Download Department of Statistics

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%