Fall 2009 not offered
In this course you will learn the basic theory of probability. Although the notions are simple and the mathematics involved only requires a basic knowledge of the ideas of differential and integral calculus, a certain degree of mathematical maturity is necessary. The fundamental concepts to be studied are probability spaces and random variables, the most important ideas being conditional probability and independence. The main theorems we shall study are the law of large numbers and the central limit theorem. Understanding the ideas is emphasized, and computational proficiency will be less important, although correct answers to problems and clarity of explanation are expected.
Logical Reasoning, Quantitative Reasoning
This course will focus on the creation of formally correct inductive and deductive arguments, and will train students to formulate mathematical theories and descriptions of specific and complex objects.
||Gen Ed Area Dept:
|Course Format: Lecture / Discussion||Grading Mode: Graded|
||Fulfills a Major Requirement for: (CADS)(CIS)(COMP)(DATA-MN)(IDEA-MN)(MATH)(MB&B)(NS&B)
INTRODUCTION TO PROBABILITY, by Charles M. Grinstead and J. Laurie Snell; see
|Examinations and Assignments: |
The course will be problem-based. Students are required to submit answers to easy problems and to attempt to answer more challenging problems, due at the beginning of each class period. Regular class attendance is essential. There will be no formal examinations, and the grade will be based on the submissions and on class performance.
|Additional Requirements and/or Comments: |
This course is a prerequisite for the spring semester course MATH232, Statistics.
|Drop/Add Enrollment Requests|
|Total Submitted Requests: 0||1st Ranked: 0||2nd Ranked: 0||3rd Ranked: 0||4th Ranked: 0||Unranked: 0|