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Winter 2010 Short Courses
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Courses
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cancelled Disease Profiling: Mapping Disease Statistics cancelled |
Pre-registration and payment of fees is required for all Short Courses.
Please follow these links for details on:
REGISTRATION
Course Fees
Certificate of Completion
Statistical Consulting Service
Introduction to SAS for Windows
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Instructor:
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Hugh McCague, PhD |
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Dates:
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February 3, 10, 24 and March 3, 2010 (Wednesdays) |
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Time:
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1-4:30pm |
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Location:
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Room 203, Accolade West Building (ACW) |
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Enrolment Limit:
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35 |
This short course provides a basic introduction to the Statistical Analysis System (SAS).
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, importing, transforming and storing numeric and character data; and, a demonstration of how output can be changed with different options. In addition, some basic procedures in SAS will be introduced.
Sessions Three and Four will concentrate on SAS programming techniques to modify data, create charts and plots, and transform temporary datasets to permanent datasets. A demonstration of how to use SAS/INSIGHT and SAS/ANALYST will be presented, as well as a basic description of the general linear model. The course is designed for participants with some introductory level statistical knowledge, but no previous experience in using SAS.
Because this material is presented sequentially and builds upon the basics presented at the beginning of each day, course participants need to arrive on time and attend the entire session.
Introduction to SPSS for Windows
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Instructor:
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Lisa Fiksenbaum, MA |
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Dates:
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February 5, 12, 26 and March 5, 2010 (Fridays) |
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Time:
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9am-12:30pm |
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Location:
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Room 203, Accolade West Building (ACW) |
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Enrolment Limit:
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35 |
This course presents the basics of the Statistical Package for the Social Sciences (SPSS).
Session One will introduce the computing concepts of SPSS, the different facilities for reading data into an SPSS spreadsheet, and saving SPSS data files for future use. At the end of the first session, participants should be able to run simple programs, including some statistical procedures.
Sessions Two and Three will cover basic data modifications, transformations and other functions, including the uses of SPSS system files. More statistical procedures will also be introduced, with an emphasis on the use of graphical methods for examining univariate and bivariate relationships.
Session Four will cover Analysis of Variance and Least Squares Regression. As with previous sessions, graphical techniques will be demonstrated. Participants will benefit if they have a basic level of statistical knowledge up to general linear models, but the course is designed as an introduction to data analysis using the SPSS program and not as a statistics course.
Because this material is presented sequentially and builds upon the basics presented at the beginning of each day, course participants need to arrive on time and attend the entire session.
Visualizing Categorical Data with SAS and R
Professor Michael Friendly February 22, March 1, 8 and 15, 2010
(Mondays)2:30-6pm Room 159, Hebb Lab,
Behavioural Sciences Building (BSB)20 Statistical methods for categorical data, such as log-linear models and logistic regression, represent discrete analogs of the analysis of variance and regression methods for continuous response variables. This short course provides a brief introduction to statistical methods for analyzing discrete data and frequency data, together with some of the graphical methods which are useful for understanding patterns of association among categorical variables. Some of the topics include: methods for discrete frequency distributions; association plots for two-way tables; correspondence analysis; mosaic displays and friends; effects plots for log-linear models and logistic regression; diagnostic plots for model assumptions; and models for repeated measures.
These methods are illustrated in the lectures using SAS software based on Friendly (2000), Visualizing Categorical Data, and also with R software, using the vcd package that is based on that book. See http://www.math.yorku.ca/SCS/Courses/VCD/ for further course information. This course is designed for people with a basic statistical background and some interest in data visualization. A good working knowledge of the principles and practice of multiple regression, as well as elementary statistical inference, is assumed. Some previous experience with either SAS or R is helpful, though not essential.
Because this material is presented sequentially and builds upon the basics presented at the beginning of each day, course participants need to arrive on time and attend the entire session.
An Introduction to Statistical Learning and Data Mining
Professor Steven Wang March 12, 19 and 26, 2010
(Fridays)9:30am-12:30pm Room 1004,
Technology Enhanced Learning (TEL) Building30 Through automated statistical learning and data mining, businesses and scientific research can discover important hidden patterns. This course will offer a non-technical overview of statistical learning algorithms and data mining techniques. It will cover clustering, classification and machine learning algorithms. Applications to finance and biology will also be demonstrated. Prerequisite: An introductory course or knowledge of probability theory and statistics will be sufficient.
Because this material is presented sequentially and builds upon the basics presented at the beginning of each day, course participants need to arrive on time and attend the entire session.
Due to unforeseen circumstances,
this seminar has been cancelled.
Disease Profiling: Mapping Disease Statistics
Co-sponsored by the Faculty of Health, York University
This one-day seminar introduces both the history and methods by which mapping serves to "profile" the incidence of disease in communities, the nation, and the world. The seminar is divided into two parts. The morning session describes the history of medical mapping in relation to the statistical methods developed since the 1820s, in an attempt to understand diseases as environmental as well as clinical phenomena. The afternoon lectures include an introduction to computerized mapping software (ARCGIS) and its application to health and disease.
The goal of the workshop is to bring together a number of elements of disease studies: cartographic, clinical, geographic, graphic, political and social. Secondarily, it promotes computerized mapping as a natural medium for this multidisciplinary convergence. Third, it will encourage participants to think of health and disease events as spatial realities whose analysis is "geostatistical," to be rigorously analyzed using a spatial and temporal perspective.
- For York students, staff, and faculty, the fee is $40 per course.
- Full-time students at other post-secondary institutions may enrol for a fee of
$60 per course.
- For external participants, the fees per course are:
| Introduction to SAS for Windows | $240 |
| Introduction to SPSS for Windows | $240 |
| Visualizing Categorical Data with SAS and R | $240 |
| An Introduction to Statistical Learning and Data Mining | $180 |
Course fees must be paid at the time of registration.
See the registration form for payment options.
Refunds are available upon three business days' notice
prior to the course start date
and are subject to an administrative fee.
Please review our policy regarding refunds here.
Registration
- You can register for courses by completing the
on-line registration form.
- To register in person (weekdays, from 9am-Noon or 2-4pm),
please see:
Anita Valencia
Room 5075
Technology Enhanced Learning Building (TEL)
- To register by mail, print a blank registration form,
complete, and send to:
Anita Valencia
Institute for Social Research
Room 5075
Technology Enhanced Learning Building
York University
4700 Keele Street
Toronto, ON M3J 1P3
Canada
- You may also fax a completed registration form to: 416-736-5749
- For further information, please telephone 416-736-5061, weekdays, from 9am-Noon or 2-4pm
- Directions to York University (Keele Campus), information on parking and building locations click here.
For those coming to York from off campus, please allow plenty of time to find parking and the building and room where your course is taking place.
- Available on request, full attendance is required (participants need to sign the attendance sheet at every session).
- A $5.00 administrative fee applies, for each certificate requested.
Consultation is provided by a group of faculty drawn from York University's Departments of Sociology, Psychology, Geography, and Mathematics and Statistics, in conjunction with full-time professional staff at ISR. The faculty and staff have extensive experience with all forms of statistical analysis. Topics for which assistance is available include regression analysis, multivariate analysis, stochastic processes, probability theory, exploratory data analysis, scaling and cluster analysis, analysis of categorical data, structural equation modeling, survey data and longitudinal data, experimental design, survey sampling, and statistical computing.
Three times a year, the Statistical Consulting Service offers short courses on various aspects of statistics and statistical computing, including regular introductions to the SPSS and SAS statistical packages. Recent course offerings have included regression diagnostics, bootstrapping techniques, an introduction to the AMOS module in SPSS, graphical methods for categorical data, confirmatory factor analysis, model-based approaches to cluster analysis, introduction to the R programming language, and visual methods for statistical data analysis.
The Statistical Consulting Service maintains a regular schedule of office hours during the academic year. The Service primarily serves the York University community; for others, consultation is available on a fee-for-service basis.
Please go to the Institute's Web site at http://www.isr.yorku.ca/scs to make appointments online with SCS consultants.
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