There are numerous types of probability sampling methods, each with its approach to ensuring that each element in the population has a known and nonzero chance of being selected to be in the sample.
Some common types of probability sampling are:
- Simple random sampling:
- In simple random sampling, every individual in the population has an equal chance of getting selected.
- It ensures that the sample is representative and unbiased and each member has an equal opportunity to be included.
- Stratified random sampling:
- In this sampling method, the population is divided into subgroups or strata based on specific characteristics (e.g., age, gender, socioeconomic status), and then random samples are selected from each stratum.
- It ensures representation from different population segments, allowing for more accurate subgroup analysis.
- Systematic sampling:
- Systematic sampling involves selecting every nth individual from a list after a random start.
- It is a systematic and straightforward method, providing a random and evenly distributed sample.
- Cluster sampling:**
- The population is divided into clusters, and entire clusters are randomly selected. Then, all individuals within the chosen clusters are included in the sample.
- It is beneficial when it is logistically challenging or expensive to obtain a complete list of the population.
- Multistage sampling:
- Multistage sampling is a combination of different sampling methods.
- It balances the advantages of different sampling methods, allowing for greater flexibility in complex sampling scenarios.
List of recommended resources #
For a broad overview #
2.4 – Simple Random Sampling and Other Sampling Methods
This guide by PennState Eberly College of Science gives an overview of the 5 main types of probability sampling, namely simple random sampling, stratified sampling, systematic sampling, cluster sampling and multistage sampling, along with examples.
What Is Probability Sampling? | Types & Examples
This blog on Scribbr by Kassiani Nikolopoulou gives an overview of probability sampling, its various types and examples. It also details the advantages and disadvantages of probability sampling, along with the basic difference between probability and non-probability sampling.
For in depth understanding #
Choosing the type of probability sampling
This chapter from the book Sampling Essentials by Sage Publications gives an in-depth understanding of the different types of probability sampling as well as the differences between them. It also details the strengths and weaknesses of each probability sampling method.
This book by Steven K. Thompson as part of Wiley Series in Probability and Statistics gives an up-to-date and in-depth understanding of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations.
Case study #
This paper by Ramiro Flores Cruz studies the COVID-19 high-frequency phone survey (HFPS) 2020 conducted in 13 Latin American countries: Argentina, Bolivia, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Paraguay, and Peru. All national samples were based on a dual frame of cell and landline phones, and selected as a one-stage probability sample, with geographic stratification of landline numbers.
This report published by the World Bank describes the results of a phone survey completed in August and September of 2022, showing the precarity of living conditions and livelihood options across Yemen, but highlighting worse conditions amongst parts of the population. The survey draws on a probability sample of 1,297 respondents, 623 of whom are based in rural areas, while 480 and 193 are living in urban and semi-urban areas respectively.
References #
Probability Sampling: Definition,Types, Advantages and Disadvantages
Sampling Methods | Types, Techniques & Examples
