Introduction to R

A Two-Day Workshop

Dr. Phillip Good

To arrange for the course to be held at or near your facility, contact courses@statisticsonline.info or 714/960-8070.

R has become the language of choice for ad-hoc work in statistics, for

  1. R supports vector arithmetic (Y = a +b*X)
  2. R is rich in built-in statistics and graphics functions
  3. R may be downloaded without charge from the Internet. 
  4. A worldwide community of users supports R.

In this two-day workshop, participants will attain sufficient mastery of the language to make use of R’s vector arithmetic capabilities as well as many of R’s built-in statistics and graphics functions.  They will learn how to expand R’s 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 instructor’s 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:

Day 1

Session 1. Calculation With R*

·        Vector Arithmetic

·        Descriptive Statistics

·        Getting Help

 

Session 2: Sampling

 

Session 3: Controlling Program Flow

·        Bootstrap

·        Permutation Tests

·        Mailing Lists

 

Session 4: Using R’s Full Capabilities

·        Saving and Retrieving Files

·        Modifying and Saving the Work Environment

·        Three Ways to Extend R’s Capabilities

 

 

Day 2

Session 5. Utilizing Graphic Options

·        Overlays

 

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 statisticsonline.info or 714/960-8070.