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Back to overview over all lectures...
Probability Spring 2008
News
- Final Grade: If you disagree with your grade or any of my corrections, please come to my office immediately, latest on Wednesday, 25 June, before 3 PM! Thereafter I will not be able to correct any mistake anymore! Thanks!
- Final Exam: The final exam will take place on
- Tuesday, 17 June, 10:10-13:00 (Note that this is one hour longer than usual!)
Regulations:
- open book: any book is allowed
- not allowed are: any telecommunication devices like mobile phones, any laptop with wireless capabilities, any "friend", or any other help from outside...
- covered material: everything covered in class
- Class Evaluation: The class evaluation will be online between June 3 to June 20. I would very much appreciate your feedback, so please spend a couple of minutes to fill out the online form! Thanks!
- Exercise 8 needs to be handed in only on 22 April and not as wronly stated on the Exercise on 15 April!
- Mid-Term Exam: The mid-term exam will take place on
- Tuesday, 15 April, 10:10-13:00 (Note that this is one hour longer than usual!)
Regulations:
- open-book: any book, notes, and exercises are allowed
- not allowed are: any telecommunication devices like mobile phones, any laptop with wireless capabilities, any "friend", or any other help from outside...
- covered material: everything covered in class from Chapter 1 to 3
Course Objectives
This course is an introduction to probability. Its goal is to give the students a profound knowledge about probability theory and some of its important applications. We will cover the following subjects:
- Sample Space and Probability
- probabilistic models and conditional probability
- total probability and Bayes' Rule
- independence
- Discrete Random Variables (RV)
- probability mass function (PMF)
- transforming RVs
- expectations
- joint PMF
- conditioning and independence
- General Random Variables
- probability density function (PDF) and cumulative distribution
function (CDF)
- joint PDF
- Gaussian RVs
- conditioning
- transforming RV
- sum of random number of independent RVs
- least squares estimation
- Stochastic Processes
- Bernoulli process
- Poisson process
- Markov chains
- Limit Theorems
- Markov and Chebyshev inequalities
- weak and strong law of large numbers
- convergence in probability
- central limit theorem
For more detail see the time table below.
We believe that this course is essential for any engineer and we very much hope that a student who finishes the course will feel comfortable with the theory and can apply it.
Prerequisites
The following lectures/topics are recommended:
- basic math from high-school
Instructor
Prof. Stefan M. Moser
Engineering Building IV, Office 727
phone: 03-571 21 21 ext. 54548
e-mail:
Teaching Assistant
In case you would like to discuss some questions in Chinese, you may contact the TA of this class:
- Liu Jen-Yang
Email:
Room: Engineering Building IV, Room 811 (ED811)
Phone: 03-571 21 21 ext. 54571
Office hours: Wednesday, 13:30-15:30, or according to prior appointments
Time and Place
The course is scheduled for 3 hours per week:
- Tuesday, 10:10-12:00, Engineering Building IV, Room 111 (ED111)
- Thursday, 9:00-9:50, Engineering Building IV, Room 111 (ED111)
The course starts on Tuesday, 19 February, and finishes on Thursday,
19 June.
Office Hours
NCTU requests that every teacher offers two hours per week where students may come to ask questions:
- Tuesday, 15:30-17:30, Engineering Building IV, Office 727
However, we would like to encourage you to show up in the teacher's or teaching assistant's office at any time in case you have questions about the class or related subjects. Moreover, we are always available during and after classes.
Textbook
Dimitri P. Bertsekas, John N. Tsitsiklis: "Introduction to Probability," Athena Scientific, Massachusetts, 2002.
For certain topics there will be additional handouts during classes.
Exercises
Every week, an exercise will be distributed in class and also made available online for download. This exercise will consist of several problems that need to be solved at home and handed in during the class of the following week. A model solution will be distributed in class and made available online afterwards.
We believe the exercises to be extremely important and crucial to the understanding of the course. They also serve as a preparation for the mid-term and final exams and we therefore highly recommend to solve them. To pass the course you need to hand in at least 10 exercises.
Exams
There will be one mid-term and one final exam. Both exams are going to last three hours and be open-book. Details about the covered material will be published in due time.
Grading
The grade will be an average of
- the homework (15%),
- the midterm exam (35%), and
- the final exam (50%).
The grade of the homework will not be based on the correctness of the answers, but rather on the effort the student shows in trying to solve them. This course is worth 3 credits.
Special Remarks
The lecture will be held in English.
Time Table
W |
Date |
Topic |
Handouts |
Exercise (due on) |
Solutions |
Comments |
1 |
19 Feb. |
Introduction, set theory, probabilistic models, conditional probability |
Syllabus (Version 2) |
Exercise 1 (26 Feb.) |
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21 Feb. |
Conditional probability |
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2 |
26 Feb. |
Total probability theorem, Bayes' rule, independence |
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Exercise 2 (4 Mar.) |
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28 Feb. |
No lecture (Holiday) |
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----- |
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3 |
4 Mar. |
Counting, discrete RV: PMF |
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Exercise 3 (11 Mar.) |
Solutions 1 |
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6 Mar. |
Functions of RVs, expectations |
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Solutions 2 |
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4 |
11 Mar. |
Joint PMFs, conditioned PMFs |
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Exercise 4 (18 Mar.) |
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13 Mar. |
Independent RVs, continuous RVs: PDF |
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Solutions 3 |
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5 |
18 Mar. |
Continuous RVs: PDF, CDF, Gaussian RV |
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Exercise 5 (25 Mar.) |
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20 Mar. |
Continuous RVs: conditioning, multiple RVs |
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Solutions 4 |
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6 |
25 Mar. |
Continuous RVs: multiple RVs |
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Exercise 6 (1 Apr.) |
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27 Mar. |
Derived distributions |
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Solutions 5 |
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7 |
1 Apr. |
Derived distributions, transform (moment generating function) |
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Exercise 7 (8 Apr.) |
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3 Apr. |
No lecture (Holiday) |
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----- |
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8 |
8 Apr. |
Transform (moment generating function), sum of independent RVs, conditional variance |
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Exercise 8 (22 Apr.) |
Solutions 6 |
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10 Apr. |
Sum of random number of independent RVs |
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Solutions 7 |
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9 |
15 Apr. |
Mid-Term Exam |
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ATTENTION: This is a 3 hours exam: 10:10-13:00 |
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17 Apr. |
Discussion mid-term exam |
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10 |
22 Apr. |
Covariance and correlation, MMSEE |
Handout about Gaussian RVs |
Exercise 9 (29 Apr.) |
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24 Apr. |
MMSEE, LMMSEE, covariance matrices |
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Solutions 8 |
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11 |
29 Apr. |
Covariance matrices, multivariate Gaussian distribution |
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Exercise 10 (6 May) |
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1 May |
Multivariate Gaussian distribution |
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Solutions 9 |
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12 |
6 May |
Multivariate Gaussian distribution, stochastic processes: Bernoulli process |
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Exercise 11 (13 May) |
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8 May |
Poisson process |
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Solutions 10 |
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13 |
13 May |
Poisson process |
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Exercise 12 (20 May) |
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15 May |
Poisson process |
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Solutions 11 |
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14 |
20 May |
Markov process |
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Exercise 13 (27 May) |
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22 May |
Markov process: steady state and stationarity |
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Solutions 12 |
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15 |
27 May |
Markov process: steady state and stationarity, long-term frequency interpretation |
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Exercise 14 (3 Jun.) |
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29 May |
Markov process: short-term transient behavior |
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Solutions 13 |
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16 |
3 Jun. |
Limit Theorems: Markov Inequality, Chebyshev Inequality, Chernoff bound, Jensen's bound, weak law of large numbers , convergence in probability |
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Exercise 15 (10 Jun.) |
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The class evaluation is online until June 20. Please take 5 minutes to fill it out! |
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5 Jun. |
Convergence in probability, strong law of large numbers, almost sure convergence, Borel-Cantelli lemma |
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Solutions 14 |
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17 |
10 Jun. |
Borel-Cantelli lemma, central limit theorem, ergodicity |
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Exercise 16 (12 Jun.) |
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12 Jun. |
Ergodicity |
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Solutions 15, Solutions 16 |
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18 |
17 Jun. |
Final Exam |
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ATTENTION: This is a 3 hours exam: 10:10-13:00 |
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19 Jun. |
Discussion of final exam |
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-||- _|_ _|_ / __|__ Stefan M. Moser
[-] --__|__ /__\ /__ Senior Scientist, ETH Zurich, Switzerland
_|_ -- --|- _ / / Adjunct Professor, National Yang Ming Chiao Tung University, Taiwan
/ \ [] \| |_| / \/ Web: https://moser-isi.ethz.ch/
Last modified: Tue Mar 3 16:47:20 UTC+8 2009
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