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

- R supports vector arithmetic (Y = a +b*X)
- R is rich in built-in statistics and graphics functions
- R may be downloaded without charge from the Internet.
- 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.** ** ****C****ourse ****P****rogram**:

**Day 1**

**Session 1**. Calculation With
R*

· Vector Arithmetic

· Descriptive Statistics

· Getting Help

**Session 2**: Sampling

- Generating Artificial Data
- Drawing Random Samples
- Data Frames

**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

** **

** **

**Session 5. **Utilizing Graphic Options

- Labels and Legends
- Side-by-Side Plots

· Overlays

**Session 6:** Testing Hypotheses

- t-Test
- Linear Models

· 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*

- Passing Information to and from Functions
- Scaffolds
- Debugging

To arrange for the course to be held at or near your
facility, contact courses@statcourse.com
or 1-714/465-9732.