This chapter discusses the crucial role of sampling in quantitative research. Selecting an appropriate sample is essential, as it directly impacts the validity and reliability of the study’s findings. The chapter explores various sampling procedures and the key factors that must be considered when determining both the sampling method and the appropriate sample size. It begins by clarifying the concepts of sampling frames and populations, discussing their significance in selecting a representative sample from a larger group. The chapter then examines various sampling strategies, including probability and non-probability methods and discussing the advantages and disadvantages of each. Understanding these approaches will enable you to make informed decisions tailored to your specific research questions. Finally, the chapter guides you through calculating the required sample sizes for your studies and examining the factors that influence sample size determination. By the end of this chapter, you will not only see the importance of effective sampling but also have the knowledge to apply these concepts confidently in your own quantitative research studies.

We show that attending to domain considerations in corpus design involves three steps: (1) describing the domain as fully as possible; (2) operationalizing the domain; (3) sampling the texts. Describing the domain requires defining the boundaries of the domain: what texts belong within the domain and what do not? Describing the domain requires identifying important internal categories of texts that reflect qualitative variation within the domain. Domain description should be carried out systematically using a range of sources that can be evaluated for quality and triangulated. Operationalizing the domain refers to specifying the set of texts that are available for sampling; operational domains are always precisely bounded and specified. A sampling frame is an itemized list of all texts (from the operational domain) that are available for sampling. A sampling unit is the individual “object” (usually a text) that will be included in the corpus. Stratification is the process of collecting texts according to identified categories within the domain, and is usually desirable in corpus design. Proportionality refers to the relative sizes of strata within the sample. Strata can be proportional or equal-sized. Sampling methods can be broadly categorized as random and nonrandom.