ANNOUNCEMENTS:
Thursday, June 7th:
I have posted solutions to the suggested revision problems, solutions to the practice final problems, and solutions to the final exam from the last time I taught this course.
Tuesday, June 5th:
I have posted suggested revision problems, practice final problems, and the final exam from the last time I taught this class. Solutions coming soon.
Thursday May 31st:
I have posted model solutions to quiz 2 and quiz 3.
Friday May 25th:
There will be an inclass quizz on Thursday, May 31st as originally scheduled.
Wednesday May 23rd:
The take home quiz is still due at the start of class tomorrow.
There will also be an inclass quiz tomorrow.
Friday May 11th:
Quiz 2 has been moved to Tuesday, May 22nd.
Tuesday May 8th:
7:35am  according to http://ucsc.edu/advisory campus is open, and CLASS WILL MEET TODAY.
Sunday May 6th:
Model solutions for the midterm are posted
Tuesday May 1st:
solutions to midterm review problems are posted
solutions to the previous midterm are posted
Monday April 30th:
1. Office hours will be held on Tuesday (1st May) this week, and not on Thursday (3rd May).
2. Currently, I intend for class to be held tomorrow. If I hear that access to campus is blocked, I will try to update this announcement.
Saturday April 28th:
For the midterm, you may bring one page of notes, 8.5x11, double sided.
Friday April 27th:
I have posted a set of midterm review questions (the circled ones in the document). Please try to work through them carefully. I will post solutions sometime next week.
Thursday April 26th:
I have posted a set of review notes and the midterm from last time I taught this class. I will post solutions to this midterm early next week. Please note that this midterm was considered difficult, and I will try to make this year's midterm more closely resemble the homework problems.
Wednesday April 11th:
Copies of the homework problems for those who have the alternative textbook are now available.
Tuesday April 3rd:
 Sections and TA office hours will start next week (week beginning Monday, April 9th)
 I have a few add codes available. I will be dealing with those who want to add at the end of the lecture on Tuesday, April 10th.
Tuesday and Thursday, 9:50  11:25am, Baskin Auditorium 101
Robin Morris
email: rdm @ soe.ucsc.edu  please put "AMS 131" in the subject line
phone: email is preferred; (650) 669 7159 if desperate
Office: Baskin Engineering 361b
Office Hours: Thursdays 11:30am  12:30pm, or by appointment
Arthur Lui, alui2@ucsc.edu
Matt Heiner, mheiner@ucsc.edu
TA Office Hours are:
Sisi Song  Monday 34pm BE 312C/D
Arthur Lui  Tuesday 8:309:30am, BE 121
Matt Heiner  Wednesday 11amnoon, BE312C/D
01A  W 8:009:05am  Matt Heiner
01B  W 9:2010:25am  Matt Heiner
01C  Th 8:309:35am  Arthur Lui
01D  F 12:001:05pm  Sisi Song
All Sections will be in Engineering 2, Room 194
The MSI instructor this quarter is Shiva Ashok, smanjaku@ucsc.edu. Meeting times are
We will be using Piazza as the discussion forum for this class.
The main course text will be
"Introduction to Probability", J.K. Blitzstein and J. Hwang.
An alternate text is
Probability and Statistics, DeGroot and Schervish, 4th Edition, Pearson (2002)
Both texts cover the course material, but not in the same order. We will be following Blitzstein and Hwang more closely. If you plan on taking AMS 132, you should consider DeGroot and Schervish.
The proposed schedule is below. Past experience is that this will change as the quarter progresses. Subjects in strikethrough are those most likely to not be covered if time is short.
Date  Topic  DG&S  B&H  Homework  Lecture Notes 
Tue April 3rd 
Introduction; 3 views of probability; sample spaces; naive definition; counting; axioms of probability 
1.11.8  1.2, 1.3, 1.6 
Section 1.9, Questions 1, 2, 5, 8, 21, 22, 27, 29, 33, 42, 43 

Th April 5th  Review of math prerequisites  notes  
Tu April 10th 
Birthday problem; properties of probability; inclusionexclusion; matching problem; independence; conditional probability; Bayes' rule 
1.7,1.10 2.12.3 
1.4, 1.6 2.5, 2.1, 2.3 
Section 1.9 Questions 45, 48, 51 
We did not cover independence, conditional probability or Bayes rule. We will cover these topics on Thursday. 
Th April 12th 
Law of total probability; conditional probability examples; conditional independence; Monty Hall problem; Simpson's Paradox. 
2.1, 2.3 10.5 
2.3, 2.7 2.8 
Chapter 2, Questions 1, 2, 5, 6, 11, 30, 35 
We did not cover the Monty Hall problem or Simpsons' Paradox. Please read the relevant sections of the textbook. 
Tu April 17th 
Gambler's ruin; random variables; Bernouli; Binomial; Hypergeometric; CDFs; PMFs 
2.4, 3.1 3.3 
2.7, 3.1, 3.3 3.4, 3.6, 3.2 
Chapter 2, Questions 42, 47, 51 Chapter 3, Question 2 
We did not cover the Hypergeometric distribution. We will do that next time. 
Th April 19th 
Independence; Geometric distribution; expected values; indicator RVs; linearity; Negative Binomial; examples QUIZ 1 
2.2, 5.5 4.1, 4.2 
3.8, 4.3, 4.1 4.4, 4.2 
Chapter 3, Questions 5, 9, 10, 21, 40, 42

We covered Hypergeometric, CDFs, PMFs from last time, and the quiz. This means that we're running about a class behind the schedule here. This is typical, and we'll adjust as we go along. 
Tu April 24th 
Poisson distribution; Poisson approximation; discrete vs. continuous; PDFs; variance; standard deviation; Uniform distribution; universality 
3.1, 3.2, 3.8 3.3, 4.3, 5.4 
4.7, 4.8, 5.1 4.6, 5.2, 5.3 
Chapter 3, Questions 40, 42 Chapter 4, Questions 3, 8 (parts a and c), 16 (part a), 20 (parts a and b), 22, 24, 30, 34 
Again, we're about a class behind the schedule.

Th April 26th 
Standard Normal Distribution; Normal normalizing constant; Normal distribution; standardization; Law of the unconscious statistician 
5.6, 4.1  5.4, 4.5 
We're still a class behind. 

Tu May 1st 
Midterm Review 
(previous review notes) practice midterm questions  these are taken from D&S. They are the circled ones in the linked document. 1.12 Q 3, 4, 6, 9 2.5 Q 3, 5, 13, 16, 20, 23, 28 3.11 Q 1, 4, 9 4.1 Q 7 4.3 Q 9 4.9 Q 4 5.11 Q 5, 11, 12, 13, 18, 20 solutions to the practice midterm questions previous midterm (note that this midterm was more difficult than anticipated) solutions to the previous midterm I will post solutions next week, after you have had a chance to try the problems for yourselves. 

Th May 3rd 
Midterm Exam (in class) 
You can bring one page of notes, 8.5x11, double sided 

Tu May 8th 
Exponential distribution; memoryless property; MGFs; Bayes rule; Laplace's rule of succession 
5.7, 4.4 
5.5 6.16.4 
Today we covered the Normal Distribution. 

Th May 10th 
Use of MGFs; moments of Exponential and Normal; Sums of Poissons; joint, conditional and marginal distributions; 2D LOTUS; examples 
4.4, 5.6 3.43.6 
6.5, 6.6 7.1, 7.2 
Chaper 4, Q 1, 2, 16(b), 57, 60 Chapter 5, 1(a), 5, 10, 22, 24, 25, 31, 36 Chapter 8, 4, 6, 11 
Today we covered the General Normal Distribution; the proof of the law of the unconcious statistician; transformations 
Tu May 15th 
Expected distance between Normals; Multinomial; Cauchy; covariance; correlation; variance of a sum; variance of Hypergeometric 
1.9, 4.1 4.6, 5.3 
7.3, 7.4  Chapter 8, 21, 22, 23, 26(ad) 
Today we covered more on transformations. Convolutions (sums of RVs). Bayes Rule and Laplace's rule of succession. 
Th May 17th 
Transformations; Log Normal; convolutions; Beta distribution; Bayes' Billiards QUIZ 2 
5.6, 5.8 3.8, 3.9 
8, 8.2 8.3 
Chapter 8, 29, 40 
Today we covered more on using Bayes Theorem, and the Beta distribution. Note that Quiz 2 has been rescheduled and will be held on Tuesday, May 22nd 
Tu May 22nd 
Gamma distribution; Poisson process; BetaGamma; order statistics; conditional expectation QUIZ 2

5.7, 5.4 7.8, 4.7 
5.6, 8.4 8.5, 8.6, 9 
Chapter 7, Q 1, 2, 6, 7, 16, 31 
Today we covered joint, marginal and conditional distributions for continuous random variables; 2D LOTUS; Covariance and the variance of a sum of random variables.

Th May 24th 
Conditional expectation (cont);waiting times  4.7  9.1  Ch 7, Q 39, 40, 49

Today we continued with covariance and correlation and the covariance of independent and nonindependent random variables. 
Tu May 29th 
Sum of random number of RVs; Inequalities; Law of large numbers; central limit theorem 
6.16.4 
10, 10.2 10.3 
Ch 7, Q 72, 73 Ch 10, Q 1, 17

Today we covered the multivariate normal and the bivariate normal; the Law of Large Numbers and the inequalities used in proving the Weak LLN. As I mentioned in class, I had a missing negative sign in the derivation of the conditional distribution of one variable in the bivariate normal. This is corrected in the notes.

Th May 31st 
Chisquared; Studentt; multivariate normal; Markov chains; transition matrix; stationary distribution QUIZ 3 
8.2, 8.4 5.10, 3.10 
10.4, 7.5 11, 11.1, 11.3 
Ch 10, Q7, 18, 21 
Today we covered more inequalities, and the central limit theorem.

Tu June 5th 
Markov chains (cont).  3.10  Ch 11, Q4  
Th June 7th 
Review 
Suggested revision problems  see this document, and look at problems 1.12 Q 4, 11 2.5 Q 2, 5, 17, 20, 21, 24, 26, 36 3.11 Q 4, 5, 8, 10, 16, 21, 27, 28, 29 4.9 Q 5, 8, 11, 14, 22 5.11 Q 7, 8, 12, 20 6.5 Q 9, 10, 12 solutions to the suggested revision problems Also, some practice final questions solutions to the practice final questions And the final exam from when I last taught this class. Note that there is a typo in question 1. It should read
solutions to the final from last time
Solutions will be posted soon are now posted. 

Wed June 13th 
Final Exam, noon3pm, Baskin Auditorium

solutions to the final 
Academic Integrity
You are reminded of the University's Policy on Academic Integrity. I hope not to have to remind any of you individually about this policy.
"In Praise of Lectures" gives some ideas about the purpose of lectures, notetaking, and not being afraid to ask questions. It's target audience is more advanced mathematics students, but everything it says applies here. Think about the ideas it presents, and you will have a better time in AMS7 lectures. In particular