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 2019 Fall Seminar Courses

Registration is now closed for Fall 2019 Short Courses.

SCS SHORT COURSES, October-December 2019

An Introduction to R and the Tidyverse

Sorry, this course is full.

Instructor: Mark Adkins, MA
Course Dates:  Wednesdays, October 2, 9, 23 and 30, 2019
Course Time: 10:30 – 1:30pm
Course Location: 159 Behavioural Sciences Building (Hebb Computer Lab)
Enrolment Limit: 20
Enrolment Minimum: At least five (5) registrants are required in order to hold the course.

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. Much of this course will be structured around a collection of packages called the tidyverse (www.tidyverse.org), which contains all of the tools necessary to learn R more easily and quickly. 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.

Click here for course materials.

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

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.

About the Instructor:
Mark Adkins is a doctoral candidate in Quantitative Methods in the Psychology Department at York University and a TA in SCS. He has years of experience as a statistical/programming tutor and has the ability to help students master complicated material regardless of their stage in the learning process.

An Applied Introduction to SPSS

Instructor: Nataly Beribisky, MA
Course Dates: Fridays, October 4, 11, 25 and November 1, 2019
Course Time:
9:00 – 12:00pm
Course Location: 
159 Behavioural Sciences Building (Hebb Computer Lab)
Enrolment Limit: 20
Enrolment Minimum: At least five (5) registrants are required in order to hold the course.

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 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.

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

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

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.

About the Instructor:
Nataly Beribisky is a doctoral candidate in Quantitative Methods in the Department of Psychology at York University. Her research interests include the use of power analysis, equivalence testing and multiplicity control.

Advanced Research Design Seminar

Instructor: Professor Bryn Greer-Wootten
Dates: Tuesdays, October 8, 29, November 12 and 26, 2019
Times: 6:00pm-9:00pm
Location: Room 5082, Victor Phillip Dahdaleh Building (Formerly 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 1, 2019.

About the Instructor:
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, qualitative and mixed methods research, with a particular interest in survey research and survey data analysis problems, for over fifty years.

Moving Beyond NHST: A Primer on the 'New Statistics'

Instructor: Professor Rob Cribbie
Course Dates: Tuesdays, October 22, 29, and November 5, 2019
Course Time:
8:30 – 11:30 am
Course Location: 159 Behavioural Sciences Building (Hebb Computer Lab)
Enrolment Limit: 15
Enrolment Minimum: At least five (5) registrants are required in order to hold the course.

Course Description:  Null hypothesis significance testing (NHST) has been the dominant and, in many cases, the only data analytic approach adopted by behavioural science researchers for decades. The limitations of NHST are finally being acknowledged within the research community, however, and an abrupt shift in research practices is inevitable. This course provides an introduction to effect sizes, confidence intervals, Bayesian analysis, replication, meta-analysis, and other tools that have been dubbed the “New Statistics”.

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

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.

About the Instructor:
Rob Cribbie is a Professor in the Quantitative Methods area of the Department of Psychology at York University. He received his PhD in Quantitative Methods for Psychology from the University of Manitoba in 2001. He has worked with the Statistical Consulting Service at York University for over 17 years. His research interests centre around robust/alternative statistics, including equivalence testing. For more details see http://cribbie.info.yorku.ca.

Getting Ready for the Bayesian Tide?

This course is full.  Register for waiting list only.

Instructor: Professor Georges Monette
Course dates: Mondays, November 11, 18, 25 and December 2, 2019
Course Time: 2:00 – 5:00pm
Location: Classroom, Research Data Centre (RDC), Statistics Canada, York Lanes 283B
Enrolment Limit: 15
Enrolment Minimum: At least five (5) registrants are required in order to hold the course.

Course description:  Statistics is the science of uncertainty, but there is a great deal of uncertainty about the ‘right’ way to deal with uncertainty, especially with respect to how to make inferences. Traditional frequentist approaches to inference have dominated statistical analyses in applications to empirical research for more than 100 years, but Bayesian inference is gaining momentum in many fields.  The reasons for this increased interest range from philosophical ones with a growing awareness that a price is paid for the objectivity ascribed to frequentist inference, to pragmatic ones, since advances in computing have made Bayesian methods more tractable than frequentist methods for many types of complex analyses.

As an indication of the rising interest in Bayesian methods, three journals in Psychology have recently published Special Issues devoted to Bayesian methods.

The aim of this course is to review the foundations of statistical inference in order to put the apparent rivalry between frequentist and Bayesian methods in context, and to explore software and techniques to implement Bayesian analyses, both for simple problems such as the Analysis of Variance (ANOVA) and basic regression, as well as for more advanced methods for complex hierarchical/multilevel models.

Probability concepts in the course should be accessible to someone with a basic probability and statistics course. With the exception of some material in the later parts of the course, most of the statistical methods should be easily understood by someone familiar with regression.

We will learn to use two software environments for Bayesian inference: (i) JASP (https://jasp-stats.org) is a package that is easy to use to perform traditional analyses such as ANOVA and basic regression; and (ii) for more advanced work, we will use Stan, a ‘state-of-the-art’ platform for statistical modeling and high-performance statistical computation (https://mc-stan.org/).

Although the course will use many references to the research literature in Psychology, it should be easy to understand and useful for researchers in any social science area.

About the Instructor:
Georges Monette is an Associate Professor of Mathematics and Statistics at York and has been affiliated with the Statistical Consulting Service for over 30 years. He enjoys teaching statistical concepts in many settings, including York’s Summer Program in Data Analysis from 2000 to 2012 and the Inter-university Consortium for Political and Social Research (University of Michigan) summer courses at York University. He is interested in the geometric representation of statistical concepts and in the modelling 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.

Course Fees

All fees include HST.

York students (with FAS account)
  • Introduction to R & the Tidyverse … $122.04
  • An Applied Introduction to SPSS … $122.04
  • Advanced Research Design Seminar … $122.04
  • Moving Beyond NHST: A Primer on the ‘New Statistics’ … $91.53
  • Getting Ready for the Bayesian Tide … $122.04
York faculty and staff
  • Introduction to R & the Tidyverse … $271.20
  • An Applied Introduction to SPSS … $271.20
  • Advanced Research Design Seminar … $271.20
  • Moving Beyond NHST: A Primer on the ‘New Statistics’ … $203.40
  • Getting Ready for the Bayesian Tide … $271.20
Full-time students at other post-secondary institutions
  • Introduction to R & the Tidyverse … $212.44
  • An Applied Introduction to SPSS … $212.44
  • Advanced Research Design Seminar … $212.44
  • Moving Beyond NHST: A Primer on the ‘New Statistics’ … $159.33
  • Getting Ready for the Bayesian Tide … $246.34*

*  For non-York students, a Wi-Fi access fee of $33.90 (including HST) has been included.

External participants
  • Introduction to R & the Tidyverse … $497.20
  • An Applied Introduction to SPSS … $497.20
  • Advanced Research Design Seminar … $497.20
  • Moving Beyond NHST: A Primer on the ‘New Statistics’ … $372.90
  • Getting Ready for the Bayesian Tide … $531.10*

*  For external participants, a Wi-Fi access fee of $33.90 (including HST) has been included.

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.