一、課程說明(Course Description)
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<br>Provide a fundamental understanding of probability theory and its applications, and build up a solid knowledge base for more advanced courses, including statistics, statistical inference, quality control, stochastic processes, reliability theory, queuing theory, sequential decision processes and Monte Carlo simulation.  
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<br>二、指定用書(Text Books)
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<br>“A First Course in Probability” (8th edition) by Sheldon Ross, Pearson Education, Inc. International Edition (Prentice Hall), 2010 or Class Notes by the Instructor
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<br>三、參考書籍(References)
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<br>機率與推論統計原理, 桑慧敏著, first edition, McGraw Hill, 2007.
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<br>四、教學方式(Teaching Method)
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<br>Power point lecture notes or blackboard.
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<br>五、教學進度(Syllabus)
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<br>1.	Role of Probability Theory in the field of Industrial Engineering
<br>2.	Concepts of Randomness, Relative Frequency, Time Average and Limit
<br>3.	Combinatorial Analysis 
<br>4.	Set and Probability Space
<br>5.	Random Variable and Probability Measure
<br>6.	Conditional Probability, Independence, Mutually Exclusive Events 
<br>7.	Discrete and continuous Probability Distributions 
<br>8.	Joint Distributions 
<br>9.	Expectations and Conditional Expectations
<br>10.	Limiting Distributions, Bounds and Approximations 
<br>11.	Transformations and Generation Functions   
<br>12.	Failure Rate and Hazard Functions (optional)
<br>13.	Random Number Generator (optional) 
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<br>六、成績考核(Evaluation)
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<br>Quizzes, Home Work, Midterms, and Final
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<br>七、可連結之網頁位址
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