機率
Probability
學期
114-2
學分
3
學分
當期課號
515006
永久課號
EEEC10006
開課單位
電機系共同課程
授課教師
李育民
校區
光復
類別
必修
上課時間表
| 節 | 週二 | 週五 |
|---|---|---|
2 09:00–09:50 | 機率 EDB01 | |
5 13:20–14:10 | 機率 EDB01 2 節連堂 | |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
概述
Introduce the basic concepts of probability, random variables, stochastic process, laws of large number, and the central limit theorem.
先修科目
Calculus, Linear Algebra
教學方式
Course Website : E3平台 TA: TBD Office Hour: TBD E-mail: TBD Phone: 03-571-2121 ext. 54586
評分方式
1. Homework assignments and Quizzes: 30% 2. Midterm exam: 35% 3. Final exam: 35% 4. Bonus: up to 5%
課程大綱
- Chapter 1: Sample Space and Probability
- Chapter 2: Discrete Random Variables
- Chapter 3: General Random Variables
- Chapter 4: Further Topics on Random Variables
- Chapter 5: Limit Theorems
- Chapter 7: Markov Chains
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Chapter 1: Sample space and probability, Conditional probability and independence |
| 第 1 週 | Chapter 1: Sample space and probability, Conditional probability and independence |
| 第 2 週 | Chapter 2: Discrete random variables, Probability mass functions (PMFs) |
| 第 2 週 | Chapter 2: Discrete random variables, Probability mass functions (PMFs) |
| 第 3 週 | Chapter 2: Functions of random variables, Expectation and variance |
| 第 3 週 | Chapter 2: Functions of random variables, Expectation and variance |
| 第 4 週 | Chapter 2: Joint PMFs, Conditioning, Independence |
| 第 4 週 | Chapter 2: Joint PMFs, Conditioning, Independence |
| 第 5 週 | Chapter 3: Continuous random variables, Probability density functions (PDFs), Cumulative distribution functions |
| 第 5 週 | Chapter 3: Continuous random variables, Probability density functions (PDFs), Cumulative distribution functions |
| 第 6 週 | Chapter 3: Normal random variables |
| 第 7 週 | Chapter 3: Joint PDFs of multiple random variables, Conditioning for continuous random variables |
| 第 7 週 | Chapter 3: Joint PDFs of multiple random variables, Conditioning for continuous random variables |
| 第 8 週 | Chapter 3: The continuous Bayes' rules |
| 第 8 週 | Chapter 3: The continuous Bayes' rules |
| 第 9 週 | Midterm exam |
| 第 9 週 | Midterm exam |
| 第 10 週 | Chapter 4: Derived distributions, Covariance and correlation |
| 第 11 週 | Chapter 4: Conditional expectation and variance as random variables |
| 第 11 週 | Chapter 4: Conditional expectation and variance as random variables |
| 第 12 週 | Chapter 4: Transforms |
| 第 12 週 | Chapter 4: Transforms |
| 第 13 週 | Chapter 4: Sum of a random number of independent random variables |
| 第 13 週 | Chapter 4: Sum of a random number of independent random variables |
| 第 14 週 | Chapter 5: Markov and Chebyshev inequalities, The weak law of large numbers |
| 第 14 週 | Chapter 5: Markov and Chebyshev inequalities, The weak law of large numbers |
| 第 15 週 | Chapter 5: Convergence in probability, The central limit theorem |
| 第 15 週 | Chapter 5: Convergence in probability, The central limit theorem |
| 第 16 週 | Chapter 5: The strong law of large numbers |
| 第 16 週 | Chapter 5: The strong law of large numbers |
| 第 17 週 | Final exam |
| 第 18 週 | Chapter 7: Discrete-time Markov chains, Steady-state behavior of Markov chains |
| 第 18 週 | Chapter 7: Discrete-time Markov chains, Steady-state behavior of Markov chains |
教科書
Introduction to Probability, Second Edition, Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, 2008.
Office Hours
- 地點
- ED 835
- 時間
- Friday 10:00~11:00
- 聯絡方式
- Email: yumin@nycu.edu.tw Phone: 31274 (03-513-1274)