Mathematics 363

Introduction to Statistical Methods

Fall 2009

Course Homepage


Course syllabus



In Introduction to Statistical Methods, we shall be using your background in biology and your previous knowledge of calculus and differential equations to consider the issues of collection, model derivation and analysis, interpretation, explanation, and presentation of data.  Even though our examples derive mainly from the life sciences, statistics is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities.


Day to Day Operations. 

The class meets Tuesdays and Thursdays from 9:30 AM to 10:45 AM in room 131 of McClelland Hall. We will supplement this material with case studies based on research work at the University of Arizona. A summary of the class notes will be available to the students. The schedule of topics, the class notes and the assignments are given in the course syllabus. We will have an assistant Wenhai Chen for the course. His office hours are 9:00AM to 10:30AM Wednesday and Friday in Math East room 149. My office hours are Mondays and Fridays at 1:00 PM and 11:00 Thursdays. The Thursday office hour is held in the upper division tutoring room Math East 145. Feel free to stop by my office, room 522 of the Mathematics building, calling me at 621-5245 or writing me  - jwatkins at


Use of Software.

We will do some software computation using R.  R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror. Copies of Introductory Statistics with R by Peter Dalgaard are available at the bookstore. Other options for software assistance can be found on the resource webpage.


Evaluation of Students.

We shall have 2 in-class midterm exams and a comprehensive final exam. Our final is scheduled for Thursday, December 17, 2009 from 8:00 a.m to 10:00 a.m.


Homework is an essential part of any mathematics course. Homework will be collected approximately bi-weekly. The homework grade will be based on the top 6 homework scores. Permission to turn in late homework for credit must be arranged in advance. Students will also design and complete a small project that analyzes data using statistical software.


The grading scheme is






problem sets




midterm exams








final exam









Grades will be given on the usual scale A is 90%-100%, B is 80%-89%, C is 70%-79%, D is 60%-69%, and E is below 60%. The instructors may move these cutoff values down. If you fail to complete the course due to circumstances unforeseen, then you may qualify for a grade of I, "incomplete'" if all of the conditions are met:



Students should take the time to become familiar with code of academic integrity.


Best wishes to you for a good semester in this course and in all your other activities.


  - Joe Watkins