S371 | 10284 | Bartley

ABOVE SECTION OPEN TO MAJORS ONLY This course is designed to develop your quantitative analytic skills by teaching you how to understand, apply, and interpret basic statistical principles. The course is organized in two main parts. The first part covers descriptive statistics and deals with techniques for organizing and summarizing data in a sample. We will start by developing tools for describing a single variable-that is, some aspect of the social world that varies from case to case or over time. We will then start looking at relationships between two variables, in order to understand how one part of the social world shapes, influences, or causes another. The second part of the course covers inferential statistics--that is, a set of methods for using data from a sample to determine the unknown characteristics of populations. The goal here is to figure out how we can make claims about an entire population based on observing only a small part of that population (a sample). Once we develop the tools for making inferences, we will use those to extend the material from the first part of the course, in order to make sense of large-scale social outcomes and their possible causes. In addition to covering the logic of statistics and developing your skills at interpreting quantitative data, this course will provide you with practical experience working with SPSS (Statistical Package for the Social Sciences). This computer program is used in a variety of academic, business, and non-profit settings, and the skills you develop at processing and interpreting data with SPSS may prove highly useful further down the line. I assume no prior knowledge of statistics and the course is not particularly math-intensive. Instead, the course emphasizes the logic of describing variation, making comparisons, moving from samples to populations, and developing substantive interpretations of quantitative analyses. However, we will work with a number of simple formulas and graphical techniques, so a solid understanding of algebra is absolutely necessary.