Introduction to Probability by David F. Anderson (ebook)Pre-requisites and course expectations. Grading See below for the breakdown of course grades. Grading will be based on weekly homework and quizzes along with two midterm examinations and one final examination. Homework will be graded for effort. It will primarily be to confirm that you are keeping up with the coursework. Quizzes will occur on Mondays and will be based on the material covered in the previous week. These will be your primary method of obtaining feedback in the course other than the exams.
Introduction to Probability
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Moodle: You can keep track of your grades in moodle. Also, the course materials such as practice problems for exams or solutions to selected homework problems will be posted in moodle. Grinstead and J. Topics: This is an introductory course in probabilitys, which contains topics such as probability spaces, random variables, distributions, expected values,variances, law of large numbers, moments, moment generating functions, joint distributions, conditional and marginal distributions, Bayes theorem. We will also discuss the normal distribution, and central limit theorem, as well as some of the other standard distributions, such as the Bernoulli, binomial, hypergeometric, Poisson, gamma, exponential, beta distributions, among others. We will aim to cover chapters 1- 7. There will be no make-up midterms.
They tie it all together with a coherent philosophy. Knowing the authors' work, I would expect nothing less. I predict that this text will become the standard for beginning probability courses. Toggle navigation. New to eBooks.
At Iowa State University, where I teach, the two undergraduate courses in probability theory for mathematics majors are cross-listed as statistics courses and taught by members of that department. Thus, I have never taught either of these courses, and never will. This has never bothered me greatly in the past, since my prior exposure to upper-level probability is limited to a couple of undergraduate and graduate courses. However, as a result of this book, and also a comparable book by Tijms called Probability: A Lively Introduction also published by Cambridge University Press, within a month of this one , I found myself thinking that it might be fun to teach a course on this material. It contains all the topics one would want to cover in an introductory course: the axioms for probability, classical probability i. There is more than enough material in this book for one semester, though likely not enough for two, so an instructor has some flexibility in its use.