Syllabus
Part I: Research Methods
Week 1: Introduction and Background to Research

Tue 30 Aug

(No reading.)

Thu 1 Sep

Bernard, Ch. 1 and 2

Week 2: Measurement and Defining Research Problems

Tue 6 Sep

Bernard, Chapter 2

Thu 8 Sep

  • Creswell, Chapters 1 and 6 PDF
  • Brown and Muchira. 2004. "Investigating the relationship between internet privacy concerns and online purchase behavior." Journal of Electronic Commerce Research. [*Focus on first 6 pages*].  PDF
  • Mark, Noah.  1998. "Birds of a Feather Sing Together" Social Forces 77:2. [*Focus on first 16 pages, up until the Results*] PDF

NOTE: The main goal for these readings is to critically examine the research problems and questions in each paper, and how the method fits the stated questions/problem.

Week 3: Survey Data Collection and Questionnaires

Tue 13 Sep

Bernard, Ch. 7
RMKB: Survey Research
(Be sure to click through all the subsections that appear when you click through the sections of Survey Research on the left-hand navigation.)

Thu 15 Sep

Bernard, Ch. 8

Week 4: Surveys, continued

Tue 20 Sep

  • Jon Krosnick, "Question and Questinnaire Design" PDF
  • Saris, W., Revilla, M., Krosnick, J. A., & Shaeffer, E. (2010). Comparing questions with agree/disagree response options to questions with item-specific response options. Survey Research Methods, 4, 61-79. PDF

Thu 22 Sep

Lab 1 in class

Week 5: Experiments and Experimental Design

Tue 27 Sep

Bernard, Ch. 4; Freedman, Pisani, and Purves, Ch. 1

Thu 29 Sep

No Class
Week 6: Working with Data and In-Class Experiment Lab

Tue 4 Oct

Special Lecture by UC Data Specialist, Fred Gey No reading, but browse the following sites and become familiar with the offerings:

Thu 6 Oct

In-Class Exercise: Lab 2-- Experimental Design
Part II: Probability and Statistics
Week 7: Wrap-Up From Experiments and Intro to Probability

Tue 11 Oct

RMKB: Design
Freedman, Pisani, and Purves, Ch. 2

Thu 13 Oct

Freedman et al. Chapters 13 (pp. 221-233), 14 (pp. 237-246) and 19 (pp. 333-353)

Week 8: Sampling and Univariate Analysis

Tue 18 Oct

Freedman et al. Chapter 20; Bernard Chapter 5, "Sampling"

Thu 20 Oct

Freedman et al. Chapters 3 and 4

Week 9: Univariate Analysis

Tue 25 Oct

ICPSR Guide to Social Science Data Preparation: Chapter 3 (carefully read pp. 13-18)
Freedman et al. Chapters 5, 6 and 7

Thu 27 Oct

Lab 3 in class: Working with Numeric Data in STATA

Part III: Bivariate and Multivariate Analyses
Week 10: Correlation and Logic of Hypothesis Testing

Tue 1 Nov

Freedman et al. Chapters 8 and 9

Thu 3 Nov

Freedman et al. Chapters 17, 18 and 26 (through page 488)

Week 11: The T-Test and Chi-Square Test

Tue 8 Nov

Bernard, Chapter 14 and 15 "Univariate Analysis" (pp. 526-535), Bivariate Analysis (pp. 546-549)
Freedman et al. Chapter 26 (488-500), Chapter 29
RMKB: The T-Test

Thu 10 Nov

Bernard Ch 14 (pp. 535-537)
Freedman et al. Chapter 28

Week 12: Analysis of Variance and F-Test

Tue 15 Nov

Bernard, Chapter 15 (pp. 549-557).

Thu 17 Nov

Lab 4 in class: Hypothesis Testing with Numeric Data using STATA

Week 13: Regression

Tue 22 Nov

Freedman et al. Chapters 10, 11 and 12

Thu 24 THANKSGIVING HOLIDAY

Week 14: Reading and Evaluating Social Research

Tue 29 Nov

Regression examples and discussion

Thu 1 Dec

Fiore, A.T., Taylor, L.S., Mendelsohn, G.A., and M. Hearst. Assessing Attractiveness in Online Dating Profiles. In Proc. ACM CHI 2008.

Week 15: Course review, Take-Home Exam Distributed in Class

Tue 6 Dec

Thu 8 Dec