York University students: $45.20 per course
York University faculty and staff: $99.44 per course
Other post-secondary full-time students: $90.40 per course
For external participants, the fees per course are:
|An Introduction to Meta-analysis
and Systematic Reviews ..................................
|Introduction to Data Analysis with R ..................
|An Applied Introduction to SPSS .......................
|An Introduction to SAS for Windows ..................
|Introduction to Linear Multilevel Modeling ............
|All participants: Certificate of Completion ............
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.
You can register for courses by completing the on-line registration form.
To register in person (weekdays, from 10:00am to Noon or
2:00pm to 4:00pm), please see:
Technology Enhanced Learning (TEL) Building
To register by mail, print a blank registration form, complete,
and send to:
Institute for Social Research
Technology Enhanced Learning Building
4700 Keele Street
Toronto, ON M3J 1P3
You may also fax a completed registration form to: 416-736-5749
Certificate of Completion
Available on request, full attendance is required.
A $5.65 administrative fee (including HST) applies,
for each certificate requested.
Additional information regarding registration:
please telephone 416-736-5061, weekdays,
from 10:00am to Noon or 2:00pm to 4:00pm
Directions to York University (Keele Campus), building and parking lot locations click here. For additional information on parking click here.
Ryan Barnhart is a PhD candidate in Psychology at York University with specialization in Quantitative Methods. His research interests and statistical work have focused on longitudinal data analysis using multilevel modeling and generalized linear multilevel modeling. This work has helped Mr. Barnhart develop a multi-platform approach to using statistical software, including SAS, STATA, R and SPSS.
Jolynn Pek is an Assistant Professor in the Department of Psychology at York University and an Associate Coordinator with the Statistical Consulting Service. She received her PhD in Quantitative Psychology from the University of North Carolina at Chapel Hill. Her research interests involve quantifying different aspects of uncertainty in results obtained from fitting latent variable models (e.g., factor analysis models, structural equation models, structural equation mixture models, multilevel models, and latent growth curve models) to data.
Michael Rotondi is an Assistant Professor of Biostatistics and Quantitative Methods in the School of Kinesiology and Health Science, and an Associate Coordinator with the Statistical Consulting Service. His research interests span a variety of biostatistical areas, and include the development of statistical methods to estimate power and sample size for meta-analysis and meta-regression models. He has also performed meta-analyses examining the impact of vitamin A supplementation on neonatal mortality, and the role of physical activity in the prevention and treatment of Alzheimer’s disease.
Matthew Sigal is a doctoral student in the Quantitative Methods area of Psychology. He is a member of Dr. Michael Friendly's lab and is particularly interested in methods of data visualization, multilevel and structural equation modeling, and alternative modeling strategies within the framework of survival analysis. He has been a Teaching Assistant for both undergraduate and graduate statistics courses, and taught an introductory statistics course in W2013.
Carrie Smith is a PhD candidate in Psychology at York University, specializing in Quantitative Methods. She received her MA in Psychology at York, and her BASc in Engineering at the University of Toronto. Her research interests include data visualization and developing robust methods of statistical analysis appropriate for behavioural science data.
Statistical Consulting Service (SCS)
The Institute for Social Research's Statistical Consulting Service provides consultation on a broad range of statistical problems and on the use of computers for statistical analysis. Its services extend beyond the social sciences to other disciplines that make use of statistics. Consultation is available to assist in research design, data collection, data analysis, statistical computing and the presentation of statistical material.
Consultation is provided by a group of faculty and graduate students drawn from York University's Departments of Sociology, Psychology, Geography, Mathematics and Statistics, and the School of Kinesiology and Health Science, in conjunction with full-time professional staff at ISR. The consultants have extensive experience with most 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, boot-strapping 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 www.isr.yorku.ca/scs to make appointments online with SCS consultants.