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MATH 2030 3.0AF (Fall 2008)
Announcements and documents will be posted here as they
- I am now out of the country. The remaining lectures are being
given by Prof. Kuznetsov instead. We will set the exam together. For
example, I will probably set all the questions for the material I
- Prof. Kuznetsov is maintaining his own webpage for his
portion of the course. See
Prof. Kuznetsov's 2030 webpage.
- Our course will have 7 classes after classes resume. This means
material will be trimmedfrom the end, and some of the remaining topics
will be done in less depth.
In particular, there will be no material covered from chapter 5, and less
will be done with the Poisson/Geometric/Exponential distributions.
See Prof. Kuznetsov's page for more details about what is being covered
and what isn't.
- The midterm that was scheduled for Nov 10 is now rescheduled for Feb 13.
shifted to Nov 6 because of the Senate amnesty declared for students
participating in that day's YFS fee protest. Because of the strike, that due date was postponed further. Assignment 5 is now due Wednesday Feb 4.
- The course will be using on-line student evaluations. Originally the university was going to open the evaluation system on Nov 12, but that has also been postponed till after the strike.
- The 2nd midterm will cover the material we have done up to and including the class on November 1: transformations, the binomial and normal distributions, normal approximations, means, and variances. But nothing on independent random variables, or on the hypergeometric distribution.
- I'm not sure exactly how many assignments Prof. Kuznetsov will be able to assign. But in case you wish to work on problems on your own, I put a list of problems up during the strike, on the assignment page. Prof. Kuznetsov will probably choose some assignment problems from those questions, but in any case I will see that solutions are posted for all thoses problems.
As of November 5, the most recent topics studied were variances (sections 3.2 and parts of section 4.1) and the hypergeometric distribution (sections 2.5 and 3.6). We have defined independence for random variables, but have not yet used it in computations.
You should be reading ahead in the textbook, to be prepared to ask about
topics that are unclear, when they come up in class. Be aware that though
we will follow the text, we will not
necessarily cover all topics, nor will we necessarily cover the topics in
the order the textbook presents them.
With this in mind, here is
the basic list of topics we will cover, in the order we will treat them. Note that this list has been shortened due to the strike.
- The model for probabilities, random variables, and events
(Sections 1.1 - 1.3)
- Counting (appendix 1)
- Independence and Conditional Probability (Sections 1.4 and 1.6)
- Bayes rule (Section 1.5)
- Representing discrete and continuous distributions (parts of
Sections 3.1 and 4.1)
- Cumulative Distribution functions, their relation with densities
and discrete distributions (parts of Section 4.5)
- Using cdf's to compute distributions
of transformed random variables (parts of Section 4.5)
- Binomial and Normal distributions (Sections 2.1 and 2.2),
and normal approximations to the binomial distribution (Section 2.2)
- Expectations for discrete and continuous random variables (parts of
Sections 3.2 and 4.1), including the method of indicators.
- Variances (part of Section 3.3), along with calculation of means and
variances for distributions like the Binomial and Normal.
- The hypergeometric distribution (Sections 2.5 and 3.6)
- Independence of random variables (parts of Sections 3.1 and 4.1), and its consequences for expectations
- The law of large numbers, Chebyshev's inequality, and the Central Limit Theorem (Section 3.3)
- Normal approximations to more general
sums of independent random variables (Section 3.3).
- The poisson distribution and poisson approximation (Sections 2.4 and 3.5)
- The geometric (and negative binomial) distribution (Section 3.4)
- The exponential (and gamma) distribution (Section 4.2)
We will not cover Sections 2.3, 4.3, 4.4, or 4.6.