Institute for Social Research

Fall 2012 Short Courses

Courses

An Applied Introduction to SPSS

~~An Introduction to SAS for Windows~~ course full

Advanced Research Design Seminar

An Introduction to Structural Equation Modeling

A Gentle Introduction to 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]

An Applied Introduction to SPSS
Instructor:	Matthew Sigal, MA
Date:	Wednesdays - Oct. 3, 10, 17, 24, 2012
Time:	1-4:30pm
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. 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. Click here to download the SPSS course data in a zip file

An Introduction to SAS for Windows -- Sorry, this course is full --
Instructor:	Ryan Barnhart, MA
Date:	Fridays - Oct. 5, 12, 19, 26, 2012
Time:	9am-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. 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. Click here for the SAS course materials

Advanced Research Design Seminar
Instructor:	Professor Bryn Greer-Wootten
Date:	Tuesdays - Oct. 9, 23, Nov. 6, 20, 2012
Time:	6-9pm
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 approaches. 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, 2012.

An Introduction to Structural Equation Modeling
Instructors:	Professor Robert Cribbie
Dates:	Thursdays - November 8, 15, 22 and 29, 2012
Times:	12-2:30pm
Locations:	Room 159 (Hebb Lab), Behavioural Sciences Building (BSB)
Enrolment Limit:	20
This course will provide a general introduction to the methods of structural equation modeling (SEM), including a discussion of developing models, evaluating the fit of models to data, evaluating the significance of model parameters and performing model modification. The primary objectives of this short course will be to provide: a) the ability to recognize situations where these techniques may be useful in research; b) an appreciation for the roles of sound theory in making these techniques useful; c) an understanding of the limitations of these methods; and d) the ability to use available software for analyzing data. Please note: This course is taught as a lecture-lab combination in the Psychology Department Hebb Lab, 159 Behavioural Sciences 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 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.

A Gentle Introduction R
Instructor:	Carrie Smith, MA
Date:	Mondays - Nov. 5, 12, 19 and 26, 2012
Time:	12:30-4:30pm
Location:	Room 159, Hebb Lab, Behavioural Science 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) 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: This course is taught as a lecture-lab combination in the Psychology Department Hebb Lab, 159 Behavioural Sciences 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 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.

Course Fees (including HST)

York University students: $45.20 per course

York University faculty and staff: $90.40 per course

Other post-secondary full-time students: $90.40 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 9:00am 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 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

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.

Professor Robert Cribbie is a Professor in the Department of Psychology at York University and the Joint Coordinator with Professor David Flora of the Institute for Social Research’s Statistical Consulting Service. He received his PhD in Quantitative Psychology from the University of Manitoba. His research interests include multiple comparison procedures, robust ANOVA strategies, and equivalence testing.

Professor Bryn Greer-Wootten is Professor Emeritus in Environmental Studies and Professor Emeritus of Geography at York University. In 2002 he joined the staff in 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.

Matthew Sigal is a doctoral student in the Quantitative Methods area in Psychology. He is a member of Dr. Michael Friendly's lab and is particularly interested in methods of data visualization, multilevel and structural equation modeling, and alternative modeling strategies within the framework of survival analysis. He has been a Teaching Assistant for both undergraduate and graduate statistics courses, and will be teaching an introductory statistics course this winter.

Carrie Smith is a PhD Candidate in Psychology at York University specializing in Quantitative Methods. She received her MA in Psychology at York, and BASc in Engineering at the University of Toronto. Her research interests include data visualization and developing robust methods of statistical analysis appropriate for behavioural science data. She has been using R for statistical computing in her research and consulting for several years.

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 Sociology, Psychology, Geography, and Mathematics and Statistics, in conjunction with full-time professional staff at ISR. The faculty and staff have extensive experience with all forms of statistical analysis. Topics for which assistance is available include regression analysis, multivariate analysis, stochastic processes, probability theory, exploratory data analysis, scaling and cluster analysis, analysis of categorical data, structural equation 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 included regression diagnostics, boot-strapping techniques, an introduction to the AMOS module in SPSS, graphical methods for categorical data, confirmatory factor analysis, model-based approaches to cluster analysis, introduction to the R programming language, and visual methods for statistical data 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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