Instructor: Dr. Mai Zhou Office: P. O. T. 849, Mailbox: P. O. T. 843, Phone: 257-6912, E-mail: mai@ms.uky.edu,  Office hour:  Tuesdays  3 - 4 pm  Fridays  3 - 4pm

Textbook: First 5 chapters of (Casella and Berger: Statistical Inference, 2nd Ed). and we have 7 weeks of class time. We need to hit the ground running...literally.
Tough on people that have to be absent for some classes. It is hard to catch up. (it goes so fast .... there is very little time for things to sink in)
Evaluations: Homeworks 35%
midterm 25% (Sept. 19 or 22 or 23?)
final 35% (Oct. 15 or 16  ? I prefer 75 min)
In class asking and answering questions 5%

Try to maximize the benefit of in-class time... read book before the class and try to resolve remaining questions as much as you can in-class. If you do not understand the materials after two classes, let me know, do not wait for
a week and then too late.

I assume you have had some probability before, like Elementary Probability, or within a Discrete Mathematics course, perhaps. For example I will spent very little time on "counting method". Also, you should have some calculus and a little matrix algebra background. On the other hand, this is not a measure theoretic probability. So we shall not proof some of the subtle measure theoretic results, but just state the results and comment on the need of such result, and how one can expect such results and why it is reasonable. I am a statistician, and will teach this course from a statistics point of view (so is the book), i.e. how probability can be useful in statistics.

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Have you heard of/how well do you know/ what in the following list are new to you?
Probability P(  )
random variables X
distribution functions , density function
Mean, Variance, Expectation
Law of large numbers
Central limit theorem 

Jacobian Matrix, double integrals

If you took a probability course, what book you used?