ECE 3530 - Engineering Probability and Statistics

Electrical and Computer Engineering Department

Course Info

Lectures: MWF 9:40 AM - 10:30 AM in WEB L103

Instructor: Tolga Tasdizen
Email: tolga@sci.utah.edu
Office: WEB 3887
Office Hours: Mondays and Wednesdays 10:30 AM - 12:00 PM

TAs: Mojtaba Seyedhosseini (mseyed@sci.utah.edu) and Jiyong Son (smirage9@gmail.com)
Study sections: Mondays 2-3:30 PM in WEB L120 and Thursdays 3-5 PM in WEB L110

Required Textbook: Probability & Statistics for Engineers and Scientists, 8th Edition
                                 Walpole, Myers, Myers and Ye
                                 Prentice Hall, Upper Saddle River, NJ 07458
                                 ISBN: 0-13-187711-9 

Prerequisite: MATH 1220 (Calculus II)

Detailed course information and syllabus (pdf)

Important Notices

PART I
(Posted 1/5) Read Chapter 1: This is introductory material, you don't have to dwell on the details too much.
(Posted 1/5) Read Sections 2.1 through 2.5 in Chapter 2: We will be covering this material in class during the next couple of weeks.
(Posted 1/23) Read the rest of Chapter 2

PART II
(Posted 2/13) Read Chapter 3.1-3.3 and Chapter 4.1 up to end of example 4.5 and Chapter 4.2 up to end of example 4.12
(Posted 2/16) Read Section 5.1-5.3 and 6.1-6.4
(Posted 2/23 Read Sections 6.6-6.9 and Section 3.4
(Posted 2/23) Read Sections 4.2-4.3

PART III
(Posted 3/26) Read Chapter 8 (except section 8.8) also read Section 4.4
(Posted 4/2) Read Chapter 9.1-9.4, 9.8, 9.12
(Posted 4/9) Read Chapter 10.1-10.7
(Posted 4/12) Read Chapter 11.1-11.5

Lecture Notes and Supplementary Material

PART I
(Posted 1/5) Slides on applications of probability and statistics
(Posted 1/5) Notes on introduction to probability and statistics 
(Posted 1/5) Notes on basic probability 
(Posted 1/5) Some more examples for basic probability and Venn diagrams
(Posted 1/13) Anology to digital logic
(Posted 1/13) One more example on Venn diagrams and probability
(Posted 1/13) Notes on counting and combinatorics
(Posted 1/13) More combinatorics examples
(Posted 1/23) Conditional probability
(Posted 1/23) Conditional probability continued
(Posted 1/25) Spy game, optional: detailed analysis of spy game
(Posted 1/25) Bayes Rule

PART II
(Posted 2/13) Random variables
(Posted 2/13) Expectation, mean
(Posted 2/13) Variance
(Posted 2/13) Binomial distribution
(Posted 2/16) Normal (Gaussian) distribution
(Posted 2/23) Some other distributions
(Posted 2/23) Joint discrete random variables
(Posted 2/23) Joint continuous random variables
(Posted 3/1) Covariance of random variables
(Posted 3/1) Linear combinations of random variables

PART III
(Posted 3/26) Chebyshev's theorem
(Posted 3/26) Introduction to statistics
(Posted 3/26) Central limit theorem, sampling distributions
(Posted 4/2) Examples using the different tables
(Posted 4/2) Confidence intervals
(Posted 4/9) Hypothesis testing
(Posted 4/9) Hypothesis testing continued
(Posted 4/12) Linear regression
(Posted 4/12) Inference on linear regression parameters

Exams & Practice Exams


EXAM POLICY: Exams will be closed book. You will be allowed 1 page of notes (front and back) but it must be handwritten (no photocopying, shrinking, etc.). Calculators can be used but no laptops allowed.

Midterm 1 practice exams:
 Practice exam 1 and solution
 Practice exam 2 and solution

Midterm 1 Solution

Midterm 2 practice exams:
Practice exam 1 and solution
Practice exam 2 and solution

Topics for Midterm 2:
    All of Chapter 3, Sections 1-3 of Chapter 4, Sections 1-3 of Chapter 5, Sections 1,2,3,4,6,7,9 of Chapter 6.
    All class notes posted in Part II above excluding
        -pages 13 and 14 of the notes on "Joint continuous probability distributions" (multivariate Gaussian)

Midterm 2 solution

Final practice exams
Practice exam 1 and solution
Practice exam 2 and solution

Topics for the final: Section 4.4, Chapter 8 (except section 8.8), Chapter 9.1-9.4, 9.8, 9.12, Chapter 10.1-10.7, Chapter 11.1-11.5. All class notes unless otherwise noted above.

Note the final is not comprehensive, it focuses on the topics since the last midterm. However, you might need certain information from previous topics. So you are allowed to bring the cheat sheets for midterms 1 & 2 as well as a new sheet for the final.

Final exam solution

Homeworks and Solutions 

Assignment 1 due January 20 - solutions
Assignment 2 due January 27 - solutions
Assignment 3 due February 3 - solutions
Assignment 4 due February  24 - solutions
Assignment 5 - due March 2 - solutions
Assignment 6 - due March 9 - solutions
Assignment 7 - due April 6 MATLAB data file for Question 1 - Solutions
Assignment 8 - due April 13 - solutions
Assignment 9 - due April 23 - solutions