113年第2學期-0743 機率與統計 課程資訊

評分方式

評分項目	配分比例	說明
課堂參與及作業	50
期中課程評量成績	25
期末課程評量成績	25

教育目標

1. Experiments, Models, and Probabilities 1) Applying Set Theory to Probability 2) Conditional Probability 3) Independence 2. Basics of Random Variables 1) Definitions 2) Probability Mass Function (PMF) 3) Families of Discrete Random Variables 4) Cumulative Distribution Function (CDF) 5) Probability Density Function (PDF) 6) Families of Continuous Random Variables 3. Random Variables and Expected Value 1) Conditional Probability Mass/Density Function 2) Probability Models of Derived Random Variables 3) Variance and Standard Deviation 4) Expected Value of a Derived Random Variable 4. Multiple Random Variables 1) Joint Cumulative Distribution Function 2) Joint Probability Mass/Density Function 3) Marginal PMF/PDF 4) Functions of Two Random Variables 5) Conditioning by a Random Variable 6) Independent Random Variables 5. Sums of Random Variables 1) Expected Values of Sums 2) PDF of the Sum of Two Random Variables 3) Moment Generating Functions 4) MGF of the Sum of Independent Random Variables 5) Random Sums of Independent Random Variables 6) Central Limit Theorem 7) Law of Large Numbers

基本資料

選修課，學分數：0-3
上課時間：四/6,7,8,12,13[遠距課程]
修課班級：共選修4(工學院開)
修課年級：4年級以上
選課備註：教育部補助臺灣大專院校人工智慧學程聯盟，開設學校：台灣大學，遠距課程，上課時間：週四下午 14:30-17:30 週四晚上 20:00-22:00。

參考書目

Probability and Stochastic Processes - A Friendly Introduction for Electrical and Computer Engineers," Second Edition