I am sorry the time and place of this course has been moved around. 
The reason is try to accommodate as much students as possible.
I was told the time that suit most students that want to take this course
is MWF at 12 noon

The location is now in OHR 226 the civil engineering building.

The web page that will have all the links to homework etc. is
http://www.ms.uky.edu/~mai/courses.html

Office Hour: M 3:30-4:30PM ;  F 11:00-11:50 AM
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Probability can be taught in several difference ways:

1. Measure theoretic probability. Stress on the rigorous foundation.
   Mostly for preparation to
   do research in probability. Probability from the math point of view.
   required for Ph.D. Students in prob/stat.

2  Non-measure theoretic probability. Use calculus instead. Standard.

2.5  Similar to 2 but more towards the preparation for a subsequal Stat
    course like Sta/OR 525

3. Probability from the modeling point of view.  applied. 
   Mainly use probability distributions to model
   real world phenomena. Familiar with distributions and their properties.
   Many example of modeling. Basic concepts still needed.
   (Textbook: Sheldon Ross: Probability Models)

4. Computer simulation point of view. More people in computer science,
   physics, business, etc like it. As computers getting faster, 
   this is appealing. But you need to be good at programming.
   All we need to know is how to generate random variable. 
   You get good feelings but not too much calculations.
   Some time this is the only viable way for complicated problems.
   (Ruin probability, probability of lost money for insurance company etc.)
   New



Q1 What is your background in Math? in computer programming?

Q2 Any previous Prob/Stat course? if yes, the details.

Q3 Which approach to prob do you like best? 

Q4 Give one or two "most-want-to-learn" topic/case you wish to
   get out of this course.



Textbook: We shall use a free book: Introduction to Probability
(this book is using approach 2 above) 

Depending which approach we decide to use, I will prepare additional
notes later (for example the computer program tutorials etc.)
plus notes that I will give you later.

Links:

http://www.math.dartmouth.edu/~prob/prob/prob.pdf

http://www.stat.umn.edu/geyer/old/5102/n.pdf 
(this is an extensive notes, 200+ pages, mainly prepares you
for a subsequent statistics course, like Sta/OR 525) 
I like the style of his writing.


Grading:

Homework   40%
Midterm(s) 35%   
Final      25%

First Midterm: Oct. 5. 
Second Midterm: Nov. ?

My office: POT 849   257-6912
Office Hour: M 3:30-4:30PM ;  F 11:00-11:50 AM
My email address is   mai@ms.uky.edu
send me an email and I will reply with the pdf file of the book
(about 500 pages).



Formal description of the course content:

1. Basic probability: definition and calculation

2. Conditional probaility.

3. Random variables: some name brand r.v. and their distributions

4. Expectation of random variables. mean and variance

5. Limit theorems (law of large numbers, central limit theorems)

6. Stochastic process (? when time permits)