- Introduction to SAS for Windows
- Data Analysis and Statistical Graphics Using 'S'
- Introduction to SPSS for Windows
- Graphical Methods for Categorical Data

- Instructor:
- Peggy Ng
- Dates:
- Windows Pre-session: October 3 Basics: October 17, 24 Intermediate Topics: October 31, November 7
- Time:
- MONDAYS 10:00 a.m. - 1:00 p.m.
- Location:
- Room T107 Steacie Science Library
- Enrolment Limit:
- 30

The course consists of three parts, which may be taken individually or as a whole:

**I Windows Pre-session:** The pre-session is intended to make the
SAS sessions accessible to those without previous experience with
Windows on personal computers. Only the bare essentials of
Windows will be covered; those familiar with Windows need not
attend.

**II Basic Introduction**: Sessions One and Two provide an overview
of SAS and its underlying logic; an explanation of the use of the
Display Manager System to run a SAS job; an introduction to the
SAS Data step for reading, transforming, and storing data; and a
demonstration of how statistical analyses may be performed in SAS
Proc (procedure) steps.

**III Intermediate Topics**: Sessions Three and Four will concentrate
on SAS programming techniques to modify data and enhance SAS
output. As well, more statistical procedures will be introduced.

- Instructor:
- Professor Claudia Czado
- Dates:
- October 6, 13, 20, 27
- Time:
- THURSDAYS 4:30 - 7:30 p.m.
- Location:
- Room S701 Ross Building
- Enrolment Limit:
- 15

The purpose of this course is to show how to use S in a Unix environment. The course will have both lecture and hands-on components. Participants will receive access to an account for running S+. The four sessions of the course will cover approximately the following material:

**I The Unix Environment:** Logging in, mail, editing with vi,
directory structure, basic file manipulation and introduction to
the X-Window environment.

**II Basic Use of S**: Data input, manipulating data, printing,
history mechanism, S arrays and data frames, random number
generation, arithmetic operators; functions for manipulating
data structures: apply and category; help facilities.

**III Programming and Graphics in S**: Writing S functions, one-
and two-dimensional graphs, interactive graphs.

**IV Introduction to the Use of Statistical Functions in S**:
Regression and regression diagnostics based on the linear-model
function, lm().

An Introduction to S and S-Plus by Phil Spector (Duxbury Press, 1994, 286 pages, ISBN 0-534-19866-X, $35.95) is a recommended text and it is available from the York University Bookstore.

- Instructor:
- Mirka Ondrack
- Dates:
- Windows Pre-session: November 2 Basics: November 9, 16 Intermediate Topics: November 23, 30, December 7
- Time:
- WEDNESDAYS 1:00 a.m. - 4:30 p.m.
- Location:
- Room T107 Steacie Science Library
- Enrolment Limit:
- 30

This course consists of three parts, which may be taken individually or as a whole:

**I Windows Pre-session**: The pre-session is intended to make the
SPSS sessions accessible to those without previous experience
with Windows on personal computers. Only the bare essentials
of Microsoft Windows will be covered.

**II Basic Introduction:** Session One is an elementary
introduction to statistical computer programs, computing
concepts, and the essentials of SPSS. At the end of the first
session, participants should be able to run very simple
programs, including some basic descriptive statistical
procedures. Session Two will cover first-session topics in greater
detail, concentrating on data definition facilities and various
ways of formatting data.

**III Intermediate Topics**: Sessions Three and Four will
introduce data modification, transformations, and functions.
Session Five will cover the use of SPSS system files.

- Instructor:
- Professor Michael Friendly
- Dates:
- November 9, 16 WEDNESDAYS 1:30 - 4:30 p.m. Room 202 ASB
- Enrolment Limit:
- 30

While graphical display techniques are common adjuncts to analysis of variance and regression, methods for plotting contingency table data are not as widely used. Moreover, while statistical methods can be used to determine which variables are related, the numerical summaries and parameter estimates do not provide easy ways to show how those variables are related.

This workshop provides a brief introduction to graphical methods which are useful for understanding the pattern of association among categorical variables. These methods can be helpful for both data exploration and for communicating results to others. Some of the methods described include:

- methods for discrete frequency distribution,
- association plots for two-way tables,
- mosaic displays,
- effects plots for log-linear models and logistic regression, and
- correspondence analysis.