[R] Online Course: Graphics in R
Dr. Paul Murrell will offer his Graphics in R course online at statistics.com May 4 June 1. Participants can ask questions and exchange comments with Dr. Murrell via a private discussion board throughout the period. This course teaches you how to produce publication-quality statistical plots of data using R (a freely available open-source statistical language and environment). It will cover plots such as scatterplots, bar plots, histograms, boxplots and Trellis plots. It will review the underlying model used to produce plots in R so that you can extensively customize these plots. Finally, the course will introduce the grid graphics system and look at producing unique plots from the ground up using basic components. Dr. Murrell, the author of R Graphics, (CRC Press 2005) has been a member of the core development team for R since 1999, with a focus on the graphics system in R. He is the Editor-in-Chief of R News, the newsletter of the R project, and an Associate Editor for Computational Statistics. He is also Chair of the American Statistical Associations Statistical Graphics Section, and a Senior Lecturer in the Department of Statistics at the University of Auckland, New Zealand. The course lasts four weeks and consists of a series of four weekly lessons (directed readings and/or notes, plus exercises). Expect to spend about 10-15 hours per week; there are no set hours when you must be online. Details and registration: http://www.statistics.com/courses/graphicsR/ Peter Bruce [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] online course - Using R for Basic Statistics
Dr. John Verzani will present his online course, Using R for Introductory Statistics April 6 - May 4 at statistics.com. Participants can ask questions and exchange comments with Dr. Verzani via a private discussion board throughout the period. This course covers the use of R to summarize and graph data, calculate confidence intervals, test hypotheses, assess goodness-of-fit, and perform linear regression. John Verzani is a member of the faculty at the College of Staten Island of the City University of New York, and the author of Using R for Introductory Statistics (CRC Press), on which this course is based. His research interests and publications are in the area of superprocesses. There are no set hours when you must be online, and we estimate you will need about 10-15 hours per week. Register: http://www.statistics.com/content/courses/advanceddoe/ Peter Bruce [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] online course - Using R for Basic Statistics
oops! I gave the wrong link - the correct one is http://www.statistics.com/courses/Rstatistics/ pb Dr. John Verzani will present his online course, Using R for Introductory Statistics April 6 - May 4 at statistics.com. Participants can ask questions and exchange comments with Dr. Verzani via a private discussion board throughout the period. This course covers the use of R to summarize and graph data, calculate confidence intervals, test hypotheses, assess goodness-of-fit, and perform linear regression. John Verzani is a member of the faculty at the College of Staten Island of the City University of New York, and the author of Using R for Introductory Statistics (CRC Press), on which this course is based. His research interests and publications are in the area of superprocesses. There are no set hours when you must be online, and we estimate you will need about 10-15 hours per week. Peter Bruce [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
