Survey Design: Definition of Populations and Sampling Frames · Introduction

Introduction

What this guide covers

The logical infrastructure of representative inference: formalization of population boundaries, mathematical characterization of biases due to lack of coverage and optimization of selection frameworks.

Overview

Topics covered

Introduction
Statistical and Design Fundamentals
Theoretical Paradigms: Design vs. Models
The Total Survey Error Framework
Definition of Populations
The Target Population

Related concepts

Main connections

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

\bar{Y} = \frac{1}{N} \sum_{i \in U} Y_i = \frac{1}{N} \left[ \sum_{i \in U_C} Y_i + \sum_{i \in U_I} Y_i \right]

View LaTeX source

\bar{Y} = \frac{1}{N} \sum_{i \in U} Y_i = \frac{1}{N} \left[ \sum_{i \in U_C} Y_i + \sum_{i \in U_I} Y_i \right]