Mode of Teaching:
Distance Education
This course will have some videos, all of which are asynchronous. There will be no live lectures.

Outline:

1. Introduction to graphical and numerical descriptive statistics including the histogram, boxplot, scatterplot, sample mean, sample median, sample standard deviation, sample coefficient of relative variation, and sample correlation coefficient.
2. Elementary probability rules, basic combinatorial formulae, conditional probability, Bayes' Theorem, and independence.
3. Introduction to discrete distributions including the probability mass functions, expectation, the binomial distribution, and the Poisson distribution.
4. Introduction to continuous distributions including the probability density function, expectation, variance, coefficient of variation, the cumulative distribution function, uniform distribution, gamma distribution, exponential distribution, normal distribution, normal approximation to the binomial distribution, jointly distributed random variables, statistics and their distributions, the Central Limit Theorem.
5. Single sample inference including estimation and testing of proportions and means.
6. Two sample inference including estimation and testing of differences in proportions and differences in means (paired and non-paired data).

This course is part of the University Accreditation Program and meets specific requirements set by the Canadian Institute of Actuaries (CIA). Please consult the CIA website for full details on CIA accreditation.