Editing Statistics and Statistical Programming (Winter 2017) (section)

== Overview and Learning Objectives ==

This course is the second course in a two-quarter quantitative methods sequence in the University of Washington's Department of Communication MA/PhD program. The first course (COM 520) is an introduction to quantitative social science in communication and focuses primarily on what you might think of the "soft skills" associated with doing social science: the conceptualization, operationalization of quantifiable variables, and the design of quantitative analyses. That course introduces some univariate and bivariate statistics at the end and briefly touches on linear regression. That said, all of the statistical work in that course this is done using the tools that students already know (e.g. with spreadsheet software like LibreOffice, Google Sheets or Microsoft Excel). This class assumes that students have taken COM 520 and that they understand what is involved in describing and testing social scientific theories with data and that basic terminology of quantitative social science is going to be familiar.

This course (COM 521) is focused on technical skill-building and aims to be a get-your-hands-dirty introduction to statistics and statistical programming. The point of the course is to give you the mathematical and technical tools to carry out your own statistical analyses. Through the process, we're going to try to help you become more sophisticated consumers of quantitative research.

Although we'll be doing some math in the course, this is not a math class. I am going to assume you're familiar with basic algebra and arithmetic. This course will not require knowledge of calculus. In general we're not going to cover the math behind the techniques we'll be covering. Unlike many statistics classes, I'm definitely not going to be doing proofs on the board.  Instead, the class is unapologetically focused on ''the application of statistic methodology''. In that sense, the goal of the is course is to create ''informed consumers'' of quantitative methodology, not producers of new types of methods. My goal is to train producers of social scientific research that use statistics as a means toward an end.

This course does not seek to be the last stats class you take. I started grad school having not taken a math class since high school (basically) and took 12 different statistics and math courses over the course of my time in graduate school. Honestly, I wish I had done more. What this class seeks to do is give you a solid basis on which to build statistical knowledge. Anyone who finishes this class should feel comfortable moving on to take advance classes in CSSS (classes above 510 on [https://www.csss.washington.edu/academics/courses this list]) and to start building toward a [https://www.csss.washington.edu/academics/phd-tracks/communication Statistics Concentration in the Department of Communication MA/PhD Program] or a [https://www.csss.washington.edu/academics/phd-tracks similar CSSS certificate/track] in another department.

We'll cover theses basic statistical techniques: t-tests; chi-squared tests; ANOVA, MANOVA, and related methods; linear regression; and end with logistic regression.

I will consider the course a complete success if every student is able to do all of these things at the end of the quarter:

* Carry out a complete analysis of a quantitative research project, start to finish.
* Read, modify, and create short programs in the GNU R statistical programming language.
* Feel comfortable reading papers that use basic statistical techniques.
* Feel comfortable and prepared enrolling in future statistics courses in CSSS.