MATH 3080
Probability 1
Autumn 2013

This is the homepage for MATH 3080 (Probability I). This page will be updated throughout the term with important information for our course, including homework assignments, review materials, solutions to assignments, and more. CHECK IT FREQUENTLY!

Announcements
  • Solutions for the practice final have been posted.
  • Assignment 9 (with solutions) has been posted. These problems do NOT need to be turned in; they're just practice problems for joint distributions.
Course Information

Instructor: Ronnie Pavlov
Office: John Greene Hall 304
e-mail: rpavlov@du.edu
Phone: (303)-871-4001
Office hours: Monday, 9:00 - 11:00 a.m. and 2:00 - 3:00 p.m.

Graduate TA: Thomas French
Office: John Greene Hall 312
e-mail: thomas.french@du.edu
Phone: (303)-871-2911
Office hours: Wednesday, 12:00 - 3:00 p.m.

Our class will meet on Tuesdays and Thursdays from 12:00 - 1:50 p.m. in John Greene Hall, room 102.

Text
Text: A First Course in Probability 9th Edition by Sheldon Ross.

This book is available at the DU Bookstore, and will also be used for MATH 3090 (Probability 2).

We will be covering most of chapters 1-4, the first half of chapter 5, and small portions of chapters 6 and 8 if time permits.

Course summary
We will begin by introducing the basic concepts of discrete probability theory. We begin with combinatorics, essentially the study of complicated counting problems. This allows us to introduce the formal definitions of probability on finite sample spaces (e.g. coin flipping and dice rolling). We then move on to the idea of conditional probability, or the notion of dependence/independence. (For example, two coin flips are independent, meaning that a heads or tails on the first has no bearing on the second. However, your performance on the midterm and final exams are dependent; a high score on one means that you probably understand the material well, and that you are more likely to get a higher score on the other.) Finally, we introduce the notion of random variables (functions on a probability space), expected value (weighted averages), and variance.

In the last portion of the course, we focus on the more difficult setup of probability theory with continuous distributions. Here, the sample space is infinite, and so we can no longer get by with the notions of counting and adding. Instead, we use calculus to define and study probabilities and random variables. We will discuss several useful examples, including the famous normal distribution (bell curve) and why it is so ubiquitous in statistics. Finally, we will spend the last week on some more advanced concepts leading into Probability 2, finishing with the famous Weak Law of Large Numbers.

Grading scheme
Your term grade will be composed of the following:

Final exam (40%)
Midterm exam (30%)
Homework (30%)

Homework

Late assignments will have a percentage subtracted according to the following policy:

1 day late: -25% (THIS INCLUDES MORE THAN 10 MIN. AFTER BEGINNING OF CLASS!)
2-3 days late: -50%
>3 days late: not accepted



Exams
You will have a midterm exam on Tuesday, October 15th, in our classroom during class time. Our final exam will be on Tuesday, November 19th, also in our classroom and during class time.
Important Documents
Course Schedule (subject to minor changes!)

Course Policies
You may use a simple scientific calculator for all exams and quizzes. Graphing or programmable calculators are not allowed as well as calculators that can perform any kind of calculus or symbolic operations. Use of a non-approved calculator will be considered a violation of DUís honor code. If you have any questions about your calculator please see me.

Makeup exams will only be offered in the event of extreme circumstances. If you think you have a problem which will force you to miss an exam, come talk to me as soon as possible!!!