MA381 Introduction to Probability with Statistical Applications Course Overview The goal of this course is to equip you with the basic concepts and tools of probability so that you can successfully construct and use probability models In other words after taking this class you should understand the basics of modeling random phenomena How to Do Well Warning For most of you this will be your first exposure to constructing and using random models instead of the deterministic models discussed in your other courses Therefore this course represents a significant departure from the mathematics you have seen previously Therefore in order to succeed you may need to spend more time studying the material and doing problems than in your prior math courses In addition to be successful in this course you should 1 Stay current on the material 2 Review the material and or do at least one problem daily 3 See me and or the tutoring center if you don t understand something Electronic Classroom Etiquette No cellphones At no point is your cell phone to be seen heard or used between the starting and ending bells for our period Any individual using his her cell phone e g viewing it and or texting during class will be assessed a 1 reduction overall class grade reduction for each infraction No laptops Except for rare occasions you will not need your laptops Therefore unless instructed otherwise by me you will not need to bring your laptop Laptop use unrelated to the course is prohibited during class Course Resources Text Fundamentals of Probability with Stochastic Processes third edition by Saeed Ghahramani ISBN 0 13 145340 8 Webpage www rose hulman edu class ma inlow Math381 Software For some hw problems you may need Maple You will not be using Maple on quizzes or exams Office Hours Office hours are 11 00 to 12 00 and 1 30 to 2 00 MTThF Please do not come to my office between noon and 12 40 start of 6th since I prep for class during this time My office is G 210A Crapo E mail I check my e mail throughout the day and occasionally during the evening I try to respond in a timely fashion relative to the urgency of the question 1 Grades Your grade in the course will computed using the following Homeworks I plan to assign one or two hw s a week Selected problems will be graded in depth completion credit will be given for the others Late and or e mailed hw s are not accepted Quizzes There will be at least 3 announced quizzes There are no make up quizzes If a valid excuse is provided in a timely fashion for a missed quiz the average of the other quizzes will be used to determine the value of that quiz otherwise the value of the quiz will be 0 Exams There will be 3 midterms There are no make up exams If a valid excuse is provided the value of the missed exam will be determined using the final Final There will be a final Part of the final will cover new material the remainder will be comprehensive Formula Grades will be determined using the usual 90 80 70 60 breakdown but I reserve the right to curve your grade upward Below are the point breakdowns Homeworks 70 Quizzes 100 Exams 3 100 Final 150 Total 620 Academic Misconduct The Rose Hulman student handbook states that academic misconduct includes actions such as cheating plagiarizing or interfering with the academic progress of other students In accord with the handbook I reserve the right to give reduced or no credit for work dishonestly done and to levy further penalties For more details see the student handbook Attendance You are expected to attend every class If you miss a class you are expected to see me and discuss what you missed in class that day I will warn you if I feel you have missed too many classes Once you are warned I reserve the right to give you a failing grade if you continue to miss classes 2 Course Outline The following provides an overview of the topics and methods in order which we will cover in the course Chpt 1 1 1 1 4 Basic probability models Kolmogorov Axioms set operations and events Chpt 2 2 2 2 4 Basic counting principles combinations and permutations Chpt 3 3 1 3 5 Conditional probability laws of multiplication and total probability Bayes Theorem independence Chpt 4 4 1 4 5 Random variables RV s distribution functions discrete RV s expectations variances and moments of discrete RV s Chpt 5 5 1 5 3 Bernoulli binomial Poisson geometric hypergeometric and negative binomial discrete RV s Chpt 6 6 1 6 3 Absolutely continuous RV s density functions functions of RV s expectaions and variances Chpt 7 7 1 7 3 Uniform normal and exponential RV s Chpt 8 8 1 8 3 Joint distribution of bivariate RV s independent RV s conditional distributions Chpt 10 10 1 10 4 Expected values of sums of RV s covariance correlation conditioning on RV s Chpt 11 11 1 11 3 11 5 Moment generating functions sums of independent RV s Chebychev Inequality central limit theorem Supplement Statistical applications estimators confidence intervals and hypothesis tests 3