Poli 101 Outline

Introduction to Research Methods                                                                          UCSC Winter 2018
J.F. Fletcher

This course provides students with a hands-on overview of many data analytic techniques and research methods used today in political science. Through the course students will learn to effectively conduct their own investigations as well as appreciate (and criticize) social scientific research reports. Students will learn to describe data, assess statistical relationships and test hypotheses. More generally, the course will prepare students to handle the in-depth research requirements of upper division courses.

Required Reading:

*Alan Bryman, 2012. Social Research Methods. Link

*Wolfgang Ludwig-Mayerhofer, Internet Guide to SPSS for Windows.

Please note, this schedule is subject to change. Notice of such changes will appear on the News page of the course website.

Week 1: Introduction to Social Research

Learning Objectives:
Understanding the social scientific approach to the study of politics; appreciating it benefits and limits; using the language of theories, concepts and hypotheses.

*Bryman, read Ch 1; skim the rest of Part 1. Read Chapt 7 160-165, 175-178.

Link to Public Policy Institute of California (PPIC) Data Depot:

Link to PPIC Search tool and Survey Crosstabs:

Link To PPIC Oct 2016 Codebook and Data:


Week 2: Describing Variables & Constructing Tables

Learning Objectives:
Understanding how and why political scientists describe groups and compare subgroups with differing degrees of precision; appreciating ways in which information is organized affects interpretations; using summary measures with frequency distributions and crosstabulations.

Homework 1: Univariate & Bivariate Homework (due Week 3).

*Bryman, read Chapt 15 pp 330-344; Chapt 16 pp 354-367; 373-374.

or Neuman  Chapt 12 pp 393-402, 406 -414

*Ludwig-Mayerhofer, Basics (Syntax, Data Files & Output), Simple Analysis (Frequency Tables), Data Transformation (Recode), Handling Data Files (Missing Values, Labeling Variables and Values; Rename Variables and Selecting Cases), Simple Analysis (Crosstabulation).

Grey et al., Chapter 4 (pp 58-60 only); Chapter 18 (pp 397-410 only).

Data Lab

Selecting Measures of Association

Interpreting Measures of Association

Week 3: Measuring, Operationalizing & Indexing

Learning Objectives:
Understanding how and why political scientists measure complex social phenomena; appreciating how concepts relate to measures; using reliability techniques to create multi-item indicators.

*Bryman, Read Chapt 7 pp 166-178;

*Ludwig-Mayerhoffer, Data Reduction (Item Analysis), Data Transformation (Compute) ;

Leech et al. Chapt 4 pp 64-71. (provides detailed example of SPSS commands & output)
under Readings (Statistics Texts);

Grey et al., Chapters 4 (pp 61-75) & 17;

Paul C. Price. 2012.  Chapt 5 pp 117-120 under Readings (Methods Texts);

Data Lab

Quiz 1

Week 4: Surveys, Sampling & Significance

Learning Objectives:
Understanding how and why political scientists gather sample data; appreciating sampling’s limits and some compensating strategies; using probability theory to make inferences.

*Bryman, Skim Chapts 8-11 & 28; Chapt 15, pp 347-9 & Plate 16.15 p 368.

*Ludwig-Mayerhoffer Handling Data Files (Case Weights);

Neuman Chapt 12 pp 422-426.

Grey et al., Chapters 6, 7 and Chapter 19 (pp 426-29 only);

PPIC Survey Methodology

PPIC Oct 2016 Survey Report

Graphic Probability Calculator

Numeric Probability Calculator

Dan Benjmin 2017. “Let’s Redefine Statistical Significance”

Daniel, T. & Kostic, B. (2017). RStats Tables and Calculators

Data Lab

Week 5: Qualitative Approaches and Methods

Learning Objectives:
Understanding how and why political scientists use qualitative approaches; appreciating limits in quantitative work; using observation, interviews and analytic narratives to investigate concrete cases.

*Bryman, Skim Chapts 12 & 13, Part III & Chapts 26 & 27.

Grey et al., skim Chapters 8-10, 11, 13, 15 & 16.

Barasko Maryann et al., 2015. Understanding Political Science Research Methods: The Challenge of Inference, Routledge, Chapter 7.

Kapiszewski, Diana, Maclean, Lauren & Read, Benjamin 2015. Field Research in Political Science: Practices and Principles. Cambridge University Press.

Homework 2: Index & Inference Homework (due Week 6).

Week 6: Correlation & Causality

Leaning Objectives:
Understanding how and why political scientists distinguish between association and causation; appreciating some of the challenges of causal inference; using correlational analysis properly.

*Bryman, Chapt 15 pp 341-3; 349-50; Chap 16, p 370; Skim Chapt 14.

*Ludwig-Mayerhoffer Simple Analysis (Correlations)

Neuman Chapt 12

Grey et al., Chapter 14, 18 (pp. 407-410 only).

Data Lab

Quiz 2

Week 7: Multivariate Regression

Learning Objectives:
Understanding how and why political scientists gauge the relative influence of multiple factors; appreciating the challenge of comparison; using standardization as an approach

Homework 3: Correlation and Regression Homework (due week 8);

Ludwig-Mayerhoffer, More Complex Analysis (Linear Regression);

Neuman Chapt 12 pp 421-422.

Grey et al., Chapter 19 (pp. 421-24 only.

Data Lab

Week 8: Experimental & Statistical Control

Learning Objectives:
Understanding how and why political scientists seek control over variables; appreciating alternative theoretical linkages; using statistical controls and similar system designs to mimic control.

*Bryman Read Chapter 3 pp 50-6;  Chapter 15  pp 345-6; Chapter 16 p 372 (bottom right);

*Ludwig-Mayerhoffer Simple Analysis (T-test & Simple Analysis of Variance);

*Neuman Chapt 12 pp 415-421.

*Price Chapt 13 pp 358-363.

Grey et al., Chapter 5 (pp 88-93 only) Chapter 12 and Chapter 17 (pp. 410-17 only).

Quiz 3

Week 9: Regression Refinements

Learning Objectives:
Understanding how and why political scientists look for omitted variables and interactions; appreciating regression’s limitations and extensions; using diagnostic tools.

Final Assignment 4 (due in exam slot)

Bryman Chapter 15, (pp 345-6 only), Chapter 16 (pp 372-3 only).

Grey et al., Chapter 18 (pp 410-415 only) statistical control Chapter 19 (pp 424-26 only) path analysis.

Neuman, Chapter 12 (pp 417-21 only).

Data Lab

Week 10: Review and Preparing Final Assignment

Learning Objectives:
Understanding how and why political scientists’ reports bring design elements together; appreciating the open-ended nature of research; using alternative reporting techniques.

*Bryman, read Chapt 27.

Grey, Chapter 3 (pp 49-54 only), Chapter 5 (93-95 only) Epilogue.


CJPS_Fletcher-Hove published version (5)

Cell Host and Microbe

Quiz 4

Week 11: Exam slot (Wednesday March 21 4-7pm).

Final Assignment due

Note: This schedule may change somewhat as the quarter progresses