Mathematics 363
Introduction to Statistical Methods
Fall 2009
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 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 6215245 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
inclass 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 biweekly. 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:
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