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Department of Statistics R251900 Applied Probability (應用機率論) Spring 2015 (103 學年度第 2 學期) 1. The mission of the College is to serve business and society in the global economy through developing professionally qualified and socially responsible business leaders as well as through advancing the frontiers of knowledge in business management. 2. The strategic objective of Department of Statistics is to cultivate quality professionals with enthusiasm and global perspectives. Graduate Program Learning Goals (goals covered by this course are indicated by checks): 1 2 3 4 5 Graduate students should be able to appreciate statistical research and to present research findings/ results effectively in speaking and in writing. Graduate students should be able to integrate different functional areas in solving statistical problems. Graduate students should be able to analyze data effectively and to recommend effective statistical methods. Graduate students should be able to demonstrate leadership skills of a data analysis manager. Graduate students should be able to identify ethical dilemmas and to determine necessary courses of action. Graduate students should possess a global statistical perspective and an awareness of the global business. Graduate students should be able to coordinate actions and solve problems jointly with other members of a professional team. Instructor/開課教師: Hsing-Ming Chang/張欣民 @stat.ncku.edu.tw 06-2757575#53631 Liang-Ching Lin /林良靖 [email protected] 06-2757575#53638 Prerequisite/先修科目: Course Description/課程描述: This course introduces students to the modeling, quantification, and analysis of uncertainty. Topics covered include: formulation and solution in sample space, random variables, simple stochastic processes such as Markov process, Poisson process and the related processes, and applications of those models. Course Objectives/課程目標: After completion of the course, the students are expected to know what is the Chapman-Kolmogorov Equation, to know some simple random process, and the most important, to know how to modeling a practical problem with a probability model. Teaching Approach(es)/教學方法: This course is intended as an introduction to elementary probability theory and stoachastic process. It is particularly well suited for those who wanting to see how probablility theory can be applied. Course Content/課程內容: Week 1: Introduction(林良靖) Week 2: Basic probability theory (I) (林良靖) Week 3: Basic probability theory (II) (林良靖) Week 4: Random variables(林良靖) Week 5: Topics from early days (I) (林良靖) Week 6: Topics from early days (II) (林良靖) Week 7: Conditional probability(林良靖) Week 8: Conditional expectation(林良靖) Week 9: Mid-exam Week 10:Markov chain (I) (張欣民) Week 11:Markov chain (II) (張欣民) Week 12:Applications of Markov chain(張欣民) Week 13:Random walks(張欣民) Week 14:Poisson process (I) (張欣民) Week 15:Poisson process (II) (張欣民) Week 16:Patterns(張欣民) Week 17:Special topics(張欣民) Week 18:Final-exam Textbook/教科書: Problems and Snapshots from the World of Probability, Blom, Holst, and Dennis (1994) References/參考書目: Introduction to Probability Models (10th ed.), Ross (2009) Grading Policy/評量方式: Grading Policy for AACSB Multiple Assessment: COMMU CPSI LEAD GLOB VSP Home Work 30% Mid-Exam 35% Final Exam 35% Writing 50 % 30 % 30 % Interdiscip. Competence/ Prob. Solving 50 % 40 % 40 % 30 % 30 % □ Speaking Critical Thinking/ Innovation □ Leadership □ Ethical Reasoning □ Global Vision □ Teamwork Home Work 30% COMMU Mid-Exam 35% Final Exam 35% 30% 30% □ Oral Communication/ Speaking Written Communication/Writing □ Creativity and Innovation CPSI Problem Solving Analytical & Computational Skills LEAD GLOB □ Leadership □ Ethic & Social Responsibility □ Global Awareness □ Values, Skills & Professionalism VSP □ Technical Skills □ Management Skills 50% 30% 30% 50% 40% 40%