1. 本課程將運用微積分,若同學尚未具備相關基礎,建議預先觀看以下台大開放式課程影片(總時長約 6 小時),內容涵蓋本課程所需主題(影片連結:https://ocw.aca.ntu.edu.tw/courses/103S121):
(1) 極限概念與自然對數(影片前30分鐘)
(2) 導函數的基本性質 (影片前40分鐘與後30分鐘)
(3) 連鎖法與其應用
(4) 反導函數與線性逼近(影片前20分鐘)
(5) 黎曼和與定積分
(6) 積分技巧-變換變數法 (影片前30分鐘)
(7) 多變數函數的積分-二重積分
觀看以上內容能建立課程所需基礎,同學亦可依個人需求尋找其他學習資源。
2. 本課程之影片將統一發布於 NTU COOL 平台,同學需觀看所有課程影片,並完成線上作業。
3. 期中考與期末考將於各校考場以「實體」方式舉行,請同學務必確認自己能於表定日期與時間出席應考。

台灣大學教授 葉丙成 授課
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

Probability and Stochastic Processes - A Friendly Introduction for Electrical and Computer Engineers,, JOHN WILEY & SONS;LTD ISBN : 9780471452591