, statistical graphics and computing, and environmental statistics. She is currently assistant professor of statistics at OSU.

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