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Data visualization using R
June 3 @ 11:00 am - 3:00 pm$200
A 4-hour workshop taught by Mariola Moeyaert, Ph.D.Register
This is the fourth of four 4-hour workshops on the R statistical programming language. Sign up for the other workshops in the series using the links below:
The R statistical programming language and computing environment is a free, open-source package for statistical analysis. R has become the de-facto standard in statistics (see Muenchen, 2018; Suda, 2017) and is widely used in the social, health, physical, and computational sciences. Researchers transition to R because it is powerful, flexible, makes routine data analysis easy and has a large and rapidly growing community of users.
Data visualization is the quickest and most powerful technique to understand new and existing information. Exploratory data analysis (EDA) through visualizations marks the starting point of each data science project. The graphs produced during the EDA can inform which data analytic technique is best suitable. The data visualization can help communicating data science findings.
This workshop will guide you on how to think about good data visualization. Through a series of examples, you will learn how to use ggplot to make graphs piece by piece. The emphasis throughout is on acquiring a practical feel for, and good judgement about, the way ggplot can be used, from the simplest cases to sophisticated, highly customized data visualizations.
Participants are strongly encouraged to have the most recent version of R installed. Participants are also encouraged to download and install RStudio, a front-end for R that makes it easier to work with. RStudio will be used during the workshop. This software is free and available for Windows, Mac, and Linux platforms.
- To understand the basic principles behind effective data visualizations, and how they are implemented in R and ggplot
- Learn how to use ggplot to make graphs piece by piece
- Become confident and fluent using ggplot, in order to make, refine, and effectively present good data visualizations
By the end of this workshop, participants should be able to import data, manipulate data, and run statistical models. The workshop will facilitate the use of R, to a level that enables participants to employ the software in their own work. Participants will understand the fundamentals of how R “thinks” so that they can begin to use R independently.
Pricing and schedule
Time: Thursday, June 3, 11AM to 3PM (EST)
We offer $50 discounts for graduate students and $25 discounts for multiple workshop enrollments. Find out about our discounts here.
The main workshop material is scheduled for four hours. Time permitting, Dr. Moeyaert will answer questions about participants’ specific research projects. Participants can ask questions via chat, microphone, or telephone. In order to allow sufficient time for questions, the number of workshop participants is limited to 30.
Who should attend?
This workshop is designed for anyone to learn R. No prior knowledge of R is assumed. Participants should have a basic understanding of data management and fundamental bivariate and multivariate statistics (e.g., simple t-test, analysis of variance, correlation analysis, and multiple linear regression).
About the instructor
Dr. Mariola Moeyaert is an Associate Professor Statistics within the division of Educational Psychology and Methodology at UAlbany. She received her PhD in Educational Statistics from the Katholieke Universiteit Leuven (KU Leuven) in Belgium and worked as a Postdoctoral fellow at the Center of Advanced Study in Education at the City University of New York. Her major research interests and publications are in the field of multilevel analysis, meta-analysis and interrupted time series analysis. She is also interested in Bayesian statistics, bootstrapping, structural equation modeling, longitudinal data analysis, and international comparative research. She (co)authored about 47 international publications, in such journals as Psychological Methods, Multivariate Behavior Research, Journal of School Psychology, Behavior Research Methods, School Psychology Quarterly, etc., reporting about developments in research methodology (including several computing intensive Monte Carlo simulation studies) and about applications of statistical models on educational/medical data. Currently, she is involved as PI and Co-PI in research projects funded by the Institute of Education Sciences about methodological advancements in the field of multilevel meta-analysis. You can find more information about Dr. Mariola Moeyaert by following these two links (1) https://www.