Grade: Your grade will be determined as follows: a midterm exam (20% of your grade), a short project (20% of your grade), weekly quizzes (20% of your grade), and a final exam (the remaining 40% of your grade).
Class Log: The homework assignments and exam dates can be found in the class log. Each Friday's class will usually include a quiz based VERY closely on the assigned homework martial.
Honor Principle: On the exams and quizzes, no help is to be given or received. While working on the short project you may use any references you'd like under the condition that you always carefully reference your sources. Also, collaboration is encouraged during the process of thinking about and collecting data for your project, but every non-referenced aspect of your final write up must be entirely in your own words.
Students with disabilities: I encourage students with disabilities, including "invisible" disabilities like chronic diseases and learning disabilities, to discuss with me any appropriate accommodations that might be helpful.
Recitation session : Every Thursday from 7:00-9:00 our TA Francois G. Dorais will be running a recitation session. (Recall every Friday there is a quiz.)
X-Session: We will missing two class days (Monday April 25th and Monday May 24th). We will be making this up with 3 X-Sessions, on Thursday April 1, Thursday April 8, and Thursday April 15.
Syllabus: In this course we will cover the three basic tools of the statistical trade: descriptive statistics, probability, and inference. First we will cover various topics in descriptive statistics, including a look at correlation and the regression line. Next we will familiarize ourselves with various probability ideas, including the understanding of discrete distributions and the central limit theorem. Lastly, we will put our first two topics together and discuss inferential statistics, including a discussion of confidence intervals and a variety of hypothesis tests. We will essentially be covering all of the text, hence our text's table of contents can be used as a more detailed syllabus (More precisely we will definitely cover chapters 1-6,8-10,13-21,23,26-29. Some of the more interesting material is in the left over chapters, which we will cover if time permits.). I feel this text is fabulous, but it gives very little discussion of how to organize and manipulate large data sets. We will be learning this topic independently of the text, and, in particular, we will learn to use Stata.