Math 5010 - 1   Introduction to Probability        January 9, 2009

                M, W, F  from  11:50 AM  to  12:40 PM  in LCB 225.
        

Instructor:     A. Treibergs, JWB 224, 581-­8350.
                Office Hours: 10:45-11:45 MWF (tent.) & by appt.
                E-mail: treiberg@math.utah.edu
                Homepage: http://www.math.utah.edu/~treiberg/M5010.html

Notice:         PhD students in departments other than mathematics wishing
                to get credit for this course should register under the
                number 6805. Mathematics PhD students cannot get 6000 level
                credit for this course.

Text:           David Stirzaker, Elementary Probability, 2nd. ed., Cambridge
                University Press, 2003.

Prerequisites   Math 2210 or 2520. (Basically, you'll need calculus through
                double integrals.) 


Grading

    Homework:   To be assigned weekly. 

                Homework, due Fridays, will be collected in
                class. Papers turned into my mailbox in the
                math mail room (JWB 228) by 5:00 PM Fridays will be
                regarded as being turned in on time. Homework that is 
                late but not more than one week late will receive half
                credit. Homework that is more than one week late will
                receive no credit at all. Students are encouraged to
                work together on homework, although solutions should be
                written up individually. Copying is cheating.

       Exams:   Exams will be open book: the text, your notes and a
                calculator are allowed. Other texts, laptops, text
                messengers will not be allowed. Exam problems will be
                modifications of homework problems.

       Midterms:   There will be two in-class one-hour midterm exams 
                   on Wednesdays Feb. 11 and Apr. 1. 

       Final Exam: Fri., May 1, 10:30 - 12:30. Half of the final
                   will be devoted to material covered after the second
                   midterm exam. The other half will be comprehensive.
                   Students must take the final to pass the course.



Course grade:   Sum of two midterms 50% + HW 15% + final 35%.
                

Withdrawals:    Last day to drop class is Jan. 21. Last day to register 
                is Jan 26. Until Mar. 6 you can withdraw from class with 
                no approval at all. After that date you must petition 
                your dean's office to be allowed to withdraw.

ADA:            The Americans with Disability Act requires that
                reasonable accommodations be provided for students
                with cognitive, systemic, learning and psychiatric
                disabilities. Please contact me at the beginning of
                the quarter to discuss any such accommodations you
                may require for this course.

VIDEO CAMERA:   The course is being recorded for transmission to remote
                students at ATK and elsewhere. Regular students who wish
                to view an individual lecture should send me an email
                with your name, email, and date of lecture you wish to view.
                I'll forward your request to Roanna Keough in Mechanical 
                Engineering who will provide you with the lecture.


                                  *  *  *

Objectives:     To cover the elementary theory of probability. To develop
                problem solving skills. To practice writing a mathematical
                argument. To review calculus.   
 
Topics:         We'll try to cover the first 8 chapters in the text, with
                lighter emphasis on Chapter 6. This will give you enough
                preparation for Math 5080 (mathematical statistics), Math
                5040 (stochastic processes), and Math 5030 (actuarial 
                mathematics).
 

  I    Ch 1 (Probability):  Sections 1-5, 8-10, 12

       Ch 2 (Conditional Probability, Independence): Sections 1-3,6,7,11,12

  II   Ch 3 (Counting):  Sections 1-4, 9, 10, 12, 15, 16

       Ch 4 (Random Variables):  Sections 1-4, 6 , 9, 10, 12, 13,

  III  Ch 5 (Random Vectors):  Sections 1-6, 8-9. Examples ???

       Ch 6 (Generating Functions):  Sections 1-4 (lightly), Examples ???

  IV   Ch 7 (Continuous RVs):  Sections 1-2, 4-6,  Examples???     

  V    Ch 8 (Jointly Continuous RVs):  Sections 1-7, 9, Examples ???