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Professor Li Richard Ye (叶理)College of Business and Economics California State University, Northridge Email: rye@csun.edu
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Overview
The goal of this seminar is to introduce students to a variety of quantitative research methods in the business and management arena. The seminar will focus primarily on defining research problems, theory and hypotheses testing, causal inference, and designing research instruments. Specific topics in research methods include: primary and secondary data analysis, sampling, survey design, and experimental design. The seminar will conclude with an introduction to a range of statistical techniques that are available for empirical research: descriptive statistics, Inferential statistics, and Linear Regression.
Required Readings
All required readings are accessible online. Given the content of this seminar, it is absolutely important that students complete the assigned readings before each class meeting. There are parts of the class discussion that would not make sense if students did not complete the readings in advance. In addition, all students are encouraged to read beyond the required materials. Listed below are additional links to a more comprehensive list of readings related to quantitative research methods, all available online. An in-depth understanding of the content covered in such readings is essential for those with a strong interest in building their research and quantitative methodology skills.
Links to Additional Readings
Web Center for Social Research Methods: Knowledge Base (link) -- a comprehensive web-based textbook that covers the entire specturm of the topics in a typical introductory undergraduate or graduate course in social research methods. Note: it appears that any direct access from a Chinese IP address to this particular site has been intentionally blocked. It can still be accessed indirectly, however, by using a Web proxy. Here are two proxy sites that I have tried successfully: www.surf100.com, and www.myproxe.info/
HyperStat Online (link) -- an online statistics textbook, with many links to related resources
Quantitative, Positivist Research Methods in Information Systems (link) -- an online tutorial on quantitative research methods, commissioned by the Association of Information Systems (AIS)
Homework Assignments
There will be three homework assignments in this seminar. The first assignment is a practice of research problem definition and hypotheses development. The second assignment is an exercise of survey design. In this assignment you will complete some tasks in small groups and then the remaining tasks individually. The third assignment will require the use of a software package to conduct some simple statistical tests on a dataset. Information on each of the assignments will be distributed in advance during class.
Software
An important part of working with quantitative research methods involves the use of statistical software. We will be using SPSS (www.spss.com), a Statistical Package for the Social Sciences that has a very strong graphic user interface (GUI) and is well suited for beginners. For exercises, a data file will be provided. If you are unfamiliar with the software, here is a simple tutorial to get you started. If you prefer, you may use other statistical software packages, such as SAS or STATA. However, you will need to convert the data file provided into the appropriate format.
Evaluation
Your performance in this seminar will be evaluated as follows:
- Homework Assignments (3 total): 75%
- Attendance and Class Participation: 25%
Tentative Schedule
| Session | Topic | Assigned Readings | Homework Assignment |
| 1 (June 6th) |
Introduction: Elements of Research Defining Research Questions and Hypotheses Theory and Measurement: Causation, Scales and Operational Definition of Variables |
HW#1 Distributed | |
| 2 (June 9th) |
Validity and Reliability in Research Survey Research |
The Layman's Guide to Social Research Methods Survey Design (skim) Survey Research (skim) |
HW#1 Due HW#2 Distributed |
| 3 (June 13th) |
Experiments: Causal Relationships and Experimental Control |
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4 (June 16th) |
Descriptive Statistics: Probability, Distribution, Univariate Data, Correlation General Linear Model: t-Tests, Analysis of Variance, Regression |
HW#2 Due HW#3 Distributed |