R has become the language of choice for ad-hoc work in statistics, for
In this two-day workshop, participants will attain sufficient mastery of the language to make use of Rís vector arithmetic capabilities as well as many of Rís built-in statistics and graphics functions.† They will learn how to expand Rís capabilities by downloading function libraries and developing their own programs.† Topics include vector arithmetic, descriptive statistics, graphics, saving and retrieving files, generating artificial data, drawing random samples, testing hypotheses, survival analysis, and model building
Structure of the Course: R commands are introduced in stages, employing first default values and gradually introducing options.† Each segment includes real-world examples, board demonstrations, and graded exercises.† Each participant should be provided with a computer during the course so they may work through the exercises.† Questions are encouraged both orally (during lectures) and written (during breaks).
Materials:† Participants are encouraged to bring in and make use of existing data files in Excel, MatLab, MiniTab, SAS, or SPSS format.† For use on the second day of the course, participants are encouraged to bring a disk (floppy or CD) containing data for building a model.† Optional is the instructorís Introduction to Statistics via Resampling Methods and R, Wiley, NY 2005.
Instructor: Phillip Good obtained his A.B. and Ph.D. in mathematical statistics from the University of California at Berkeley.†† He has lectured in Australia, Belgium, France, Holland, Ireland, and Spain, and served as Traveling Lecturer for the American Statistical Association.† The present course is based on his text Introduction to Statistics via Resampling Methods and R, Wiley, NY 2005.†† Five other statistical texts of his are in print, four of which are in their second or third editions.
Warning: The course is structured so that each session requires knowledge of the material provided in previous sessions. The schedule for the final session of the workshop is tentative and may be devoted entirely to resolving issues raised in earlier sessions.
Introduction to R.† †Course Program:
Session 1. Calculation With R*
∑ Vector Arithmetic
∑ Descriptive Statistics
∑ Getting Help
Session 2: Sampling
Session 3: Controlling Program Flow
∑ Permutation Tests
∑ Mailing Lists
Session 4: Using Rís Full Capabilities
∑ Saving and Retrieving Files
∑ Modifying and Saving the Work Environment
∑ Three Ways to Extend Rís Capabilities
Session 5. Utilizing Graphic Options
Session 6: Testing Hypotheses
∑ Analysis of Variance
∑ Alternative Modeling Methods
Session 7: Downloading/Using Function Libraries
∑ Quantile Regression
∑ Building Your Own Functions
∑ Fitting Censored Lifedata
∑ Better Bootstraps
Session 8: Developing Your Own Programs*
To arrange for the course to be held at or near your facility, contact firstname.lastname@example.org or 1-714/465-9732.