General Course Information  Course Content  Required Background  Software 
Textbooks  Required Work  Grading  Detailed Course Schedule 
Linda Chen 
Ned Cramer 
chenavx@bc.edu 
cramered@bc.edu 
OH: Tuesday 10PMmidight 
OH: Thursday 2:454:15 
My colleague Bob Muller calls this policy the
'laptopfree classroom'. (For 'laptop', read 'laptop and
smartphone'.)
A successful class requires your attention,
engagement, and participation. You need to be prepared
to ask and answer questions during the lectures, and to
attend to the questions and answers of your fellow students
and of the instructor. That screen open to your email
or Facebook page distracts not only you, but the students
sitting behind you. For this reason, open laptops are
not permitted in the classroom, unless they are part
of some planned activity for which your computer is
required.
You say you're taking notes on that
laptop instead of shopping on Amazon? You should be aware
that (a) it is very difficult to take notes for this class
on a computer, given the large number of mathematical
symbols, formulas and diagrams that we use; and (b) taking
notes by hand is better for you. It is
acceptable to take notes on a tablet computer with a stylus.
Exceptions to this rule will be made for the
rare instances of inclass activities that require students
to use their computers. There will be one such activity on
the first day of class.
Date 
Topic 
Handouts and Lecture Notes 
Assignments

Week 1 January 1618 
A cointossing
experiment. Simulations in Python and matplotlib. 
The
inclass exercise for the first day Installing and using the software Cointossing experiments (heavily commented Python code to demonstrate the plotting and numerical tools) How to prepare the homework (a mockup homework assignment). The 'hot hands' paper by Gilovich, Vallone and Tversky Nonrequired reading: Is there such a thing as an unfair coin?No, say these Statistics professorsYes, claims this guy (along with disturbing photographic instructions for how to make such a coin). Maybe they're all unfair. 
Assignment
1, due January 24. 
Week 2 January 2325 
Discrete probability
spaces, Independent events (2.1,2.2) 
Assignment 2, due January
31. 

Week 3 January 30February 2 
Counting (2.3) 
Graphical
solution to the birthday problem. 
Assignment 3, due February
8. The birth date data for 20002003. 
Week 4 February 6February 8 
Discrete random variables. (Chapter 3)  Assignment 4, due February
24. 

Week 5 February 13February 15 
More discrete random variables. Geometric distribution. Poisson distribution.  Python code using cumulative distribution function to simulate roll of two dice.  
Week 6 February 20February 22 
Expected value. 

Week 7 February 28March 2 
First midterm. Conditional probability and Bayes's Theorem. 
The midterm with
solutions. 

Spring break 

Week 8 March 14March 16 
Continuous sample spaces
and continuous random variables. 
Simulation
of Buffon Needle problem 
Assignment 5. Part 1 is
due March 20, Part 2 March 27. (The supporting files are on the Canvas site.) 
Week 9 
Variance, Markov's and
Chebyshev's inequalities 
Simulation
of exponential and Poissondistributed random
variables 
Assignment 6, due Monday
April 2. 
Week 10 (just one class:) 
Normal distribution, Law of Large Numbers and Central Limit Theorem  Central
Limit Theorem demo, showing convergence of
binomial and sums of exponential random variables to
standard normal density. Polling demo, graphical display of confidence intervals in repeated simulations of poll. 
Assignment 7, due Tuesday,
April 10 
Week 11 
More on Central Limit Theorem (Chapter 5)  
Week 12 
Second midterm 
heights.py
demonstrates normal distribution of realworld data probplots.py demonstrates probability plots The second midterm, with solutions. 
Assignment 8, due April 26 
Week 13 
Markov Chains (Chapter 9) 
Simulating a Markov chain (with one line of code!) 
Assignment 9,
due May 3 
Week 14 
Markov Chains 

Week 15 
Review 