This is the first semester of the two-course sequence in social
statistics required of graduate students in Sociology. This course
takes a systematic approach to the exposition of the general linear
model for continuous dependent variables; the second semester course
covers nonlinear regression models for categorical and limited
dependent variables. In addition to laying the theoretical foundations
for future social science research, this course introduces students to
the use of computerized statistical analysis using the software
program Stata. Students are encouraged to think creatively about how
to use statistical methods in their own research. Students meet twice
each week for a 75 minute lecture on statistical fundamentals, theory,
applications, and topics. Students are also required to attend
two-hour lab sessions after each lecture. The labs focus on computing
methods and data analysis techniques. The prerequisite for this course
is at least one statistics course at the level of S250, the
undergraduate course required of Sociology majors. There are no
mathematics prerequisites. Students are not expected to have a
background in calculus, but facility with algebra and exposure to the
rudiments of statistical distribution theory and hypothesis testing is
expected.