Book cover for Sample Size Without the Guesswork: How to Choose, Calculate and Justify Sample Size for Research by James Harris

Sample Size Without the Guesswork

How to Choose, Calculate and Justify Sample Size for Research

2026 Released
308 Pages
5-7 Hours
Ebook Unavailable
Audiobook Unavailable
Hardback Unavailable
Independently PublishedISBN 9798177810911
How many samples do you actually need?

Choosing the right sample size is one of the most important, and often most confusing, parts of planning research.
Choose too few, and your study may lack the statistical power or precision needed to answer the research question reliably. Choose too many, and you may waste time, money, samples and other valuable resources.

Sample Size Without the Guesswork provides a clear, practical way through the decision.
Rather than treating sample size as simply a number to plug into a formula, this book explains the reasoning behind the calculation. It helps you identify the appropriate approach for your research question and study design, understand the assumptions involved, perform the calculation, and clearly justify the sample size you choose.
With straightforward explanations and step-by-step worked examples, you will learn how to:
- choose an appropriate sample-size method for different research designs
- understand the roles of statistical power, precision, effect size and variability
- work through sample-size calculations step by step
- account for practical considerations such as attrition, clustering and finite populations
- recognise when different study designs require different approaches
- document and justify your sample-size decisions clearly

Designed for researchers, students and professionals who need practical answers rather than unnecessary mathematical complexity, this book provides a structured framework you can return to whenever you need to plan a study.

Whether you are designing a thesis, experiment, survey, clinical study, field investigation or monitoring program, Sample Size Without the Guesswork will help you answer one of the most important questions in research: How much data is enough?

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