Analyzing Quantitative Anthropological Data
Anthropology 322
Fall 1998


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Course Description

This class examines how to discover patterning in quantitative data, or data that come to us in the form of numbers. The emphasis is on data exploration rather than on the application of confirmatory statistics to test hypotheses. Although it is a crucial aspect of data analysis, data exploration is seldom covered in courses on research design or traditional statistics. This course aims to fill in the gaps left by these other courses.

Anth 322 is designed particularly, but not exclusively, for students who are working on their own research (e.g., undergraduate honors thesis, pre-dissertation paper, MA thesis, Ph.D. dissertation, or article). It assumes that the best way to master the course material is to apply it in your own research.

There are several course objectives:

  • Define a philosophy of data analysis;
  • Examine the delicate balance of technique and art you need to produce usable, efficient data analyses; and
  • Investigate and apply a wide range of exploratory and data visualization techniques.

Students should have completed an introductory level statistics course and Anth 318, "Anthropological Research Design," or have equivalent training and experience. Grading will be based on problem sets, class presentations, and a semester project of your choice.

Course Outline

Click on a line to see a general synopsis of what the topic includes, or access each part separately through the "lectures" and "assignments" buttons.

Disc/Lec: 2 MW, 209a Davenport/ 2 F, 206 Lincoln Hall

Aug 26

Introduction

Aug 31

What is Data Analysis?

Sep 9 & 14

Graphical Data Displays

Sep 21

Univariate Displays

Sep 28

Data Transformations

Oct 5-12

Bivariate and Simple Multivariate Displays

Oct 14-19

Smoothing

Oct 21-30

Complex Multivariate Displays

Nov 2

Introduction to Bootstrapping

Nov 9 & 16

Correspondence Analysis

Nov 23-Dec 11

Student Presentations

Dec 18

Seminar Papers due by 1 pm

Grading

Each student will be expected to participate actively in class discussions and presentations.  Problem sets that apply principles covered in class will be assigned throughout the semester.

Semester Project (50% of your final grade)

This is the key assignment of the course.  It is intended to give you the opportunity to apply the course materials in a real analysis of your own design (which we can help you to develop if need be).  See the project guidelines for details. 

Each student also will have to give a class presentation on their semester project.  The presentation must be comparable in quality and scope to a paper given at a national conference.  The final written report on this project will comprise 40% of the final grade; the in-class presentation will count for 10% of the final grade.

Homework (50% of your final grade)

In keeping with my belief that the course materials are best learned by applying them, there will be 5 homework assignments, each of which are worth 10% of your final grade.

Feel free to discuss the homework problems with other students but I want to see your work, not a group consensus. I also want to see the details of your work, but don't hand me a 2 cm thick printout and expect me to explore it to find your answer. If I cannot reconstruct from your homework papers how you came up with the answers you turn in, then you will receive a low grade for the assignment. See the Assignments section of this class web page for homework deadlines. Late homework will be marked down a letter grade for each day it is overdue.

Textbooks

  • Jacoby, William G. (1997) Statistical Graphics for Univariate and Bivariate Data. Thousand Oaks, CA: Sage.
  • Jacoby, William G. (1998) Statistical Graphics for Visualizing Multivariate Data. Thousand Oaks, CA: Sage.
  • Clausen, Sten-Erik (1998) Applied Correspondence Analysis: An Introduction. Thousand Oaks, CA: Sage.
  • Hamilton, Lawrence C. (1998) Statistics with Stata 5. Pacific Grove, CA: Duxbury.
  • Other assigned articles will be on reserve in the Anthropology Reading Room (193 Davenport Hall).

Instructors:

Instructor: Barry Lewis
Hours: 8-11 Wednesday
Office: 209f Davenport Hall
Phone: 244-3501
Email: blewis@uiuc.edu