MATH-UA.0233.001: Theory of Probability (Spring 2013)

Goals and topics

An introduction to the mathematical treatment of random phenomena occurring in the natural, physical, and social sciences. Axioms of mathematical probability, combinatorial analysis, binomial distribution, Poisson and normal approximation, random variables and probability distributions, generating functions, the Central Limit Theorem and Laws of Large Numbers.



WWH 1302, Tuesday and Thursday, 9:30am – 10:45am (75 mins).
Attendance of lecture is important: there will often be activities such as worksheets which you will do in pairs or small groups. These will allow you to grapple with concepts and explain them to each other.
For students lying on grade boundaries I will take lecture participation into account.

Office Hours

Tuesday 3pm-5pm in Room 926 WWH. Office hours are also available by appointment (please make arrangements via e-mail).


Room TBA, Friday, 3:30pm – 4:45pm (75 mins).

Text book

A First Course in Probability by Sheldon Ross. The books Introduction to Probability Theory by Hoel, Port and Stone; and Probability and Statistics by Morris DeGroot and Mark Schervish are optional as reference texts. The book Introduction to Probability by C. M. Grinstead and J. L. Snell is available free online.


MATH-UA 122 Calculus II and MATH-UA 123 Calculus III with a grade of C or better and/or the equivalent.


Course materials and other details will be published on NYU classes.


For free peer tutoring see the University Learning Center website here.


Solving a lot of problems is an extremely important part of learning probability. Homework will be assigned weekly on Thursdays, to be handed in at the start of next Thursday lectures.
In order to get credit, the homework must be submitted to the instructor by the beginning of class on the specified due date. In fairness to the other students in the course, late homework will generally not be accepted. We will, however, drop the lowest homework score in computation of final grades. Please talk to the instructor in cases of emergency.


I encourage you to study in groups. Get to know others in class. If you have no-one to study with, I can help you find someone.All resources (including the textbooks, the instructor, and computational devices) may be utilized. However you must write up homework in your own words, and understand what you write. Plagiarism (in homework or in exams) is a serious offense (see NYU CAS Academic Policies).


Quizzes will be given every ... There will be - quizzes. Quizzes will start at the beginning of class. We will drop the lowest quiz.


In-class midterm and final; collaboration is forbidden. The midterm exam will take place in class on Thursday, April 4, 2012 at 9:30am-10:45am. The final exam will take place in class on Thursday, May 16, 2012 at 8am-9:50am.


Grades will be computed by a weighted average:

Homework 10%
Quizzes 15%
Midterm 25%
Final 50%
Total 100%

Final scores will be converted to letter grades beginning with the following scale:

93 A
90 A-
87 B+
83 B
80 B-
75 C+
65 C
50 D

As for a curve, these cutoffs might be adjusted, but only in the downward direction (to make letter grades higher).

Timeline: (approximate)

Week Date Due Content

1 Tu Jan. 29 Combinatorial Analysis and Story proofs.
Th Jan. 31

2 Tu Feb. 5 Axioms and properties of Probability, Birthday problem.
Th Feb. 7

3 Tu Feb. 12 Conditional Probability, LoTP, Monty Hall, Simpson's paradox
Th Feb. 14 Feb 15 is last day to drop courses not receiving a grade of "W".

4 Tu Feb. 19 Gambler's ruin, Random variables and their distributions,
Th Feb. 21 Expectations, Indicator random variables.

5 Tu Feb. 26 Poisson Distribution, Discrete vs.~continuous,
Th Feb. 28 Uniform Distribution.

6 Tu Mar. 5 Normal Distribution, location, scale and LOTUS
Th Mar. 7

7 Tu Mar. 12 Exponential Distribution, MGFs
Th Mar. 14

8 Tu Mar. 19 No classes. Spring break.
Th Mar. 21 No classes. Spring break.

9 Tu Mar. 26 Joint, Conditional and Marginal Distributions, Multinomial
Th Mar. 28 and Cauchy distributions, Covariance and correlation.

10 Tu Apr. 2 Midterm Review
Th Apr. 4 In class Midterm Exam

11 Tu Apr. 9 Transformations and Convolutions,
Th Apr. 11 Beta and Gamma Distributions, Poisson process

12 Tu Apr. 16 Order statistics and conditional distribution
Th Apr. 18

13 Tu Apr. 23 Inequalities, Law of Large numbers and
Th Apr. 25 Central Limit Theorem

14 Tu Apr. 30 Chi-square, Student's t and
Th May 2 multivariate Normal distribution, Markov chains.

15 Tu May 7 Markov chains and random walks.
Th May 9 Final Exam review.

16 Th May 16 Final Exam: 8am-9:50am