Sampling Errors, Bias, and Objectivity

  • David M. FlintonEmail author


The basis of any good piece of research is making sure you have sampled correctly and avoided bias. In this chapter the need for sampling is considered. The more commonly used methods of obtaining a sample in quantitative research are reviewed. The importance of a sample reflecting the population, and the various forms of bias that might arise because of study design with particular reference to health research, are discussed. Random and systematic errors and how they affect the data being collected are discussed. An overview of considerations are taken into account when looking at sample size and power is included. The concepts of reliability and validity are discussed along with common methods of establishing reliability and validity of measurement.


Sample size Reliability Validity Systematic error Random error Power 


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Further Readings

  1. Altman DG. Practical statistics for medical research. London: Chapman and Hall; 1991.Google Scholar
  2. Bland M. An introduction to medical statistics. 4th ed. Oxford: Oxford University Press; 2015.Google Scholar
  3. Petrie A, Sabin S. Medical statistics at a glance. 3rd ed. Oxford: Wiley Blackwell; 2009.Google Scholar
  4. Web Resources

    1. There are a number of web pages that deal with sampling and probability, including some with Java applications. Other useful resource on the web are random number generators.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Health SciencesCity, University of LondonLondonUK

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