Short Courses

Statistical Consulting Service (SCS) offers short courses on various aspects of statistics and statistical computing, including regular introductions to the SPSS and SAS statistical packages three times a year (Fall, Winter, and Summer). 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 SCS website to make appointments online with SCS consultants.

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

 

NEW! 2016 Spring Seminar Series on Research Methods (View PDF version of course listings)

List of Fall 2015 Courses offered

1) Introduction to Linear Multilevel Modeling

Instructor: Professor Jolynn Pek

Dates: Fridays – September 25, October 2 and 9, 2015  

Time: 9:30am – 12:30pm

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

Enrolment Limit: 20

Course Description: Data structures are often hierarchical in that cases are clustered into groups (e.g., students in classrooms or repeated measures of individuals) and where the usual assumption of independence of observations in classical techniques is violated. Multilevel models are designed to model such nested data structures allowing for within- and between-group effects which may be separately estimated.

This short course provides an introduction to the basic concepts of linear multilevel models. Topics include approaches to analyzing nested data structures, computing and interpreting the intra-class correlation, level 1 predictors, partitioning variance into within- and between-group components, level 2 predictors, cross-level interactions, ML and REML estimation, model assumptions, model diagnostics and modeling longitudinal data structures.

The short course assumes familiarity with multiple linear regression, and will involve both lectures and data examples using SAS. Familiarity with the SAS environment is recommended.

Because these materials are presented sequentially and build upon the basics presented at the beginning of each class, course participants need to arrive on time and attend the entire session.

2) An Introduction to SAS for Windows

Instructor: Ryan Barnhart, MA

Dates: Wednesdays – Oct. 7, 14, 21 and 28, 2015

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). Washrooms are available nearby outside the 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 the entire sessions.

3) An Applied Introduction to SPSS

Instructor: Alyssa Counsell, MA

Dates: Fridays – Oct. 9, 16, 23 and Nov. 6, 2015

Time: 9:00am – 12:30pm

Location: Steacie Instructional Lab, Room 021, Steacie Science Library

Enrolment Limit: 35

Course description:  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 the entire 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). Washrooms are available nearby outside the library.

4) Accessing Statistics Canada Data and Resources

Instructors: Sara Tumpane, MA
Walter Giesbrecht, MLIS
Hugh McCague, PhD

Date: Tuesdays – Oct. 13 and 20, 2015

Time: 1:00pm-3:30pm  

Location: Research Data Centre (RDC), Statistics Canada,
York Lanes 283B

Enrolment Limit: 20

Course description: This course introduces participants to the use of the extensive Statistics Canada data and statistics that are available through the public website and the secure Research Data Centre (RDC) at York University. York University community members have an exceptional research opportunity to access and analyse the broad-ranging and detailed confidential data (micro-data) from over 80 high-quality household and population surveys. In order to assist you in determining which surveys are relevant to your research, an overview of the Statistics Canada public use data and the secure RDC data will be given, including for example, the National Population Health Survey, the Survey of Labour and Income Dynamics, and the General Social Survey. The Short Course will cover the practical issues involved in searching for, accessing and handling Statistics Canada data, and important resources such as codebooks providing complete information on the data and variables. You are encouraged to bring a laptop and to work with the illustrative public use files and resources.

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.

5) Advanced Research Design Seminar

Instructor: Professor Bryn Greer-Wootten

Dates: Tuesdays – Oct. 13, 27, Nov. 10 and 24, 2015

Time: 6:00pm – 9:00pm

Location: Room 5082, Technology Enhanced Learning (TEL) Building

Enrolment Limit: 10

Course description: 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 October 5, 2015.

Because these materials are presented sequentially and build upon the basics presented at the beginning of each class, course participants need to arrive on time and attend the entire session.

6) Using Computers in Qualitative Analysis: NVivo 10 for Windows Workshop (Sorry, this course is full)

Instructor: Stella Park

Dates: Thursday, November 12 and Friday, November 13, 2015

Times: 9:30am-Noon; 1:00pm-3:30pm

Location: Room 2004, Technology Enhanced Learning (TEL) Building

Enrolment Limit: 20

Course Description: This hands-on workshop will provide both a basic and advanced introduction to NVivo 10 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 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.

Please note that this two-day Workshop comprises BOTH morning AND
afternoon sessions.

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.

Course Fees

All fees include HST.

For external participants, the lab access fee of $33.90 has been included.

For York students (with FAS account), the fees are:

Introduction to Linear Multilevel Modeling
$90.40
An Introduction to SAS for Windows
$90.40
An Applied Introduction to SPSS
$90.40
Accessing Statistics Canada Data and Resources
$56.50
Advanced Research Design Seminar
$90.40
An NVivo Workshop
$90.40

For York faculty and staff, the fees are:

Introduction to Linear Multilevel Modeling
$198.88
An Introduction to SAS for Windows
$198.88
An Applied Introduction to SPSS
$198.88
Accessing Statistics Canada Data and Resources
$56.50
Advanced Research Design Seminar
$198.88
An NVivo Workshop
$198.88

Full-time students at other post-secondary institutions,
the fees per course are:

Introduction to Linear Multilevel Modeling
$152.55
An Introduction to SAS for Windows
$192.10
An Applied Introduction to SPSS
$192.10
Accessing Statistics Canada Data and Resources
$90.40
Advanced Research Design Seminar
$158.20
An NVivo Workshop
$214.70

For external participants, the fees per course are:

Introduction to Linear Multilevel Modeling
$332.22
An Introduction to SAS for Windows
$431.66
An Applied Introduction to SPSS
$431.66
Accessing Statistics Canada Data and Resources
$90.40
Advanced Research Design Seminar
$397.76
An NVivo Workshop
$395.50

All participants, Certificate of Completion : $5.65 each

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.

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
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 applies, for each certificate requested.

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.

Alyssa Counsell is a third year doctoral candidate in the Quantitative Methods program in Psychology. Her research interests include equivalence testing, robust statistics, measurement invariance, structural equation modeling, and pedagogical methods for improving statistical knowledge in applied psychological research. She is currently an SCS TA with proficiency in both SPSS and R.

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.

Bryn Greer-Wootten is Professor Emeritus in Environmental Studies and 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.

Hugh McCague is the 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.

Stella Park joined ISR in 2014 as a Project Manager. She has over 10 years of experience in conducting both quantitative and qualitative research projects at the local, provincial, and international levels, on a diverse range of topics, including health, education, employment, and the non-profit sector. At ISR, she is currently managing YouthREX (qualitative) research project, CAMH’s Ontario Student Drug Use and Health Survey, CAMH’s Monitor Survey, and SSHRC-funded Second-generation Employment project.

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.

Sara Tumpane is the SC-appointed Analyst at the Statistics Canada Research Data Centre on the York University campus.  Sara is also a PhD Candidate in the Department of Economics at the university, with a research focus on quantitative research in health and environmental economics.

Additional Information

Any questions? Contact Information

Additional information regarding registration, contact Institute for Social Research (ISR) by telephone 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