York University
GS/PPAL 6200 Sections M & N
Research Methods & Information Systems
Winter Term 2012
Class M: Weds. 19:00 Osgoode Professional Development Centre
Class N: Tues. 19:00 Room 216 McLaughlin College Bldg. Keele Campus
Please Note: This course outline is being provided in advance of class to help you plan your term.
Additional material that will assist you and which you will be required to familiarize yourself with in
order to complete the assignments and other components of the course will be provided throughout
the term via the instructor’s website (see below) and websites linked from the page the instructor will
create for these two classes. More will be said about this in the first class.
Course Director:
Office:
Email:
Website:
Office Hours:
Daniel Cohn, Ph.D
122 McLaughlin College
dcohn@yorku.ca
http://www.yorku.ca/dcohn
Weds. @ OPD 18:00 – 19:00 Tues. 17:30 – 18:30 @122
McLaughlin
Course Description: This course is the first of a two-course sequence in research methods in the
MPPAL Program. There are no formal prerequisites, but prior knowledge of elementary Algebra is
assumed. The broad goals of the course are:
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To enhance your appreciation of the benefits and limitations of quantitative research;
To prepare you for more advanced or specialized topics, and specifically, the subsequent
MPPAL course: Program Evaluation;
To enable you to critically read published or unpublished papers and reports that use
quantitative methods;
To provide you with basic statistical and computer skills that will help you to prepare your
own papers/reports using quantitative methods.
To achieve these goals, the course material will cover various aspects of information collection and
management, data description, and data analysis.
The information collection and management component includes use of data archives, research
design, survey design and ethics both for researchers and those charged with protecting privacy and
providing the public access to information. The data description and data analysis components
consist mostly of applied statistics, designed to develop skills in three broad areas:
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Knowledge of which statistics and/or graphs are appropriate under various conditions,
Knowledge of how to access canned computer programs that compute statistics and/or
prepare graphs, and
Knowledge of how to interpret the graphs, or the computed statistics.
Virtually all of the material used including the required readings, will be on a course web site
accessible to students enrolled in the course. A printed version is also provided.
The on-line course-related materials provided by the publisher are extensive, multidisciplinary, and
easy to use. They include an unusually large number of practice problems, both theoretical and data
based, as well as integrated statistical software that allows quick and easy computation of statistics
without going outside the course web-site. Significantly, a number of different kinds of statistical
software packages are included; in the case of most examples offered, the identical data could be
analyzed using any of a number of different software packages, from the ubiquitous and relatively
straightforward Excel, to the very sophisticated SPSS.
The lecture sessions dealing with statistics will usually be devoted largely to:
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A description of a hypothetical situation in which statistics or graphic techniques are useful to
describe or analyze data;
A description of statistics or graphs that could be used in that situation;
A generalization of that specific problem – a discussion of the circumstances under which
those statistics/graphs are appropriate;
An explanation of how to interpret those statistics/graphs;
A description of one or more other examples of their use.
In some instances, the lecture may also illustrate the use of one or more of the software packages to
compute the statistic (or generate the graph) being considered during that class session. However,
most of this work is quite straightforward, is very well described in the text, and will be left for
students to do on their own outside of class. As well, technical assistance will be provided during
office hours.
Student Responsibilities:
1. It is important that you attend class regularly, for a number of reasons. First of all, attendance, as
evidence of effort in learning the material, may directly affect your final grade. Secondly, you are
responsible for learning all of the substantive material presented. I post the slides that I present
during class on the course website. However, reviewing those slides is generally not enough to fully
understand the lecture. You should try to get a classmates notes that further elaborate on the slides.
Generally, I will not have enough time during my office hours to review all of the material covered
during a lecture. Having said that, I recognize that everyone has very busy lives and there are times
when miss class is unavoidable. Still, as per the policy of the MPPAL program ATTENDANCE
IS REQUIRED and deductions to your mark of up 20% may be made if you are absent without
suitable explanation from three or more classes. Pressing commitments at work represent a
suitable explanation for missing a class or two but not three or more.
2. It is of utmost importance that you read the assigned material before the relevant lecture. The
lectures will be presented based on the assumption that you have completed the reading assignment
for that date. Reading the material on schedule will not only help you to understand the lecture, but
also give you an opportunity to use the lecture to ask questions about material that you find difficult.
The subject matter in this course, more than in most other courses, requires you to keep up with the
readings, since the material almost always builds on what has been covered previously. Falling
behind is likely to make your task much, much more difficult.
3. As noted earlier, the required text has many sample problems and exercises at the ends of chapters.
Each week, you should do some of the exercises pertinent to the assigned reading. This is an essential
part of the course. Practice quizzes are available after most chapters in the text. You will receive
10% of your mark for completing them.
4. You should ask questions whenever you have trouble understanding the material. Time permitting,
questions asked during lectures will be answered then; otherwise an answer will be posted on the
website, or covered during the next lecture. I am committed to helping you learn, but I may not be
aware that you’re having difficulty unless you communicate that to me. If you want to meet with me
to discuss anything pertaining to the course, email me or call me at home to try to arrange a mutually
convenient time.
5. There is a lot of material to cover, some of it difficult. Our success depends on creating an
atmosphere conducive to learning. This is a responsibility we share. Please feel free to provide me
with feedback, preferably on a one-to-one basis, on any aspect of the course.
Grading:
Assignment
Due Date
Marks
Practice Quizzes
Most Weeks
10
Assignment 1
In Class Week of Feb 7 - 8
25
Assignment 2
In Class Wee of Feb 28 - 29
25
Assignment 3
One Week After Final Class April 3 - 4
25
Final Exam
Last Class of Term March 28 - 29
15
Total:
100
Please Note: As per above, a deduction of up to 20% may be made if a student fails to attend
three or more classes without suitable explanations.
Academic Honesty and Integrity:
Collaboration among students in learning is encouraged. However, copying any part of someone
else’s work, or allowing a student to copy yours, is cheating. Similarly, telling someone how to do an
assignment, or being told specifically how to do it, will be regarded as cheating. If you are uncertain
about the distinction between helping and cheating, please talk to me about this. These restrictions
are intended primarily to ensure that everyone learns as much as possible; please don't deny yourself,
or a fellow student, the opportunity to do so. Having said that, I should also point out that the
University seriously frowns on academic dishonesty. If you are caught either cheating or helping
someone else to cheat the penalties can be quite severe. All students ought to familiarize
themselves with the regulations on this matter. They can be found in the Faculty of Graduate Studies
Calendar and also on the FGS website:
http://www.yorku.ca/grads/current_students/faculty_regulations.php?id=8
Self-help Diagnostics:
Self-help diagnostic tests are available on-line. Both pre-tests and post-tests are available. A number
of such tests will be identified as “required.” Students who complete all of the pretests assigned, and
successfully complete a specified proportion of them, will receive a perfect score on this component
of the final grade.
Required Text:
The Basic Practice of Statistics (5th ed.), David S. Moore. New York: W. H. Freeman and Company.
Other required material will be available electronically.
Weekly Topics and Readings:
DATE
Introduction
Week 1
Jan 3-4
TOPICS
READINGS
Course planning: Intro to
online tools that will be used
in the course
No Reading
Information Collection & Management I
Week 2 Jan 10-11
Protecting Privacy and
Freedom of Information
RSO 1990 Chapter F.31 Freedom of
Information and Protection of Privacy Act
http://www.elaws.gov.on.ca/html/statutes/english/elaws_s
tatutes_90f31_e.htm
Ann Cavoukian (2010) The Seven
Foundational Principles, Implementation and
Mapping of Fair Information Practices,
Toronto: Office of the Information and
Privacy Commissioner of Ontario.
http://www.ipc.on.ca/images/Resources/pbdimplement-7found-principles.pdf
Canadian Internet Policy and Public Interest
Clinic (2006) On the Data Trail: How
Information about You gets into the hands of
Organizations with whom You have No
Relationship. A Report on the Canadian
Data Brokerage Industry
http://www.cippic.ca/sites/default/files/May1
-06/DatabrokerReport.pdf
Measurement and Data Description
Week 3
Measurement; Univariate
Jan 17 - 18
description Central
Tendency; Dispersion
Normal distribution
Ch 1, 2, 3
Week 4
Jan 24 - 25
Bivariate description
Ch. 4, 5
Relating 2 interval variables;
correlation and regression
Week 5
Jan 31 – Feb 1
Bivariate description
Relating 2 nominal variables
Relating 2 ordinal variables
Information Collection and Management II
Week 6
Research Ethics and Design
Feb 7 - 8
Ch. 6, 7
Second Tri Council Policy Statement,
TCPS 2: Ethical Conduct for Research
Involving Humans
http://www.pre.ethics.gc.ca/eng/policypolitique/initiatives/tcps2-eptc2/Default/
You might also find the TCPS 2
Tutorial and Quiz useful
http://www.pre.ethics.gc.ca/eng/educati
on/tutorial-didacticiel/
York University’s Policy on Research
Ethics
http://www.yorku.ca/secretariat/policies
/document.php?document=94
Week 7
Feb 14 - 15
Research Design and
Sampling Methods
Ch. 8, 9
Feb 18-24 Reading Break No Classes or Office Hours
Data analysis
Week 8
Feb 28 - 29
Inferential Statistics I
Ch. 10, 11
Week 9
Mar 6 - 7
Inferential Statistics II
Ch. 14, 15, 16
Week 10
Mar 13 – 14
Inference re a single interval
variable
Ch. 17, 18, 19, 21 (Ch. 21 is a review,
you may omit material relevant to Ch.
20.)
Week 11
Mar 20 - 21
Inference re regression;
Inference re two
nominal/ordinal variables
Ch. 23, 24, 27
(Note that Chapter 27 is not in printed
text.)
Week 12
Mar 27 – 28
In Class Final Exam