sampleone - Survey Sampling Methods for Teaching and Practice

Planning, selection, and estimation for surveys under the main probability sampling designs taught in introductory sampling courses: simple random sampling with and without replacement, stratified sampling (proportional, Neyman, and cost-based allocation), systematic sampling, one- and two-stage cluster sampling, and ratio and regression estimators. Functions accept a superset of the inputs a given formula requires and silently ignore arguments that are not needed for the selected computation. Each function returns a structured object with the point estimate, the associated variance and confidence interval, a step-by-step breakdown of the calculation, and a short pedagogical note suggesting related methods to explore, making the package suitable both for applied survey work and for classroom use. Methods follow Cochran (1977, ISBN:0-471-16240-X) and Bolfarine & Bussab (2005, ISBN:8521203675), among others referenced in each function's documentation.