2 項進行中

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 進行中 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 進行中 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

加入行事曆

選擇訂閱 Google Calendar,或下載通用的 ICS 檔案。

使用 Google Calendar 時,Google 會收到這份課表的公開連結。

機率

Probability

學期
113-2
學分
0 學分
當期課號
515000
永久課號
EEEC10006
開課單位
電機系共同課程
授課教師
李明峻
校區
光復
類別
必修
上課時間表
週二
週五
2
09:00–09:50
機率
ED203(光復)
5
13:20–14:10
機率
ED203(光復)
2 節連堂
6
14:20–15:10

* 根據陽明交大上課時間表所列

概述

The goal of this course is to teach the fundamental theories, results, and applications of probability. Major topics in this course include but are not limited to discrete and continuous random variables, expectation and moments, functions of multiple random variables, covariance and correlation, conditional probability and expectation, Transforms of random variables, limit theorems, and a brief introduction to discrete time Markov chains. Applications and examples of probability theory will include but are not limited to wireless systems and networks and machine learning.

先修科目

Calculus. Some understanding of linear algebra is recommended.

備註

無備註

教學方式

Course materials will be provided on New e3 system.

評分方式

Homework (will include 8~12 problem sets): 30% Midterm Exam: 30% Final Exam: 35% In-class participation and in-class performance: 5%

課程大綱
  • Sample Space and Probability

    Chapter 1

    講授:
    6
  • Discrete Random Variables

    Chapter 2

    講授:
    9
  • Continuous and General Random Variables

    Chapter 3

    講授:
    12
  • Further Topics on Random Variables

    Chapter 4

    講授:
    9
  • Limit Theorems

    Chapter 5

    講授:
    9
  • An Introduction to Discrete-Time Markov Chains

    7.1 Discrete-Time Markov Chains 7.2 Classification of States 7.3 Steady-state behavior

    講授:
    6
  • Selected topics

    Poisson processes, Bayesian statistical inference, fundamental of queuing theory, etc.

    講授:
    3
週次計畫
週次主題
第 1 週

Chapter 1: sample space and probability, conditional probability and independence

2025-02-18(二),2025-02-21(五)
第 2 週

Chapter 2: discrete random variables, probability mass function

2025-02-25(二),2025-02-28(五)
第 3 週

Chapter 2: functions of random variables, expectation and variance

2025-03-04(二),2025-03-07(五)
第 4 週

Chapter 2: joint PMF, conditioning independence

2025-03-11(二),2025-03-14(五)
第 5 週

Chapter 3: continuous random variables, cumulative distribution functions

2025-03-18(二),2025-03-21(五)
第 6 週

Chapter 3: Normal random variables

2025-03-25(二),2025-03-28(五)
第 7 週

Chapter 3: joint PDFs of multiple random variables

2025-04-01(二),2025-04-04(五)
第 8 週

Chapter 3: conditioning for continuous random variables, The continuous Bayes' rules

2025-04-08(二),2025-04-11(五)
第 9 週

Midterm exam

2025-04-15(二),2025-04-18(五)
第 10 週

Chapter 4: Derived distributions, covariance and correlation, conditional expectation and variance as random variables

2025-04-22(二),2025-04-25(五)
第 11 週

Chapter 4: Transforms, sum of a random number of independent random variables

2025-04-29(二),2025-05-02(五)
第 12 週

Chapter 5: Markov and Chebyshev inequalities, The weak law of large numbers

2025-05-06(二),2025-05-09(五)
第 13 週

Chapter 5: Convergence in probability, central limit theorem

2025-05-13(二),2025-05-16(五)
第 14 週

Chapter 5: The strong law of large numbers

2025-05-20(二),2025-05-23(五)
第 15 週

Chapter 7: Concept of stochastic processes, discrete-time Markov chains

2025-05-27(二),2025-05-30(五)
第 16 週

Chapter 7: Steady-state behavior of Markov chains Selected topics: Poisson process, Bayesian statistical inference, fundamental of queuing theory, etc.

2025-06-03(二),2025-06-06(五)
第 17 週

Final exam preparation week.

2025-06-10(二),2025-06-13(五)
第 18 週

Final exam

2025-06-17(二),2025-06-20(五)
教科書

Introduction to Probability, 2nd Edition, D. P. Bertsekas and J. N. Ysitsiklis, Athena Scientific, 2008.

Office Hours
地點
ED 833.
時間
Friday 10:00~12:00
聯絡方式
Email: mingchunlee@nycu.edu.tw 助教:TBD (at ED 821)