Simon Fraser University
Engaging the World

Course Outlines

Spring 2022 - CRIM 861 G100

Research Methods II: Quantitative Methods (3)

Class Number: 4117

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 10 – Apr 11, 2022: Wed, 2:30–6:20 p.m.
    Burnaby

Description

CALENDAR DESCRIPTION:

The coverage of a range of statistical techniques, including linear regression, logistic regression, and data reduction techniques such as cluster and factor analysis. The purposes, assumptions, and conduct of such analyses using a statistical software package for social sciences (e.g. SPSS, Stata, R) will be covered. Attention will be given to the decisions involved in data exploration and preparation for statistical modeling purposes. Students enrolling in this course are expected to have a solid background in undergraduate quantitative research methods, equivalent to CRIM 320.

COURSE DETAILS:

Each week focuses on a particular statistical technique or set of related techniques. This will include describing a technique’s purpose, assumptions, and type of information provided. Lectures will also cover how to conduct the analysis in SPSS and interpret the results. An optional one-hour lab will be held at the end of lecture. This lab is meant to give students an opportunity to contact the TA for guidance in troubleshooting analyses conducted for course assignments/term paper.

Grading

  • Assignments (4) 20%
  • Big Quiz 25%
  • Oral Presentation 15%
  • Term Paper 40%

Materials

REQUIRED READING:

A. Garson Blue Books

The primary textbook material for this class is a set of books from the “Blue Book” series written by G. David Garson. These books are approximately $5 for Kindle versions at Amazon.ca (you don’t need a Kindle – just the free Kindle app that works on any laptop/tablet). The books can also be obtained for free by filling out a form requesting PDF copies. Do it sooner rather than later because you need to obtain a password from Garson first, via his website. The web page for these books is here: http://www.statisticalassociates.com/booklist.htm

You will need the following Blue Books:

  • Significance Testing 2012 edition
  • Measures of association 2012 edition
  • Correlation
  • Multiple Regression 2014 edition
  • Logistic Regression, Binary & Multinomial 2016 edition
  • Cluster Analysis 2014 edition
  • Factor Analysis 2013 edition

B. Readings Uploaded to Canvas

A series of empirical articles will be uploaded to Canvas that cover some of the different analyses taught in the course. Reading these articles is often helpful to understand why a particular analysis should be used to answer a given research question. Information contained in these papers is fair game from inclusion in the Big Quiz.

C. Sage Green Books

The “Sage Little Green Books” are technical at times, but important background resources for the material we will cover. We will not have time to cover them directly in most seminars. Be efficient in your reading of those books, it is not for memorization. The following books are all available in Full text - Unlimited user access from SFU Library Online. See the syllabus for which specific sections you are expected to read.

  • Lewis-Beck, Michael S. (1995). Data Analysis. Print ISBN: 9780803957725 | Online ISBN: 9781412983846
  • Lewis-Beck, Michael. Applied Regression: An Introduction. Thousand Oaks, CA: Sage Publications, 1980. ISBN: 9780803914940
  • Berry, William D. and Stanley Feldman. Multiple Regression in Practice. Thousand Oaks, CA: Sage Publications, 1985. ISBN: 9780803920545
  • Pampel, Fred C. Logistic Regression: A Primer. Thousand Oaks, CA: Sage Publications, 2000. ISBN: 9780761920106
  • Aldenderfer, Mark S. and Roger K. Blashfield. Cluster Analysis. Thousand Oaks, CA: Sage Publications, 1984. ISBN: 9780803923768
  • Dunteman, George H. Principal Components Analysis. Thousand Oaks, CA: Sage Publications, 1989. ISBN: 9780803931046

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

TEACHING AT SFU IN SPRING 2022

Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place.  Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes.  You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).

Enrolling in a course acknowledges that you are able to attend in whatever format is required.  You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.

Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.