institute for social research

York University  

Over 40 years of excellence in conducting applied and academic social research
York University
4700 Keele Street
Toronto, ON Canada
M3J 1P3

Telephone: 416-736-5061
Toll-free: 1-888-847-0148
Fax: 416-736-5749
E-mail: isrnews@yorku.ca

Winter 2011 SCS Short Courses

Courses
A Gentle Introduction to R  course full
An Introduction to SAS for Windows
An Introduction to SPSS for Windows
Longitudinal and Hierarchical Data Analysis with Mixed Models in R
Visualizing Categorical Data with SAS and R

Pre-registration and payment of fees is required for all Short Courses.

Please follow these links for details on:

Course Fees
Registration
Certificate of Completion
Statistical Consulting Service

[Click here for Previous Courses]

A Gentle Introduction to R       -- Sorry, this course is full --
Instructor: Professor Robert Cribbie
Dates: January 31, February 7 and 14, 2011 (Mondays)
Times: 9am-Noon
Locations:

Room 159 (Hebb Lab),
Behavioural Sciences Building (BSB)

Enrolment Limit: 20

R is an independent open source statistical software package that is of value for its wide-ranging pre-programmed statistical procedures and capacity for programming tailored statistical analyses. Also, R is invaluable for generating informative high-quality graphics. This short course is a gentle step-by-step hands-on introduction to R. No familiarity with R is assumed, but participants will need a basic working knowledge of statistics. Participants will learn how to: 1) install R on their computers; 2) enter, import, and manipulate data; and 3) do basic mathematical, statistical and graphical operations and procedures in R. Upon completion of this course, participants will be comfortable with, and able to do, basic statistical work in R. Additionally, they will be familiar with resources for follow-up help and learning about R.

Please note: This course is taught as a lecture-lab combination in the Psychology Department Hebb Lab, 159 Behavioural Science Building. You will need to have an active FAS login account for the Hebb Lab (all Psychology undergraduates, graduate students and faculty already have one) to carry out the lab components. A temporary FAS login account for the Hebb Lab for this course will be provided if you do not have one.

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 SAS for Windows
Instructor:
Hugh McCague, PhD
Date:
Feb. 2, 9, 16 and Mar. 2, 2011 (Wednesdays)
Time:
1-4:30pm
Location:

Steacie Instructional Lab, Room 021,
Steacie Science Library

Enrolment Limit:
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.

Please note that the Steacie Instructional Lab [Steacie 021] is accessed by entering Steacie Library and then proceeding to the basement of that Library.

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.

Click here to download the SAS course data

Click here for the SAS course assignments
and related materials


An Introduction to SPSS for Windows
Instructor:
Lisa Fiksenbaum, MA
Date:
Feb. 4, 11, 18 and Mar. 4, 2011 (Fridays)
Time:
9am-12:30pm
Location:

Steacie Instructional Lab, Room 021,
Steacie Science Library

Enrolment Limit:
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.

Please note that the Steacie Instructional Lab [Steacie 021] is accessed by entering Steacie Library and then proceeding to the basement of that Library.

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.

Click here to download the SPSS course data


Longitudinal and Hierarchical Data Analysis with Mixed Models in R
Instructor:
Professor Georges Monette
Date:
March 3, 10, 17 and 24, 2011 (Thursdays)
Time:
6-9pm
Location:

Room 306, Accolade West Building (ACW)

Enrolment Limit:
25

Mixed models provide a flexible approach for the analysis of data in which each subject is observed more than once, or in which subjects are clustered in groups like classes. Mixed models are easily extended to allow non-linear models and response variables that are not normally distributed.

This course will emphasize the visualization of the basic concepts in longitudinal and hierarchical data analysis to help participants develop a strong understanding of the strengths and limitations of these methods. The proposed list of topics includes: mixed models; clustered data; longitudinal data; extensions of mixed models; the structure of the linear mixed model: fixed effects, random effects, variance and covariance components; how mixed models are used to fit longitudinal data; contextual versus compositional effects, splines, and model building and diagnostics.

This short course assumes familiarity with linear regression as presented, for example, in John Fox, Applied Regression Analysis and Generalized Linear Models, Second Edition (Sage, 2008). Familiarity with the basics of R will also be an asset and participants are encouraged to install R and work through introductory tutorials to prepare for the course. Extensive examples will be given in the R programming environment.

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
Instructor:
Professor Michael Friendly
Date:
March 8, 15, 22 and 29, 2011 (Tuesdays)
Time:
2:30-6:30pm
Location:

Room 159 (Hebb Lab),
Behavioural Sciences Building (BSB)

Enrolment Limit:
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.

Please note: This course is taught as a lecture-lab combination in the Psychology Department Hebb Lab, 159 Behavioural Science Building. You will need to have an active FAS login account for the Hebb Lab (all Psychology undergraduates, graduate students and faculty already have one) to carry out the lab components. A temporary FAS login account for the Hebb Lab for this course will be provided if you do not have one.

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.

Course Fees

All fees include HST

For York University students, the fees are $45.20 per course.

For York University faculty and staff, the fees are $90.40 per course.

Full-time students at other post-secondary institutions may register for a fee of $79.10 per course.

For external participants, the fees per course are:

A Gentle Introduction to R ............................... $271.20
An Introduction to SAS for Windows .................. $361.60
An Introduction to SPSS for Windows................. $361.60
Longitudinal and Hierarchical Data Analysis
with Mixed Models in R.....................................
$361.60
Visualizing Categorical Data with SAS and R ......... $361.60

All participants: Certificate of Completion............ $5.65 each

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 9:00am to 12:00pm or 2:00pm to 4:00pm), please see:

Anita Valencia
Room 5075
Technology Enhanced Learning (TEL) Building

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

Certificate of Completion

Available on request, full attendance is required.

A $5.65 administrative fee applies, for each certificate requested.

Additional Information

Additional information regarding registration:
please telephone 416-736-5061, weekdays,
from 9:00am to 12:00pm 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.

Instructors

Professor Robert Cribbie is an Associate Professor in the Department of Psychology at York University. He received his PhD in Quantitative Psychology from the University of Manitoba. His research interests include multiple comparison procedures, robust ANOVA strategies, and structural equation modeling.

Lisa Fiksenbaum is a doctoral candidate in Social/Personality Psychology at York University. She also received her BA and MA from York. Her training and experience in statistics includes a Teaching Assistantship for the Honours Thesis course (Psych 4170) and she has been involved in several research projects, both at the University and in the private sector. Her research interests include organizational issues, work-family relationships, stress and coping. Ms. Fiksenbaum is proficient in SPSS, and regularly consults with graduate and undergraduate students for SCS.

Professor Michael Friendly received his doctorate in Psychology from Princeton University, specializing in Psychometrics and Cognitive Psychology. He is a Professor of Psychology at York and an Associate Coordinator with the Statistical Consulting Service. Professor Friendly has broad experience in data analysis, statistics and computer applications. He is the author of SAS for Statistical Graphics, 1st Edition and Visualizing Categorical Data, both published by the SAS Institute, and an Associate Editor of the Journal of Computational and Graphical Statistics. His recent work includes the further development of graphical methods for categorical data.

Hugh McCague completed a BMath (Honours) in Statistics at the University of Waterloo, and an MA in Statistics and a PhD in Environmental Studies both at York University. He has worked as a statistician in both private and public sectors. He is a Data Analyst at the Institute for Social Research, and a consultant and instructor in ISR’s Statistical Consulting Service. His research and publications have concentrated on applications of mathematics and statistics in the history of art and architecture. He is the Secretary of the Southern Ontario Regional Association of the Statistical Society of Canada and the Southern Ontario Chapter of the American Statistical Association.

Georges Monette is an Associate Professor of Mathematics and Statistics at York and an Associate Coordinator with the Statistical Consulting Service. Most of his research has been in the mathematical foundations of statistical inference. His recent interests are the geometric visualization of statistical concepts and the modeling and analysis of longitudinal data. He has worked in a number of applied areas, including pay equity and the statistical analysis of salary structures. He received his PhD in Statistics from the University of Toronto.

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 drawn from York University's Departments of Psychology, Mathematics and Statistics, and Geography in conjunction with full-time professional staff at ISR. The faculty and staff have extensive experience with many forms of statistical analysis. Topics for which assistance is available include regression analysis, multivariate analysis, analysis of categorical data, structural equation modeling, factor analysis, multilevel/mixed 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 addressed factor analysis, structural equation modeling, graphical methods for categorical data, introduction to the R programming language, and mixed models.

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.

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