Registration is now closed for Fall 2017 Short Courses.  Courses will be offered again in the winter 2018 semester.

The Institute’s Statistical Consulting Service (SCS) offers short courses on various aspects of statistics and statistical computing, including regular introductions to commonly used statistical packages, three times a year (Fall, Winter and Spring). Recent course offerings have addressed factor analysis, structural equation modeling, graphical methods for categorical data, linear regression 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 SCS website to make appointments online with SCS consultants.

Pre-registration and payment of fees is required for all 2017 Fall Seminar Courses

SCS SHORT COURSES, October-November 2017

An Introduction to SAS for Windows

Instructor: Ryan Barnhart, MA
Teaching Assistant: Joo Ann Lee, MA
Dates:  Wednesdays, October 11, 18, 25 and November 1, 2017
Time: 1:00pm – 4:30pm
Location: Steacie Instructional Lab, Room 021, Steacie Science Library
Enrolment Limit: 35

Course Description:  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.

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).

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 the entire sessions.       

SAS course materials                                         

About the Instructors
Ryan Barnhart is a PhD candidate in Psychology at York University with the 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 Ryan to develop a multi-platform approach to using statistical software, including SAS, STATA, R and SPSS.

Joo Ann Lee is a doctoral candidate in Quantitative Methods in the Graduate Program in Psychology at York University. She is interested in issues concerning the combination of data from multiple sources or studies, data visualization, and measurement issues. A finalist in a ‘Big Data’ competition sponsored by SAS, she is proficient in both SAS and R for data analysis and visualization.

An Introduction to R

Instructor: Amanda Tian, MSc
Dates: Fridays, October 13, 20, November 3 and 10, 2017
Time:  9:00am– 12:30pm
Locations: Steacie Instructional Lab, Room 021, Steacie Science Library
Enrolment Limit: 35

Course Description:  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 course is a 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) carry out 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 that the Steacie Instructional Lab [Steacie 021] is accessed by entering Steacie Library and then proceeding to the basement of that Library.

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).

Because this material is presented sequentially and builds upon the basics presented at the beginning of each class, course participants need to arrive on time and attend the entire session.

R course materials

About the Instructor
Amanda Tian is a doctoral candidate in Statistics at Mathematics Department of York University. Her research interest is about discrete log-concave distribution MLE in higher dimensional space. She has been working as a Statistical Consulting TA since 2012, provided statistical consulting to internal/external clients about generalized linear models,
longitudinal data analysis, mixed models, and R.

Accessing Canadian and International Data and Statistics

Instructors: Walter Giesbrecht, MLIS, Valerie Preston, PhD and Hugh McCague, PhD
Dates: Tuesdays, October 17 and 24, 2017
Time: 9:00am-12:30pm.
Location: Classroom, Research Data Centre (RDC), Statistics Canada, York Lanes 283B
Enrolment Limit: 20

Enrolment Minimum: At least five registrants are required in order to hold the course.

Course Description: This course introduces you to the high quality data and statistics available through Canadian and international government statistical agencies, academic survey institutes, and as well as emerging Big Data sources. The course focuses on Statistics Canada data which provide a broad coverage of current and historical aspects of Canadian society. The Statistics Canada resources are accessible through a public website and a secure Research Data Centre (RDC) at York University that holds detailed confidential micro-data from over 80 household and population surveys and the census master files. In order to assist you in determining which data may be relevant to your research, the Statistics Canada public use data and secure RDC data will be reviewed. For example, the Census, the National Population Health Survey, the Survey of Labour and Income Dynamics, and various General Social Surveys will be discussed. Resources for accessing other Canadian and international data including Big Data sources will be introduced. The course will cover the practical issues involved in searching, accessing and handling data, and important resources such as codebooks that offer complete information about the data. You are encouraged to bring a laptop computer to work on the in-class exercises to access data in your subject area of interest.

About the Instructors
Valerie Preston is Professor of Geography at York University where she teaches urban social geography, Associate Director of the Institute for Social Research, and Academic Director of the Statistics Canada Research Data Centre at York University. She was also Director of the Institute for Social Research, York Director for CERIS – The Ontario Metropolis Centre and the Graduate Program Director in Geography. Her research examines gendered and racialized aspects of migration and settlement and their impacts on Canadian cities. Currently, she is the project director for “Migration and Resilience in Urban Canada,” a partnership funded by SSHRC to create and disseminate new knowledge about international migration and settlement trends in cities.

Walter Giesbrecht is the Data Librarian in the Scott Library at York University. He helps students, staff, and faculty to find the data and statistics sources they need for their research and assignments. Often such sources include reference to the Public Use Master Files, but sometimes involve referrals to the Research Data Centre at York. His research interests cover data and statistical literacy.

Hugh McCague is a Data Analyst and Statistical Consultant at the Institute for Social Research and Statistical Consulting Service at York University. His work and research concentrate on applications of statistics in health and environmental studies, including the use of data at the Statistics Canada Research Data Centre at York University, as well as the on-going public health surveys of the Institute. 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.

Using Computers in Qualitative Analysis: An NVivo 11 for Windows Workshop

Instructor: Marshia Akbar, PhD
Dates: Friday, November 3, 2017 and Monday, November 6, 2017
Time: 9:30am-Noon; 1:00pm-3:30pm
Location: Room 2004, Victor Phillip Dahdaleh Building
Enrolment Limit: 20

Course Description: This hands-on Workshop will provide both a basic and advanced introduction to NVivo 11 for Windows. 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 research assumptions, theories and methods before attending this Workshop. The overall objective 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 and use charts to show patterns in your information. Time will be provided on both days of the Workshop for participants to work with their own data.

Please note this course is designed for NVivo 11 for Windows users (and not NVivo for Mac users). NVivo for Mac has different features and cross platform limitations.

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

Because these materials are presented sequentially and build upon the basics presented at the beginning of each day, participants need to arrive on time, attend all sessions and must bring a USB key to save work.

About the Instructor
Marshia Akbar is a research coordinator at the Center of Excellence for Research on Migration and Settlement (CERIS) at York University. Her research interests have focused on the social and economic integration of immigrants in Canada. She received her doctorate degree in Geography from York University with specialization in qualitative research methods. Her expertise in NVivo 10 and 11 has helped her analyze qualitative data for her PhD dissertation, as well as for the on-going Toronto Second Generation project funded by SSHRC.

Introduction to Linear Regression Models

Instructor: Professor David Flora
Dates: Fridays, November 3, 10, 17, and 24, 2017
Time: 9:30am-11:30am
Location: Room 061, Behavioural Sciences Building (BSB)
Enrolment Limit: 15

Course Description: Linear regression is an essential tool for the analysis of quantitative data in the social sciences. Many of the most commonly used methods of data analysis can be expressed in terms of linear regression and regression also provides a basis for many advanced procedures. Beginning with the simple regression model for a single predictor variable, the key concepts of regression will be examined, including model specification and estimation, inference, and diagnostics. This material will be extended to multiple regression models for several predictors, addressing the incorporation of categorical predictors and interactions. Concepts will be illustrated with input and output from statistical software (R, SAS, and SPSS syntax).

Course participants will be expected to have prior knowledge of basic principles in statistics and data analysis.

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 the entire sessions.

About the Instructor
David Flora is an Associate Professor and Coordinator of the Quantitative Methods Area in the Department of Psychology at York University and Joint Coordinator of the Statistical Consulting Service. His research interests include longitudinal data analysis, psychometric analysis, factor analysis, and structural equation modeling.

Course Fees

All fees include HST.

York students (with FAS account)
  • An Introduction to SAS for Windows … $90.40
  • Introduction to R … $90.40
  • Accessing Canadian and International Data and Statistics … $56.50
  • An NVivo 11 for Windows Workshop … $101.70
  • Introduction to Linear Regression Models … $90.40
York faculty and staff
  • An Introduction to SAS for Windows … $198.88
  • Introduction to R … $198.88
  • Accessing Canadian and International Data and Statistics … $56.50
  • An NVivo 11 for Windows Workshop … $226.00
  • Introduction to Linear Regression Models … $198.88
Full-time students at other post-secondary institutions

For non-York students, a lab access fee of $40.00+HST = $45.20 has been included.

  • An Introduction to SAS for Windows … $203.40
  • Introduction to R … $203.40
  • Accessing Canadian and International Data and Statistics … $90.40
  • An NVivo 11 for Windows Workshop … $226.00
  • Introduction to Linear Regression Models … $158.20
External participants

For external participants, a lab access fee of $40.00+HST = $45.20 has been included.

  • An Introduction to SAS for Windows … $442.96
  • Introduction to R … $442.96
  • Accessing Canadian and International Data and Statistics … $90.40
  • An NVivo 11 for Windows Workshop … $431.66
  • Introduction to Linear Regression Models … $397.76

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.

Certificate of Completion

Available on request, full attendance is required.
A $5.65 administrative fee applies, for each certificate requested.

Registration

You can register for courses by completing the on-line registration form, which is date-stamped.

You can register in person (weekdays, from 10:00am to 12:00pm or 2:00pm to 4:00pm), please see:

Betty Tai
Room 5075
Victor Phillip Dahdaleh Building (DB)

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

Betty Tai
Institute for Social Research
Room 5075
Victor Phillip Dahdaleh Building (DB)

York University
4700 Keele Street
Toronto, ON M3J 1P3
Canada

You may also fax a completed registration form to: 416-736-5749.

Additional Information

Additional information regarding registration, contact Institute for Social Research (ISR) by telephone at 416-736-5061, weekdays, from 10:00am to 12:00pm or 2:00pm to 4:00pm

Directions to York University (Keele Campus), building and parking lot locations.

Additional information on parking.