Statistical Tools for Quantitative Reasoning

Peter D. Brandon
Carleton College

Summary


This course introduces students to advanced statistical models for detecting and quantifying social relationships and to strategies for arguing that discovered statistical relationships reflect broader social realities. Students will learn how to generate findings from scientific household surveys and then use those findings to create persuasive narratives and attention-getting posters. The first half of the course focuses on writing about findings generated from multiple regression models for continuous response variables. The course's second half concentrates on writing about findings produced from nonlinear regression models for binary response variables.

Course Size:
15-30

Institution Type:
Private four-year institution

Course Context:

This is an advanced course introducing students to advanced statistical models and quantitative writing. Students must have had basic statistics and math courses and must already have skills using statistical software. Students who take this course should at the end of the course feel confident with several statistical models and know new pathways for writing about their findings from those modeling strategies.

Course Content:

This course focuses on advanced multiple regression models for continuous and binary response variables. The course is applied in that students draw data from several scientific household surveys, detect and quantify empirical relationships, and then effectively write about those discovered statistical relationships. Much emphasis is placed on the graphical presentation of findings, persuasive writing, and assessment of the strengths and weaknesses of data.

Course Goals:

The goals of the course are to build students' knowledge and skills in the following areas:
  • assessing survey data for the study of social phenomena and relationships;
  • choosing, applying, and interpreting advance statistical methods for analyzing survey data;
  • using advanced statistical software to generate findings relevant to the social world;
  • constructing compelling written and oral arguments base upon scientifically-generated data;
  • reading social science studies with a deeper appreciation of the methods and prose;
  • presenting attention-grabbing posters about scientific findings.

Course Features:

The course provides many avenues for writing about findings from multivariate statistical models. Seven intensive assignments, a team poster project, and a capstone final project create an environment in which the students use data, mold that data, and interpret that data to reach substantive, defensible conclusions about social relationships. The team learning approached mixed with the individual capstone project should enhance the learning experience.

Course Philosophy:

I chose this design to permit students to have "hand-on" learning experiences with real data on real social issues. My teaching style involves challenging the students to work both cooperatively and independently and the course design permits this. The design also gives students the opportunity to communicate their findings to peers and lay audiences, not just me. I think that students should be taught not just how to discover and quantify statistical relationships but also have the opportunity to learn how to communicate those findings in writing and orally.

Assessment:

Improvement in presentation techniques and writing.
Improvement in statistical routines and skills for assessing models.
Improvement and confidence in using the vocabulary of a quantitative social scientist.

Syllabus:

Syllabus (Microsoft Word 2007 (.docx) 36kB Aug14 09)

Teaching Materials:

First 4 assignments (Microsoft Word 2007 (.docx) 40kB Aug14 09)
Document describing STATA data sets used in the course (Microsoft Word 2007 (.docx) 37kB Aug14 09)
Initial class survey (Microsoft Word 2007 (.docx) 13kB Aug14 09)

References and Notes:

"Statistical Methods for the Social Sciences" Alan Agresti and Barbara Finlay
"An Introduction to Modern Econometrics Using Stata" Christopher F. Baum
"The Chicago Guide to Writing about Numbers" Jane E. Miller
Lecturer's notes
Resource support team that includes data manager, expert in poster presentation, writing specialist, and library archivist
ASA guidelines for statistical education, See ASA website.
Treiman's book "Quantitative Data Analysis: Doing Social Research to Test Ideas"
Kamenta "Elements of Econometrics"
Johnson and DiNardo "Econometric Methods"
Theil, "Principles of Econmetrics"