Introduction
The purpose of this course is to equip
students with the skills and confidence to count things creatively. It will
introduce the methods used by economic and demographic historians to answer questions
about the past with quantitative data. In addition to statistical methods and
data management, we will cover research design and measurement issues. By the
end of the course, you should be able to:
·
Develop testable research questions
·
Design an analysis that will answer your
questions
·
Apply appropriate measurement strategies and
statistical techniques
·
Critically read and understand quantitative
historical research
The course meets the Liberal Education
Mathematical Thinking requirement, which means that it goes beyond rote
computational skills. Students will gain
broad understanding of mathematical thinking and quantitative analysis as a
body of knowledge. In addition, students will learn specific analytic tools
that have broad application for understanding the quantitative dimensions of
historical change.
The course emphasizes the logic of
quantitative measurement rather than cookbook recipes for statistical analysis.
Students will be expected to manipulate equations both to understand the probabilistic
basis of statistical analysis and to apply demographic and economic methods to
historical data.
We will focus on four general areas:
1.
Methods and statistics
We
will move quickly through elementary statistics (percentages, means, basic probability
and tests of statistical significance, bivariate regression and correlation)
and then turn to more advanced topics of special significance for historians
(e.g., sample designs, family reconstitution, multiple standardization and
demographic decomposition, indexes, measures of inequality, and logistic
regression).
2.
Data management, software, and computers
We
will focus on the use of SPSS for Windows and Microsoft Excel. We will also
briefly cover several other programs for quantitative analysis. The topics
covered will include design of data collections, data entry, analysis of
microdata, management of hierarchical data, making
graphs, mapping, and techniques of aggregate data analysis.
3.
Principles of measurement and presentation of quantitative information
These
often-neglected topics are the heart of the course. They include the principles
and philosophy of measurement, research designs and data sources, and aesthetic
considerations in the presentation of quantitative findings. Choosing what to
measure and how to measure it is a vital skill, and the most advanced
statistics in the world won't help you if you haven't got it right. In fact,
very often clever measurement strategies can actually save you from having to
use fancy statistics. Presentation is also critically important, especially for
historians because our audience is often innumerate. Measurement and
presentation issues will permeate all aspects of the course, and will be the
sole focus of several classes.
4.
Literature of quantitative history
We
will read and discuss quantitative historical articles. The readings for most
of the quarter are not set in stone; we will tailor them to the substantive
interests of the class.
Prerequisites
Although
there are no prerequisites, HIST 3011 is an advanced undergraduate course.
Students are expected to have a solid background in intermediate algebra. Basic
computer skills are also assumed.
Organization
The
class will meet in 440 Blegen Hall. I have scheduled
the room for an extra hour each day for lab time to carry out your assignments
and so we will have time to pursue extra topics of interest to particular
students. HIST 3011 and HIST 5011 students will meet together from 11:15 to
12:30. From 12:30 to 1:10, we will have lab work, in the same room. The basic
lab (intended mainly for students in HIST 3011) will be on Tuesdays, and the advanced
lab (intended mainly for students in HIST 5011) will be on Thursdays.
Software
Most of the course
will focus on two software applications: SPSS and Excel. SPSS once stood for
Statistical Package of the Social Sciences, but after IBM bought it and decided
to market it more broadly, it no longer stands for anything. SPSS will be available
in our labs in Blegen 440, but you will also need to
use SPSS outside of class time. SPSS is available in multiple computer labs on
campus, including Coffman Memorial Union B060 (open Monday-Thursday 8 a.m. - 9
p.m., Friday 8 a.m. - 6 p.m. and Saturday 10 a.m. - 6 p.m.), Walter Library 103
(open Monday-Thursday 8 a.m. – 9 p.m., Friday 8 a.m. - 6 p.m., and Saturday 12
p.m. - 6 p.m. and Magrath B50 on the St. Paul Campus
(Monday-Thursday 8 a.m. - 8 p.m. and Friday 8 a.m. - 5:30 p.m.). Visit
http://www.oit.umn.edu/computerlabs/ for more locations and hours. If you want
your own copy, you can buy the SPSS Statistics Grad Pack; the best price I have
seen is $79.99 from StudentDiscounts.Com (and you get two installs, so you
could team up with someone else and get it for $40). You need proof of
enrollment.
Excel is available in all labs. For most of the
exercises you can probably get away with the Google spreadsheet, but there will
be several cases in which you will need the real thing.