Basic Probability and Applications - STAT51600
By the end of this course, students will be able to understand probability measure, random variables, and their distribution functions, master many of the distribution finding techniques, such as transformation methods, know a lot of special distributions such as Binomial, Poisson, normal, and understand order statistics and the law of large numbers and the central limit theorem.
Learning Objective:
By the end of this course, students should be comfortable with probability distributions and random variables. They are also expected to master many of the distribution finding techniques, such as transformation methods, know a number of specific distributions (e.g. Bernoulli, Binomial, Poisson, Normal, t-, F-distributions etc), and understand order statistics, law of large numbers and the central limit theorem.
Description:
By the end of this course, students will be able to understand probability measure, random variables, and their distribution functions, master many of the distribution finding techniques, such as transformation methods, know a lot of special distributions such as Binomial, Poisson, normal, and understand order statistics and the law of large numbers and the central limit theorem.
Topics Covered:
Set theory, classical probability, random variables, conditional probability and expectation, important inequalities, multivariate random variables, special distributions, histogram, order statistics, central limit theorem
Prerequisites:
Applied / Theory:
10 / 90
Web Address:
http://www.stat.purdue.edu/~mlevins/
Web Content:
Syllabus, online notes
Homework:
Approximately 11 homework assignments
Projects:
None