Mathematics 363
Introduction to
Statistical Methods
Spring 2013
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 202 of Modern Languages
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
an undergraduate teaching assistant, Taylor Corcoran. Taylor has two academic
majors – mathematics and economics.
name |
email |
office hours |
location |
Joe Watkins |
jwatkins
at math.arizona.edu |
12:00-1:30 Monday 10:30-12:00 Friday |
220 Mathematics 522 Mathematics |
Taylor Corcoran |
taylorc3 at email.arizona.edu |
1:30-2:30 Tuesday 9:00–9:50 Wednesday 1:00-2:30 Thursday |
220 Mathematics 220 Mathematics 220 Mathematics |
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 Tuesday, May 7th, 2012 from 8:00 a.m
to 10:00 a.m.
Homework is an essential part of any mathematics or
statistics 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 |
varies |
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