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Understanding Sampling Techniques in Research

Learn about population, sample, types of sampling, probability and non-probability techniques, and reasons for sampling. Understand attributes of good sampling and how to select a representative sample.

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Understanding Sampling Techniques in Research

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  1. SAMPLING AND SAMPLING TECHNIQUESBYABU MICHAEL SUNDAY P13SCBC8010DUNE PIUS DANIEL P13SCBC8035ALBERT DAYO P13SCBC8008ESSIEN EDETH BASSEY P13SCBC8019

  2. BASIC TERMINOLOGIES • Population may be defined as a collection or set of individuals, objects or measurements whose characteristics are to be analysed. • Sample is the portion or parts of the population of interest to be studied. • Sampling is the process of selecting the desired sample from the population. • Sampling frame or sample frame is the actual list of all elements or units in the population. It is the population from which a suitable sample is drawn. • Sampling error = Ẍ population - Ẍ sample

  3. REASONS FOR SAMPLING The main reasons why statisticians use samples are: • Time constraints • Limited resources

  4. ATTRIBUTES OF GOOD SAMPLING • A good sampling must be able to identify a representative sample whose characteristics cut across the population in which it is been drawn. • Generally, the larger the sample, the more representative it is of the population and the better the results extrapolation from sample to population.

  5. SAMPLING TECHNIQUES Two main types: • Probability sampling • Non-probability sampling

  6. PROBABILITY SAMPLING Divided into: • Simple random sampling • Stratified sampling • Systematic sampling • Cluster sampling

  7. PROBABILITY SAMPLING CONt’D • Simple random sampling- elements are randomly selected. This technique is suitable for a homogenous population. • Stratified sampling- population is divide into strata. Suitable for heterogeneous population. • Systematic sampling-the first item is randomly selected after which every other item is selected in a systematic manner. • Cluster sampling- elements are groups or clusters rather than individual units.

  8. NON-PROBABILITY SAMPLING Divide into: • Convenience sampling • Judgement sampling • Quota sampling

  9. NON-PROBABILITY SAMPLING CON’D • Convenience sampling- in this sampling method the key word is convenience. useful in pilot study. • Judgement sampling-expert individual or team use their judgement to select what in their opinion, is a true representative sample from a population. • Quota sampling-Usually, the sample frame is stratified e.g according to age or sex.

  10. CONCLUSION • The importance of sampling and sampling techniques in research of any sort can not be over emphasised.

  11. THANK YOU FOR LISTENING

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