STA 322 covers 20 topics. StudyPath paces them into daily study
sessions that finish before your exam date, with practice questions and worked
answers for each one.
Estimation of mean and variance in systematic sampling
Confidence intervals in systematic sampling
Relative precision in systematic sampling
Cluster sampling concepts
Single-stage cluster sampling
Equal and unequal size cluster sampling
Confidence intervals in cluster sampling
Ratio-to-size sampling
Probability proportional to size sampling
Relative precision, variance and cost functions
Stratified random sampling
Principles of stratification
Estimation under stratified sampling
Estimation in stratified sampling
Confidence intervals for population parameters
Relative precision in stratified sampling
Sample size determination in stratified sampling
Allocation methods in stratified sampling
A sample from this course
One topic, as StudyPath teaches it.
Systematic sampling
Systematic sampling is a probability technique where every kth element from a list is selected after a random start. It is essential for exams because it offers a simple, cost‑effective alternative to simple random sampling while still providing a representative sample if the list is not ordered in a way that biases the pattern.
What you get for STA 322
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.