See the syllabus
The material covered in this course is fundamental to all other statistics courses. So, it is
extremely important that you understand this material well; you can test yourself by doing the homework problems (see my note on home work assignments). Also, the material covered in this course is also the material that is covered in Exam P of SOA and CAS. By the end of the course, you should:
1）Understand
a）Characterizing measurements: Graphical, Numerical
b）How Inferences are made
c）Probability
d）Moments and Moment Generating Functions
e）Probability-Generating Functions
2）Understand, and Identify
a）Discrete Random Variables
b）Binomial Random Variable
c）Geometric Random Variable
d）Negative Binomial Random Variable
e）Hypergeometric Random Variable
f）Poisson Random Variable
3）Understand and Identify
a）Continuous Random Variables
b）Uniform Random Variable
c）Normal Random Variable
d）Gamma-Type Random Variable
e）Beta Random Variable
4）Understand
a）Multivariate Probability Distributions
b）Marginal and Conditional Probability Distributions
c）Independent Random Variables
d）Expected Value of a Function of Random Variables
e）Bivariate Normal Distribution
5）Compute
a）Probability Distribution of a Function of Random Variable using Method of
（i）Distribution Functions
（ii）Transformations and
（iii）Moment Generating Functions
b）Sampling Distributions
c）Normal Approximation to Binomial
