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This is the homepage for MATH 3080 (Probability 1). 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! |
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Course Information
Instructor: Ronnie Pavlov Text: A First Course in Probability 8th Edition by Sheldon Ross. NOTE: I have received several questions about whether it's ok to buy the 7th edition of the text instead. There are not many differences between the 7th and 8th editions, so if you already have or would like to buy the 7th edition, this is probably fine. However, the main differences are in homework problems. So, if you buy the 7th edition, it will be YOUR responsibility to make sure that you have all of the assignment problems, and, if necessary, to borrow a book from a classmate to copy any problems missing from the 7th edition. 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
Exams You will have a midterm exam on Monday, October 17th, in our classroom during class time. Our final exam will be on Monday, November 21st, 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 DU’s 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!!! |