Sociology | Statistics for Sociology
S371 | 3781 | James


Can students win some of David James’ hard-earned money while
attending class and learn some probability stuff too?  How can you
calculate your chances of survival (or Leonardo’s) had you been a
passenger on the Titanic?  When is the best time to watch the geyser
OLD FAITFULL erupt?  How much can you learn from the typical CNN “man
in the street interview?”  Who will win the next election?  Do tall
men tend to marry tall women?  What does a grade point average tell
you about a person?

If you would like to learn the answers to these and other interesting
questions, then this is the class for you!  If you prefer to read a
rather standard description of this course, please read on.

S371 is a statistics course required for undergraduate majors in
Sociology that also satisfies the COAS Math requirement.  It provides
an introduction to statistical theories and techniques appropriate
for answering sociological questions through the analysis of
quantitative data.  No prior knowledge of statistics is assumed but
students must have a good understanding of algebra.  If you have
never had a course in algebra at the high school level or above, you
should consider taking one before taking this course.

Descriptive and inferential statistics are covered in this course.
Descriptive statistics are used to describe or summarize sets of
numbers.  Grade point average, for example, is a descriptive
statistic.

Inferential statistics are designed to test sociological theories
based upon samples of data when it too expensive or impossible to
obtain all of the information needed from a population of interest.
Using a sample to estimate the proportion of voters who will vote for
a political candidate is an example of inferential statistics. By
making good choices about who to interview, one can generalize to the
national level, for all 180 million adult Americans, from the
information obtained from only about 2500 people.  Inferences are
educated guesses and students will learn how to distinguish good from
bad guesses.  You will also learn the following: how to construct and
describe frequency distributions, how to calculate and interpret
measures of central tendency and dispersion, how to tabulate data,
how to measure the association between two variables and how to
control statistically for a third, the logic of statistical inference
and hypothesis testing, how to decide if two groups of people are
different on some characteristic such as income, education, wealth,
age, occupation, skill, birth rates, death rates, or voting behavior
and how to estimate and interpret a linear regression model.

The course will focus on doing statistics.  Doing statistics will
require numerical computations, some by hand, some using hand
calculators or personal computers.  Nevertheless, I will de-emphasize
calculations per se, and concentrate instead on concepts and the
information conveyed by the numbers.