UNIVERSITY OF ILLINOIS AT URBANACHAMPAIGN
Actuarial Science Program
DEPARTMENT OF MATHEMATICS
Math 370 X
Actuarial Problem Solving
Fall, 2011 245 Altgeld Hall 7:008:30 pm Monday Starting Sep. 12 12 Lectures in Total 

Office Hours: By appointment Email: actuarialillinois@gmail.com 
Course web page: https://math.uiuc.edu/~fengzhu2/Math370X.htm
Course Overview
This course serves as a
preparation/review for the actuarial exam P/1. You can take it for credit (one
hour), or just sit in without registering (no prior approval needed). With or
without registration, you can get (if you want) your quizzes scored.
Exam P materials would be covered in
the following order:
These topics correspond to the exam P/1
syllabus and to the first five chapters in the MATH 408 text (Hogg/Tanis,
Probability and Statistical Inference). I will briefly review the relevant
concepts and formulas, but the majority of the time will be devoted to working
actuarial exam problems.
Required Text
There is no required text, though you
should have a basic probability text available for reference; commercial test
preparation manuals are advised, but not necessary for this class. Handouts,
notes, quizzes and solutions will be posted on course web page.
Grading
Grading for this course is on an S/U
(Satisfactory/Unsatisfactory) basis.
There will be no homework or final
exam for this class, but we would have a quiz at the end of each lecture. These
quizzes will be similar in format and difficulty to the actuarial exams.
To get "S" credit, you need
to
a) Attend at
least 9 of the 12 lectures, OR
b) Score 75% or above on
at least 6 of the 12 inclass quizzes.
There will be no makeup quiz.
Resources
Lecture
1 Sep.12 
General Probabilities 

Lecture
2 Sep.19 
Conditional Probabilities and Independent 

Lecture
3 Sep.26 
Random Variables and Probability Distributions 

Lecture
4 Oct. 3 
Expectations, Variance and Moment Generating
Function (Discrete R.V.s) 

Lecture
5 Oct. 17 
Expectations, Variance and Moment Generating
Function (Continuous R.V.s) 

Lecture
6 Oct. 24 
Discrete Distributions (Part I) 

Lecture
7 Oct. 31 
Discrete Distributions (Part II) 

Lecture
8 Nov. 7 
Continuous Distributions (Part I) 

Lecture
9 Nov. 15 
Continuous Distributions (Part II) 

Lecture
10 Nov. 28 
Joint & Marginal Distributions (Part I) 

Lecture
11 
Joint & Marginal Distributions (Part II) 








