University Mathematics
Probability & Statistics
A calculus-based first course in probability and statistics for engineering, science and mathematics students: from random variables and distributions to estimation and hypothesis testing.
Curriculum / Syllabus
- Sample Spaces, Counting and the Axioms of Probability
- Conditional Probability, Independence and Bayes' Theorem
- Discrete and Continuous Random Variables
- Expectation, Variance and Moment Generating Functions
- Common Distributions (Binomial, Poisson, Normal, Exponential)
- Joint Distributions and the Central Limit Theorem
- Point Estimation, Confidence Intervals and Hypothesis Tests
Exam & Course Strategy
Exams combine computation (setting up the right distribution and summing or integrating correctly) with interpretation. Most points are lost when modelling the problem, so we practise turning word problems into random variables.