ENG 131 - INTRODUCTION TO PROBABILITY THEORY

Winter 2002

Professor:	Bruno Sansó
Hours:	Tues. and Thus. 10 to 11:45
Room:	Baskin 372
Office:	Baskin 143
Office Hours:	Tues. and Thus. 4:30 to 6:00
e-mail:	bruno @ ams.ucsc.edu

• General Description: This course consists of an introduction to probability theory and its applications. The main goal is to develop the basic mathematical tools to consider models that incorporate uncertainty using a probabilistic framework. We start by introducing the axioms of probability and the rules needed to perform calculations with probabilities. We then move into the concepts of independence, conditional probability and Bayes theory, define a random variable, both discrete and continuous, and consider its probability distribution function as well as its expectation and higher order moments. We extend these ideas to the multivariate case. Finally we consider some more advanced topics like the Law of Large Numbers, Central Limit theorem and, time permitting, a brief introduction to some simple stochastic processes like Markov Chains and Poisson Processes.
• Textbook:
  • Probability and Statistics (third edition). M.H. DeGroot and M.J. Schervish. Addison Wesley
• Other References:
  • A First Course in Probability (sixth edition). S. Ross. Prentice Hall
• Grading: There will be one midterm (35%, Tues., Feb. 5), two quizes (15%, Tues., Jan. 22 and 15%, Tues., Feb. 26) and a final exam (35%, Mon., March 18, 16:00-19:00). Exams and quizes will be based on the homeworks.
• Homeworks: There will be weekly homeworks which will not be graded. Homeworks will give a very close indication of the material that will be covered in exams and quizes.

Course Calendar

Homeworks

Solutions