Overview Section
This lesson starts with the rationale for using unequal probability sampling in section 3.1. We then discuss in section 3.2 the Hansen-Hurwitz estimator which may be used when the sampling is with replacement. In section 3.3, we introduce the Horvitz-Thompson estimator which can be used when the sampling is with or without replacement. In section 4, a small population example is used to illustrate some properties of these two estimators. Through this example, one can see that both estimators are unbiased.
Lesson 3: Ch. 6.1, 6.2, 6.4 of Sampling by Steven Thompson, 3rd edition
Objectives
Upon completion of this lesson, you should be able to:
- Identify the situations that unequal probability sampling is beneficial and explain why,
- Explain and perform unequal probability sampling,
- Compute the Hansen-Hurwitz estimator and its estimated variance,
- Compute the Horvitz-Thompson estimator and its estimated variance, and
- Demonstrate that Hansen-Hurwitz and Horvitz-Thompson these two estimators are unbiased through an artificial small population example.