Advanced statistics will focus on some of the actual quantitative models used by sociologists in empirical research. We will focus on the interpretation of data rather than calculations. We will discuss contemporary usage of these tools and some of the key issues confronting working social scientists. The goal is a better understanding of data analysis in social research.

Our main text will be OpenIntro Statistics (3rd edition), a free, open-source textbook. You can download a PDF of the book for free or buy a low-cost paperback. There is also a PDF optimized for tablets. The purpose of the readings is to make the lecture and exercises in class easier to understand. In the schedule, below, the chapters refer to this textbook. I've also prepared an online primer, An Introduction to Data Analysis & Presentation, to help you learn the material. In addition, I have made available, in the comment below, some additional readings on the topics we will discuss.

Learning objectives:
By the end of the semester, students will be able to:
* Interpret the results of linear and logistic regression;
* Interpret the results of factorial and multivariate analysis of variance;
* Interpret the results of principal components analysis and scaling models;
* Interpret the results of discriminant function analysis;
* Interpret the results of canonical correlation analysis; and,
* Interpret empirical evidence from sociological research articles.

About the course:
* Attendance is required. Every unexcused absence will result in a two point deduction. If you must miss a meeting, you are required to fill out the absence form. (Fill out the form in advance if the absence is planned. Otherwise, complete the form as soon as possible after the meeting you missed.) If I do not receive a completed form, the absence will be counted as unexcused.
* Class meetings will be a mixture of lecture presentation and hands-on activities.
* Be prepared to participate in discussions. You should complete the assigned readings prior to the class meeting in which they will be discussed. Take notes on the readings: ask questions about what is unclear; make connections to other points of knowledge.
* Be prepared to participate in group exercises. The best way to learn is to teach, and we will often engage in exercises that require you to explain material to each other.
* Be prepared to interact through the course web site. This will allow us to extend the course beyond the class meetings.
* Out of respect for your classmates, you should refrain from disruptive activities, such as talking in class during the lecture, sleeping, arriving late or leaving early, etc. Please do not bring your cellular phone to class, or turn it off during the class meeting. You will be marked as absent on a given day for persistent infractions.

Grading will consist of three parts: (a) three midterm examinations; (b) the final examination; and, (c) participation. The examinations will involve short answer questions about the statistical tools and readings. Each midterm exam is worth up to 20 points. The final exam is worth up to 25 points. Participation in class and on the course site is worth up to 15 points.

Grades will be assigned according to the following scale: 100-94 = A, 93-90 = A-, 89-87 = B+, 86-82 = B, 81-80 = B-, 79-76 = C+, and, 75-70 = C. The minimum passing score is 70.

Consult the Brooklyn College Bulletin and the university policy [PDF] for regulations regarding academic integrity. If you submit work for credit that is not your own, you will receive a zero on that assignment. Academic dishonesty is grounds for failure in the course. Additional penalties may result, at the discretion of the college.