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4321-5323sum08
Course: STA 4321, Fall 2008School: FSU
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4321/STA STA 5323 Introduction to Mathematical Statistics Summer 2008- Session B Time & Place: Instructor: Email: Office Hours: Grader Info: Grader Office Hours: Text: M through F 9:30 - 10:50 AM, OSB 110 Dr. Vic Patrangenaru vic@stat.fsu.edu T W R 11:00AM - 1:00 PM , OSB 208 Ms. Jihyung Shin, e-mail: jshin@stat.fsu.edu M through F 12:30 AM - 1:30 PM , OSB 209B Statistical Inference, Second Edition, by...
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4321/STA STA 5323 Introduction to Mathematical Statistics Summer 2008- Session B Time & Place: Instructor: Email: Office Hours: Grader Info: Grader Office Hours: Text: M through F 9:30 - 10:50 AM, OSB 110 Dr. Vic Patrangenaru vic@stat.fsu.edu T W R 11:00AM - 1:00 PM , OSB 208 Ms. Jihyung Shin, e-mail: jshin@stat.fsu.edu M through F 12:30 AM - 1:30 PM , OSB 209B Statistical Inference, Second Edition, by George Casella and Roger Berger. ISBN: 0534243126
Important Dates: Monday, May 12 Tuesday, May 13 Thursday, May 15 Monday, May 26 Thursday, May 29 Friday, May 30 Monday, June 9 Friday, June 20
First day of Summer Session B. First day attendance is compulsory. In class test of prerequisites. Results on May 14. A score of 60% is needed to continue. Last day to drop and add and have fees adjusted. Memorial Day, no class. In class Midterm Exam 1. Last day to drop a course without receiving a grade. In class Midterm Exam 2. Last day of class. In class Final exam.
Prerequisite: MAC 2313 (Calculus III) Course Outline: (following the book) Chapter 1 Probability Theory Chapter 2 Transformations and Expectations Chapter 3 Common Families of Distributions Chapter 4 Multiple Random Variables Chapter 5 Properties of a Random Sample Course Topics: Stat 4321 is a course designed to give students both an intuitive and a logical account of basic probability needed statistics. for Upon completion of the course students should master concepts such as probability space; counting principles; conditional probability; Bayes rule; independence; distributions of random variables; joint, marginal and conditional distributions of multivariate random vectors; expectations ; sampling distributions . Time depending the course will also cover limiting distributions, the Central Limit Theorem and its applications. Grading: The course grade will be calculated on the basis of attendance (5%), homework (25%) , midterm exams 1 of 25%, midterm exam 2 of 15% and final exam of 30%. The dates of the first two tests will be discussed and announced in class. There will be no make ups. Homework will be collected typically on Mondays and Thursdays. Class Attendance: If you need to miss an exam due to an officially approved trip, illness, family emergency, religious holiday (see below), or other emergency situations, please let me know as soon as possible. Makeup exams will only be given if an acceptable documentation is produced. If at all possible, please be courteous and notify me before the scheduled time of the exam. Active attendance adds up to 3% bonus points. On the other hand, if you miss at least 3 times in a row, this extra credit is lost. Disclaimer: This syllabus provides a general plan; deviations may be necessary.
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