Mathematics 363
Introduction to Statistical Methods
Fall 2011
Course Home Page
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 319 of Harvill Building.
A summary of the class notes will be available to the students. The
schedule of topics, the class notes and assignments
are given in the course
syllabus. The class will have a
graduate assistant, Clayton Mosher. Clayton received an undergraduate degree in
mathematics and is now a graduate student in neuroscience.
|
name |
email |
office
hours |
location |
|
Joe Watkins |
jwatkins at math.arizona.edu |
Monday
2:00-3:00 PM Thursday
11:00-12:00 AM Friday
1:00-2:00 AM |
Math 220 Math 522 Math 522 |
|
Clayton Mosher |
cmosher at email.arizona.edu |
Tuesday 3:30-4:45 PM |
Math 220 Math 220 Life Sciences
North 327 |
Feel free to stop by my office in the Mathematics Building,
call me at 621-5245 or send an email.
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 15th, 2011 from
10:30 a.m to 12:30 p.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 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