Instructor: Tolga Tasdizen

Email: tolga@sci.utah.edu

Office: WEB 3887

Office Hours: Mondays 10:30 AM - 12 PM and Tuesdays 11 AM -12 PM and 2 PM -3 PM

TAs: Yu-Pin Hsu (u0789228@utah.edu) and Matt Hales (matt.ee.hales@utah.edu)

Study sections: Wednesdays 3 - 5 pm WEB L114

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)

(Posted 12/11) Read Chapter 1: This is introductory material, you don't have to dwell on the details too much.

(Posted 12/11) Read Sections 2.1 through 2.5 in Chapter 2: We will be covering this material in class during the first couple of weeks.

(Posted 1/17) Read the rest of Chapter 2

PART II

(Posted 2/6) 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 2/13) Read Section 5.1-5.3 and 6.1-6.4

(Posted 2/19) Read Sections 6.6-6.9 and Section 3.4

(Posted 3/1) Read Sections 4.2-4.3

PART III

(Posted 3/22) Read Chapter 8 (except section 8.8) also read Section 4.4

(Posted 4/1) Read Chapter 9.1-9.4, 9.8, 9.12

(Posted 4/2) Read Chapter 10.1-10.7

(Posted 4/15) Read Chapter 11.1-11.5

(Posted 12/11) Slides on applications of probability and statistics

(Posted 12/11) Notes on introduction to probability and statistics x

(Posted 12/11) Notes on basic probability

(Posted 12/11) 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 1/18) Conditional probability

(Posted 1/19) Conditional probability continued

(Posted 1/23) Spy game, optional: detailed analysis of spy game

(Posted 1/23) Bayes Rule

(Posted 2/4) Monty Hall Matlab code

PART II

(Posted 2/6) Random variables

(Posted 2/6) Expectation

(Posted 2/6) Variance

(Posted 2/13) Binomial distribution

(Posted 2/13) Normal (Gaussian) distribution

(Posted 2/13) Some other distributions

(Posted 2/19) Joint discrete random variables

(Posted 2/19) Joint continuous random variables

(Posted 3/1) Covariance of random variables

(Posted 3/1) Linear combinations of random variables

PART III

(Posted 3/22) Chebyshev's theorem

(Posted 3/22) Introduction to statistics

(Posted 3/22) Central limit theorem, sampling distributions

(Posted 4/2) Examples using the different tables

(Posted 4/2) Confidence intervals

(Posted 4/2) Hypothesis testing

(Posted 4/2) Hypothesis testing continued

(Posted 4/15) Linear regression

(Posted 4/15) Inference on linear regression parameters

(Posted 5/15) Linear essay attachment

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 solutions

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)

Chapter 7 of leadership essay

Midterm 2 solutions

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.

Reflective essay for final focuses in certain information

Final exam solutions

Assignment 2 paper topics Assignment 2 due January 25 - solutions

Assignment 3 due February 1 - solutions

Assignment 4 due February 22 - solutions

Assignment 5 due March 1 - solutions

Assignment 6 due March 8 - solutions

Assignment 7 due April 5 Q1data.mat ... solutions

Assignment 8 due April 12 - solutions

May 13 - argumentative essay topics Assignment 9 due April 22 - solutions