Mathematics 363

Introduction to Statistical Methods

Spring 2010

Course Homepage

Overview.

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 206 of the Harshbarger Building . 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. My office hours are 1 on Wednesday and 11 on Friday in my office. Feel free to stop by my office, room 522 of the Mathematics building, calling me at 621-5245 or writing me - jwatkins at math.arizona.edu.

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 Tuesday, May 11, 2010 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

	number	points	total
problem sets	6	25	150
midterm exams	2	100	200
project	1	50	50
final exam	1	200	200
total			600

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:

You have completed all but a small portion of the required work.
You have scored at least 50% on all work completed.
You have a valid reason for not completing the course on time.
You agree to make up the material in a short period of time.
You ask for the incomplete before grades are due - 48 hours after the final exam.

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