There are TWO sections of AMS131 being offered in Spring 14. The two sections will run parallel. The intention is for the same material to be covered in the same weeks for the two sections. This page will provide information for both sections.
Section 1: Tuesday and Thursday, 1011:45am, J Baskin Auditorium 101
Section 2: Tuesday and Thursday, 23:45pm, N. Sci Annex 101
Robin Morris
email: rdm @ soe.ucsc.edu  please put "AMS 131" in the subject line
phone: email is preferred; (408) 821 8932 if desperate
Office: Baskin Engineering 357b
Office Hours: Tuesdays and Thursdays 12:301:30pm, or by appointment
Section 1: Chelsea Lofland, clofland@soe.ucsc.edu and Sisi Song, song@soe.ucsc.edu
Section 2: ChengHan Yu, cheyu@soe.ucsc.edu
TA office hours are
All the office hours will be held in Baskin Engineering 358.
Section 1: Tu 23:10pm, E2194; Th 6710pm, E2194; Th 7:308:40pm, E2194
Section 2: M 11am12:10pm, Phys Sciences 130; W 3:304:40pm, Phys Sciences 130
The first section will meet on Wednesday April 2nd, and the last section will meet on Tuesday June 3rd.
There is one holiday this quarter, Memorial Day on Monday May 26th. Sections will not meet on that day.
Tutoring may be available, if a suitable tutor can be found. If you know anyone who might be a good tutor for this course, please let me know.
There is a piazza discussion forum available at https://piazza.com/ucsc/spring2014/ams131
Please address all technical issues with the discussion forum to Vladimir Furman, vfurman @ ucsc.edu
Probability and Statistics, DeGroot and Schervish, 4th Edition, Pearson (2002)
The proposed schedule is below. Note that this may (will?) change depending on how the quarter progresses
Date  Topic  Chapter  Homework  Lecture Notes 
Tue April 1st 
Introduction; 3 views of probability; sample spaces; naive definition; counting; axioms of probability 
1.11.8 
1.4, Q 6, 7, 8 1.5, Q 5, 6, 8, 9, 10 1.6, Q 3, 4, 8 1.8, Q 1, 6, 9 
notes 
Th April 3rd 
Birthday problem; properties of probability; inclusionexclusion; matching problem; independence; conditional probability; Bayes' rule 
1.7,1.10 2.12.3 
1.7, Q 1, 2, 10 1.10, Q 2, 7, 10 2.1, Q 2, 3, 4, 7 2.2, Q 2, 4, 6, 7, 10, 11, 19 2.3, Q 4, 5 
notes 
Tu April 8th 
Law of total probability; conditional probability examples; conditional independence; Monty Hall problem; Simpson's Paradox. 
2.1, 2.3 10.5 
2.1 Q 14 2.3 Q 1, 4, 5, 6 10.5 Q 1, 7 
Please read the textbook section on Simpson's paradox. 
Th April 10th 
Gambler's ruin; random variables; Bernouli; Binomial; Hypergeometric; CDFs; PMFs 
2.4, 3.1 3.3 
2.4 Q 1, 2, 7 3.1 Q 2, 3, 4, 7 3.3 Q 2, 3, 5, 6, 16 
notes 
Tu April 15th  Class will not meet.  
Th April 17th 
Independence; Geometric distribution; expected values; indicator RVs; linearity; Negative Binomial; examples QUIZ 1 
2.2, 5.5 4.1, 4.2 
5.5 Q 5, 6 4.1 Q 1, 3, 4, 5, 8, 11 4.2 Q 2, 3, 8, 9 
(5.5 Q5  we haven't covered the negative binomial yet, but we will) (4.1 Q 8, 11  come back to these once we've covered continuous RVs) (4.2 Q 3  come back to these once we've covered continuous RVs)

Tu April 22nd 
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 
3.2 Q 2, 10 3.8 Q 3, 4, 8, 13 4.3 Q 4, 5, 7 5.4 Q 4, 5, 6, 12 
We only covered up to Poisson distribution/Poisson approximation today; We'll catch up later. 
Th April 24th 
Standard Normal Distribution; Normal normalizing constant; Normal distribution; standardization; Law of the unconscious statistician 
5.6, 4.1 
5.6 Q 3, 5, 8, 10, 11, 14, 16 4.1 Q 1, 3, 8, 11 

Tu April 29th 
Midterm Review 
Review Problems: 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 

Th May 1st 
Midterm Exam (in class)  Read "a mathematician's lament" and join the discussion on Piazza 
I will post solutions to the midterm soon. 

Tu May 6th 
Exponential distribution; memoryless property; MGFs; Bayes rule; Laplace's rule of succession 
5.7, 4.4 
We finished off the Normal distribution today. I'll figure out soon what we're going to cover going forwards. 

Th May 8th 
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 
5.6  see above 4.1, 4.2, 4.3  see above 5.2 Q 6, 7, 10 5.4  see above

Today we covered the proof of LOTUS, the variances of the Poisson and Binomial distributions, and Laplace's rule of succession. 
Tu May 13th 
Expected distance between Normals; Multinomial; Cauchy; covariance; correlation; variance of a sum; variance of Hypergeometric 
1.9, 4.1 4.6, 5.3 
7.2 Q 2, 3, 6 
Today we covered Bayesian inference for the success parameter of a Binomial distribution, and derived the normalizing constant for a Beta distribution with integer parameters. 
Th May 15th 
Transformations; Log Normal; convolutions; Beta distribution; Bayes' Billiards QUIZ 2 
5.6, 5.8 3.8, 3.9 
3.4 Q 2, 4, 8 3.5 Q 2, 3, 7 3.6 Q 2, 3, 9 
Today we looked at two examples of Bayesian inference (including online spelling correction), and then covered joint, marginal and conditional pdfs. We also covered 2D LOTUS. NOTE: quiz 2 has been moved to Tuesday May 20th 
Tu May 20th 
Gamma distribution; Poisson process; BetaGamma; order statistics; conditional expectation
QUIZ 2

5.7, 5.4 7.8, 4.7 
4.6 Q 5, 9, 13 5.3 Q3, 4 
Today we looked at covariance and correlation, and derived the variance of a Hypergeometric distribution. 
Th May 22nd 
Conditional expectation (cont); waiting times  4.7 
3.8 Q 3, 4, 8, 13 3.9 Q 2, 3 
Today we covered transformations of random variables, convolution (sums of RVs) and waiting times when tossing coins. 
Tu May 27th 
Sum of random number of RVs; Inequalities; Law of large numbers; central limit theorem 
6.16.4 
6.2 Q 2, 3, 8 6.3 Q 2, 3, 8 6.4 Q 1 
Today we covered inequalities, law of large numbers and the central limit theorem, and the normal approximation. 
Th May 29th 
Chisquared; Studentt; multivariate normal; Markov chains; transition matrix; stationary distribution QUIZ 3 
8.2, 8.4 5.10, 3.10 
3.10 Q 2, 4, 9, 12 
Today we started Markov Chains, covering multistep transition matrices and the evolution of the PMF over the states. 
Tu June 3rd 
Markov chains (cont).  3.10  notes  
Th June 5th 
Review 
Review Questions 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 review questions are now available.
Inclass review notes, AMS 13101. Inclass review notes, AMS 13102


Monday June 9th 
Section 1 Final Exam, 811am, Baskin Auditorium Section 2 Final Exam, 811am, Baskin Auditorium Section 2 Final Exam, 14pm, BE 358, for those who have a conflict with the morning session. 
Some practice final questions are available. Solutions are now posted. Please do try to solve the problems yourself before looking at the solutions The table of distributions is now available. 

Thursday June 12th 
Section 2 Final Exam, noon3pm 
If you qualify for classroom accomodations because of a disability, please submit your Accomodation Authorization from the Disability Resource Center (DRC) to me during my office hours in a timely manner, preferably within the first two weeks of the quarter. Contact the DRC at 4592089 V, 4594806 TTY.
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