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

Fall 2014 Short Courses

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

Please follow these links for details on:

[Click here for Previous Courses]

Advanced Research Design Seminar
Instructor:
Professor Bryn Greer-Wootten
Dates:
Tuesdays - Oct. 7, 21, Nov. 4 and 18, 2014
Time:
6:00pm - 9:00pm
Location:

Room 5082
Technology Enhanced Learning (TEL) Building

Enrolment Limit:
10

Research design in the social, environmental and behavioural sciences today must consider the choices to be made between quantitative, qualitative and mixed (i.e., both quantitative and qualitative) methods. This short course is designed as a seminar to examine such choices. An introductory presentation distinguishes between these approaches from philosophical perspectives. Subsequent sessions discuss (i) the primary issues, based on assigned readings, (ii) critical reviews of participant-chosen research articles, and (iii) group critique of individual research proposals. Sufficient time between meetings is allowed for the work required for these activities.

Enrolment is limited to 10 in order to maximize the seminar setting. This short course is open to everyone, but the participant likely to gain most from the experience is a PhD candidate post-comprehensives or a junior faculty person. It may be necessary to select participants based on their applications: please be sure to enter your reasons for applying for this short course in the online Registration Form in the box marked "Additional Information".

Applicants will be notified of acceptance one week prior to the first seminar meeting, i.e., by September 30, 2014.

An Applied Introduction to SPSS
Instructor:
Yawen Xu, MA
Dates:
Wednesdays - Oct. 8, 15, 22 and 29, 2014
Time:
1:00pm - 4:30pm
Location:

Steacie Instructional Lab, Room 021
Steacie Science Library

Enrolment Limit:
35

This course aims to acquaint participants with IBM SPSS Statistics, a popular and respected program for analyzing data that is used across a range of disciplines. The curriculum has been recently revised to not only introduce the basic functions and features of the software (including data entry and manipulation), but also to demonstrate how to conduct a range of statistical analyses. Hands-on exercises will supplement the lecture material.

The curriculum for this course is designed to be an applied introduction to a statistical program; as such, familiarity with basic statistical procedures (e.g., t-tests, ANOVA, regression) is assumed. Further, participants are encouraged to bring a USB flash drive to store their work.

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 these materials are presented sequentially and build upon the basics presented at the beginning of each day, course participants need to arrive on time and attend all sessions.

Please note that food and drink are not allowed in Steacie Library and the Steacie Instructional Lab. The only exceptions are capped bottles of water (not juice/pop) and spill proof mugs (not cups of coffee).

Click here to download the SPSS course data in a zip file


An Introduction to SAS for Windows
Instructor:
Ryan Barnhart, MA
Dates:
Fridays - Oct. 10, 17, 24 and 31, 2014
Time:
9:00am - 12:30pm
Location:

Steacie Instructional Lab, Room 021
Steacie Science Library

Enrolment Limit:
35

This short course provides an introduction to the Statistical Analysis System (SAS) syntax commands and procedures. We will cover the basics of:

  • reading, transforming, sorting, merging and saving data files in some common formats;
  • selecting cases, and modifying and computing variables;
  • performing some basic statistical procedures and tests such as descriptive statistics, correlations, contingency tables, Chi-square tests, t-tests, ANOVA and linear regression;
  • creating bar charts and scatter plots;
  • composing simple macros for tailored procedures; and
  • saving output results and work in some common formats.

This course is designed for participants with some introductory level statistical knowledge, but no previous experience in using SAS. Please note that while this course will focus on the implementation of introductory statistics in SAS, it is not intended as a review of basic statistics. This short course will get you well underway 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 these materials are presented sequentially and build upon the basics presented at the beginning of each day, course participants need to arrive on time and attend all sessions.

Please note that food and drink are not allowed in Steacie Library and the Steacie Instructional Lab. The only exceptions are capped bottles of water (not juice/pop) and spill proof mugs (not cups of coffee).

Click here for the SAS course materials

Sorry, this course is full. Register for waiting list only.
Using Computers in Qualitative Analysis: An NVivo Workshop
Instructor:
Professor Pamela Grassau
Dates:
Thursday, Oct. 30 and Friday, Oct. 31, 2014
Times:
9:30am-Noon; 1:00pm-3:30pm
Location:

Room 2004
Technology Enhanced Learning (TEL) Building

Enrolment Limit:
25

This hands-on workshop will provide both a basic and advanced introduction to NVivo 10. As this workshop will focus on how to move forward into your analysis, participants are required to have had some prior experience and/or exposure to qualitative assumptions, theories and methods before attending this workshop. The overall objective of this workshop is to provide you with the tools to ensure that the theory and methods guiding your project remain central as you move into NVivo.

On Day One you will create a project and learn how to import and work with a wide range of qualitative data formats (e.g., interview transcripts, focus group transcripts, survey spreadsheets, etc.).

On Day Two you will learn how to organize and explore your material, use advanced queries, identify relationships, use models and charts to show patterns in your information and create reports. Time will be provided on both days of the training for participants to work with their own data.

Because these materials are presented sequentially and build upon the basics presented at the beginning of each day, participants need to arrive on time and attend both sessions.

The Concepts Behind Regression:
A Visual Approach to Learning Almost All About Regression
Instructor:
Professor Georges Monette
Dates:
Tuesdays - Nov. 4, 11, 18 and 25, 2014
Times:
6:00pm - 9:00pm
Location:

Room 1005
Technology Enhanced Learning (TEL) Building

Enrolment Limit:
25

Regression is one of the most widely-used statistical techniques. The basic ideas are not too difficult but when you apply regression to real problems you discover myriads of seemingly complex issues. Almost all of these issues are richly interconnected in a way that can be visualized and understood using simple geometric figures, sometimes dynamic figures in 3 dimensions in the "spaces" of regression.

We explore three spaces: 1) data space: the familiar space in which things like scatterplots live; 2) "beta" space: the space of parameters in which confidence intervals and confidence regions live; and 3) the more abstract “variable space” in which n observations on a variable are represented by a vector of length n.

Some of the concepts that will come to life include:

  • Simpson's Paradox, sign reversals and causality
  • variance inflation, collinearity and when is principal components a reasonable solution
  • strange and unexpected consequences of measurement error
  • univariate versus multivariate outliers and corresponding concepts of leverage and influence
  • mediation and moderation
  • the roles of partial residuals versus partial regression plots
  • multiple comparisons and multiparameter confidence coverage, suppression
  • types of data: experimental versus observational
  • types of inference: causal versus predictive.

Most of the graphics created in the course are programmed in R and you are encouraged to bring a laptop and to work with the R scripts. However understanding how the graphics are generated is not directly relevant to the course. The graphics are used primarily for conceptual visualization.

Because these materials are presented sequentially and build upon the basics presented at the beginning of each day, participants need to arrive on time and attend all sessions.

Course Fees (including HST)

York University students: $90.40 per course

York University faculty and staff: $198.88 per course

Other post-secondary full-time students: $158.20 per course

External participants: $397.76 per course

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 10:00am to 12:00pm or 2:00pm to 4:00pm), please see:

Betty Tai
Room 5075
Technology Enhanced Learning (TEL) Building

To register by mail, print a blank registration form, complete, and send to:

Betty Tai
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 (including HST) applies,
for each certificate requested.

Additional Information

Additional information regarding registration:
please telephone 416-736-5061, weekdays,
from 10:00am to 12:00pm or 2:00pm to 4:00pm

Maps and Directions

Directions to York University (Keele Campus), building and parking lot locations click here. For additional information on parking click here.

Instructors

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.

Pamela Grassau is a PhD candidate in the Factor-Inwentash Faculty of Social Work at the University of Toronto. She is a Research Manager with the Palliative Care, Education and Research Group at the Bruyère Research Institute in Ottawa. Pam’s research focuses on relational experiences of health and illness, particularly as families move into Palliative and End-of-Life Care. She has been offering qualitative software trainings for more than 10 years.

Bryn Greer-Wootten is a Professor Emeritus in Environmental Studies and Professor Emeritus of Geography at York University. In 2002 he joined the staff of the Statistical Consulting Service, where he is currently an Associate Coordinator, and in 2004 was appointed an Associate Director of ISR. He has taught and carried out quantitative and qualitative research, with a particular interest in survey research, especially for environmental and social policy.

Georges Monette is an Associate Professor of Mathematics and Statistics at York and an Associate Coordinator with the Statistical Consulting Service. He is interested in the geometric visualization of statistical concepts and in the modeling and analysis of hierarchical and longitudinal data. He has worked in a number of applied areas, including pay equity, the statistical analysis of salary structures, and patterns of cognitive and motor recovery after traumatic brain injury.

Yawen Xu is a PhD student in the Department of Mathematics and Statistics at York University. Prior to this, Yawen graduated from the Financial Engineering Program in the Schulich School of Business. Her main research interests are regression models, generalized linear models, longitudinal data analysis and numerical methods for Finance. Yawen is proficient in Splus/R, SAS, SPSS and Maple.

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, Geography, and Kinesiology, 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, research design more generally, 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, mixed models, and meta-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.

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