### Class Schedule and HW Assignments

###### GS = Grinstead and Snell's Introduction to Probability
Normal CDF Table

Week Date Topics Sections Practice Problems
(don't turn in)

1 6/22 Course Introduction; What is Probability?;
Introduction to Counting
M: 1.1-1.2
GS: 3.1-3.2
M, p.36:
1.1, 1.2
GS, p.88:
1, 2, 5, 12, 13

2 6/25 Ordered and Unordered Sets M: 1.3-1.6 M, p.36: 1.3, 1.6
p.12: 1
p.20: 1, 2
6/27 Induction; Binomial and Multinomial Coefficients M: 1.8;
(above)
M, p.36: 1.7, 1.8, 1.9, 1.15
6/29 Stars and Bars; License Plate Problems M: 1.7, 1.9 M, p.36: 1.11, 1.14
Homework Due 7/6 (Solutions)

3 7/2 Independence and Conditional Probability M: 2.1-2.2 M, p.109: 2.1, 2.4, 2.7
7/3(x) More on Conditional Probability; Disjoint Events M: 2.2-2.3 M, p.109: 2.9, 2.13
7/6 Bayes' Theorem; Classical Probability Problems M: 2.4-5
M, p.109: 2.14, 2.15, 2.22
Homework Due 7/11 (Solutions)
Exam 1 Practice Problems GS p.88: #3, 7, 13, 14, 15
GS p.113: #8, 9, 16, 17, 19, 20, 35
GS p.150: #1, 2, 3, 4, 5, 9, 14, 18

4 7/9 Midterm Review
7/11 The R Programming Language Install R AND
Install RStudio
7/13 Intro to Discrete Random Variables and
Probability Distributions; Expected Value
M: 4.1, 4.4-5, 4.6.1, 3.1
GS: 1.2
M, p.165: 3.3
Homework Due 7/18 (Solutions)

5 7/16 (Discrete) Expected Value and Games M: 3.1 M, p.165: 3.2, 3.4-5
7/17(x) R Practice (optional)
7/18 (Discrete) Variance and Standard Deviation M: 3.2-3 M, p.165: 3.6, 3.7, 3.8
7/20 Hypergeometric and Poisson Distributions M: 4.7 M, p.222: (4.5,) 4.13, 4.16, 4.17
Homework Due 7/25 (TeX)
(Solutions)
Discrete Distributions Practice Problems GS p.197: #1, 6, 7, 8, 13, 14, 16, 18, 21
Expected Value Practice Problems GS p.246: #1, 2, 3, 4, 6, 8, 16, 23
Variance Practice Problems GS p.263: #1, 3, 4, 7, 9, 10, 12, 23

6 7/23 Poisson Approximation of the Binomial Distribution;
Continuous Distributions: Uniform
GS: 5.1
M: 4.2-4.3
GS, p.197: #13, 14, 16
7/25 Continuous Expected Value and Variance;
The Exponential Distribution
GS: 6.3
M: 4.6, 4.8
GS, p.277: #1, 2, 3, 4
7/27 The Exponential and Normal Distributions GS: 5.2
M: 4.8
GS, p.209: #25-30
(M, p.222: 4.22-23)
Homework Due 8/1 (TeX)
(Solutions)

7 7/30 Inequalities of Markov and Chebyshev;
The Weak Law of Large Numbers
GS 8.1-8.2
Class Notes
GS, p.312: #5-8
GS, p.320: #2, 4, 5
8/1 Midterm Review
8/3 Convolutions GS 7.1-7.2 GS, p.289: #2, 3, 5;
GS, p.300: #2-5

8 8/6 The Central Limit Theorem GS 9.1 GS, p.338: #1-6
8/8 The Central Limit Theorem GS 9.2-3 GS p.352: #1, 3-7
GS p.361: #4, 5, 9
8/10 Introduction to Markov Chains GS 11.1 GS p.413: #2, 4, 5, 7, 11
Homework Due 8/15 (TeX)
(Solutions)

9 8/13 Absorbing Markov Chains GS 11.2 GS p.422: #1, 2, 3, 5
8/15 Absorbing Markov Chains II;
Ergodic and Regular Markov Chains
GS 11.2-3 GS p.422: #6, 9
GS p.442: #1, 3
8/17 Ergodic and Regular Markov Chains II GS 11.3 GS p.442: #5, 12, 14, 24
Homework Due 8/22 (TeX)

10 8/20 Class Cancelled
8/22 Final Review

#### Important Dates

Date Event
Friday, June 22: First lecture
Tuesday, July 10: Midterm Exam 1 (4:30-6:30 pm, Kemeny 007)
Monday, July 23: Lab Assignment 1 due in class
Thursday, August 2: Midterm Exam 2 (4:30-6:30 pm, Kemeny 007)
Tuesday, August 7: Final day to withdraw from the course
Friday, August 10: Lab Assignment 2 due in class
Wednesday, August 22: Final lecture
Saturday, August 25: Final Exam (8-11 am, Kemeny 007)

C. Coscia
Last updated August 20, 2018