Sample Size and Sample Selection Bias

This chapter explores the fundamental concepts of sample size, population and sampling techniques, which are important for conducting robust statistical analysis and ensuring the generalisability of research findings. The chapter begins by explaining the reasons why sampling is undertaken, and the concepts of population, sampling size and the sample. The chapter discusses in detail both the probability-based and non-probability-based sampling techniques, such as simple random, stratified and convenience sampling, explaining their appropriateness for different research objectives. Practical guidance on how to determine an adequate sample size by considering key parameters like statistical power, confidence level and effect size is also discussed in the chapter. Finally, various forms of sampling bias, including ascertainment, survivorship and non-response bias, help researchers identify and, if possible, address these biases to ensure the validity of their findings. By understanding these concepts, researchers can better interpret the limitations of their data and make more accurate claims about the larger population.