SAMPLE SIZE

How big should my sample be?   It all depends on what you want to do with your findings and the type of relationship you want to establish in your study.   The sample size is crucially important in a correlational research design, i.e. tests of hypotheses and significance, or establishing an association or relationship between two of more variables.   However, there is no relationship between the sample size and the size of the study population, sample size is determined by the variability of the factor, element or characteristic prevalent in the study population.   Other things being equal, precision increases steadily up to sample sizes of 50-200; after that, there is only a modest gain in precision to increasing sample size.   Whilst increasing sample size reduces errors attributable to sampling, managing large amounts of data may increase non-sampling errors (e.g. field-work problems, interviewer-induced bias, clerical errors in transcribing data, etc.).   In determining the size of a sample, consideration should be given to:

1. the degree of accuracy required in the estimation of the variables in the chosen study population
2. the level of confidence demanded from the sample to test the significance of the findings or hypotheses
3. the extent to which the variability of the factor in the chosen study population is known, or can be estimated

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