Statistics in Sports

Math 116

Spring 2013


Professor Bradley A. Hartlaub
Office 305 Rutherford B. Hayes Hall
Phone PBX 5405
e-mail hartlaub@kenyon.edu

Office Hours

Required Text

Josh Tabor and Chris Franklin (2011), Statistical Reasoning in Sports, W. H. Freeman and Company

Supplemental Text

Albert, Jim (2003), Teaching Statistics Using Baseball , The Mathematical Association of America
Goals Statistical Package and Computing

MINITAB is available at all LAN sites on campus and will be used throughout the course. Assignments and course announcements will be sent to you via e-mail or posted on the course web page. Data sets and Minitab worksheets will be placed in P:\Data\Math\Hartlaub\SportsStats. Proper maintenance of computer accounts, files, etc. is your responsibility. I recommend that you back up your data sets and Minitab worksheets on a regular basis. I will not assume you have prior experience with statistical software so you do not need to be concerned about the use of technology in the classroom. Some of you may also use R, but this will be optional. This software is free and must be downloaded to your own personal machine.

Our class meets in a computer equipped classroom, and we will be using statistical software extensively in the course. During regular class hours, the use of computers is restricted to students enrolled in the course. Furthermore, the use of the computers is also restricted to activities deemed appropriate by the instructor. Playing computer games, reading e-mail, conversing in a chat room, surfing the web, and working on assignments for other courses are a few examples of inappropriate activities that can be distracting to the instructor and other students in the course. Inappropriate computer use may result in penalties ranging from warnings to loss of computer privileges for the period. In cases of extreme and/or repeated violations, grade penalties or expulsion from the course may result.

Learning Disabilities and Math Anxieties
If you have a disability and feel that you may have need for some type of academic accomotation(s) in order to participate fully in this class, please feel free to discuss your concerns with me in private and also identify yourself to Erin Salva, Coordinator of Disability Services at PBX 5453 or via e-mail at salvae@kenyon.edu.
Homework & Labs
Homework and lab assignments will be given throughout the semester. Subsets of these assignments will be collected and graded frequently. You should work on as many problems as possible. This includes problems which have not been assigned. All papers that you turn in must be legible with problem numbers and solutions clearly marked. I encourage you to discuss the concepts and problem solving techniques presented in class with other students. However, you must submit your own solution for each of the assigned problems to be collected. Most of the data sets from the supplemental textbook are available in P:\Data\MATH\Hartlaub\SportsStats\Albert.
Statistics Clinic
Tutors will be available Sunday, Tuesday, and Thursday evening throughout the semester. They will help you with technical software questions or general questions about the course material, but they will not solve your homework problems.
Late Policy
Assignments must be turned in at the beginning of the class period on the assigned due date. No credit will be given for late papers. If for any reason you cannot turn in your paper on the assigned date, you must contact me before class. If you are unable to contact me, you can leave a message with Connie Miller (PBX 5069) or send e-mail to hartlaub@kenyon.edu.
Exams
  • Exam 1 - Friday, March 1
  • Exam 2 - Friday, April 26
  • Quizzes

    Short quizzes will be given on a weekly basis, starting in the second week of classes. These quizzes wll typically last approximately 20 minutes.

    Final Project

    Each student will find a data set and apply an appropriate statistical analysis. The variables in the data set and the purpose of the study must be clearly defined. If the data is obtained from a periodical, the date of publication must be later than January 1, 2008. Summaries of your proposed analysis must be submitted on or before Monday, April 29. Final papers explaining the problem of interest, your analysis, and your conclusions must be submitted on or before Monday, May 6 at 11:30 am. A short presentation to the class, perhaps in the form of a poster session, will also be required.

    Group Presentations

    You will be responsible for preparing and delivering two presentations to the class. You may work with one or two of your peers on these class assignments. The presentations should be prepared with Microsoft Power Point (or similar software) and sent to me before class begins on the date of your presentation. The specific problem of interest is up to you. You must carefully describe your problem of interest, obtain appropriate data for addressing this problem, and provide a complete statistical analysis to the class. Your first presentation should deal with exploratory data analysis and statistical modeling and your second presentation must contain at least two statistical inferences.
    Grades
    Your course grade will be based on your overall percentage. The categories used to determine your overall percentage are listed below with their respective weights.
  • Homework (15%)
  • Presentations (20%)
  • Quizzes (15%)
  • Exam 1 (15%)
  • Exam 2 (15%)
  • Final Project (20%)
  • Class participation will be used to help make borderline decisions.
    Course Description

    Appropriate applications of statistical methods have changed the way some Major League Baseball teams manage the game, see Moneyball: The Art of Winning an Unfair Game. Statistics are used in other sports to evaluate the performance of individual players or teams. Students will use appropriate methods to examine interesting questions such as: Are there unusual patterns in the performance statistics of "steroid sluggers" such as Barry Bonds and Mark McGwire or pitchers such as Roger Clemens? The focus of this course will be on the proper application of statistical models in sports. Investigating the impacts of a penalty kick in soccer, home field advantage in football, technological improvements in golf or cycling or training methods on marathon times are other possible topics. Although the sport and question of interest will change, the focus on proper applications of appropriate statistical methods will remain the same. Students will analyze data and present their results to the class. Oral and written reports will be expected. QR (Prerequisite: Permission of instructor.)