This course will introduce basic statistical tools from probability and descriptive statistics. These have valuable "real-world" applications in a variety of fields. We will explore many of these applications, in a wide range of areas, from gambling, to the stock market, to environmental concerns, to civil rights, to sports. The class will prepare you to take STAT 301, the main business statistics course.
Students having difficulty with the course are always welcome to see the instructor during office hours (listed in the course syllabus). The university also provides tutoring resources; the schedule is available here.
The final record of grades from the Spring 2015 semester in the class is posted here. Grades for Fall 2015 will be posted as they come available.
This course is oriented around a "mastery" concept of learning. In this framework, exams and homework are intended primarily to provide a structure for mastery of course content, and only incidentally give a mechanism for assigning a grade. This is in direct contrast with traditional classes, where (at least functionally, if not intentionally) tests and assignments are primarily grade-oriented.
Material in the course is presented sequentially, from the most basic to the most advanced. We begin with foundational statistical procedures (the standard deviation, expected value, and normal distribution). Mastery of these topics is essential for success in further work in statistics. Students who demonstrate this mastery, on homework and by passing a "Basic Skills Test," merit a passing grade (D) in the course.
We then move on to somewhat more advanced topics — material that is still fairly fundamental, but more focused on real-world application and less on necessity as prerequisite for further course work in statistics. As part of this unit, students will read Darrell Huff's classic work, How to Lie with Statistics, as well as completing assignments on graphical techniques and foundational statistical tools. Students who demonstrate mastery at this level, as evidenced by successful completion of homework assignments, merit a satisfactory (C) grade in the course.
Next comes material of more specialized real-world application. We'll consider more advanced procedures in ranking and rating techniques. We'll also devote time to understanding correlation and regression techniques, widely used to describe and quantify the relationship between two (numerical) variables. Mastery of the material at this level, as demonstrated through homework, is indicated by a good (B) grade in the course.
The course ends with coverage of basic topics in probability, including rules for probability of compound events, combinatorial probability, and conditional probability. While these are not "advanced" topics, they tend to be more difficult ones. They are presented not only for their own usefulness, but also for their value in building quantitative and analytic skills. Mastery of this material, as evidenced through homework and a final exam, is indicated by an outstanding (A) grade in the course.
There will be a homework assignment most weeks in this class. They progress in mastery levels (as discussed above) and are design to facilitate learning of course material. On each assignment a satisfactory grade of 80% or higher is expected. While the intention is that students will normally demonstrate this level of mastery on first attempt, the homework assignments may be repeated until sufficient competence is shown. General instructions for the format of homework submissions can be found here.
*Note that Monday sections of the class will not meet during Week 3 (because of the Labor Day holiday), and Wednesday sections of the class will not meet during Week 14 (because of the Thanksgiving holiday).