Mathematics 363

Introduction to Statistical Methods

Spring 2014

Course Home Page

Overview.

In Introduction to Statistical Methods, we shall be using your background in biology, economics, or engineering 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 many of our examples are derive 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, Antony Pearson. Antony has two academic majors – mathematics and molecular & cellular biology.

name

email

office hours

location

Joe Watkins

jwatkins at math.arizona.edu

10:00-11:00 Wednesday

11:00-12:00 Wednesday

1:30-2:30 Thursday

220 Mathematics

522 Mathematics

Antony Pearson

antonyp@email.arizona.edu

9:30-11:00 Monday

10:30-12:00 Friday

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 13th, 2014 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. In addition, we will have short assignments – either short reflections or in class activities. Students will also design and complete a project that analyzes data using statistical software.

The grading scheme is

	number	points	total
problem sets	6	varies	135
short assignments	5-10	varies	40
midterm exams	2	100	200
Project	1	50	50
final exam	1	175	175
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