Introduction
What this guide covers
An exhaustive and formally rigorous exposition of the most basic design of probabilistic sampling: combinatorial foundations, unbiased estimators, theoretical variances, determination of sample size and exercises solved with complete development.
Overview
Topics covered
- Introduction
- Sampling Theory: Simple Random Sampling
- 01 Basic Concepts and General Theoretical Framework
- 1.1 Population and Sampling Frame
- 1.2 Population Parameters
- 1.3 Sample Design and Inclusion Probabilities
Related concepts
Main connections
Compatible notation
Mathematical sample in LaTeX
The expression is rendered accessibly, with its LaTeX source preserved below.
View LaTeX source
\text{Population total:} \quad Y = \sum_{i=1}^{N} y_i