STA 321 covers 21 topics. StudyPath paces them into daily study
sessions that finish before your exam date, with practice questions and worked
answers for each one.
Characteristic function of sums of independent variables
Distribution of the sum of two independent random variables
Gamma function
Chi-square distribution
Characteristic function of the chi-square distribution
Degrees of freedom
Moments of the chi-square distribution
Student's t distribution
Fisher's F distribution
Cochran's theorem
Hypothesis testing concepts
Randomized and non-randomized tests
Power, UMP tests and OC curves
Neyman-Pearson lemma
Likelihood function
Maximum likelihood estimation
Cramér-Rao and Bhattacharyya bounds
Unbiased estimation and MVUE
Sufficient and complete statistics
Rao-Blackwell theorem
A sample from this course
One topic, as StudyPath teaches it.
Independence of discrete random variables
Independence of discrete random variables is a foundational concept that determines whether the joint probability distribution can be expressed as the product of individual marginal distributions. Mastering this idea is crucial for the Nigerian tertiary exams because many probability problems hinge on recognising or proving independence to simplify calculations.
What you get for STA 321
Every topic above, split into sessions and dated against your exam.
Practice questions per session, with answers that explain themselves.
Offline reading — the whole course is a few hundred KB on your phone.
An AI tutor that answers questions using this course's own material.