Systematic sampling, also called nth name selection technique, is often used instead of random sampling due to its simpler process. After the sample is collected, every nth member within the population is recorded within the sample.

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As discussed earlier, probability sampling techniques cannot be used for qualitative research by definition, because the members of the universe to be sampled are not known a priori, so it is not possible to draw elements for study in proportion to an as yet unknown distribution in the universe sampled.

Maximum variation sampling (sometimes referred to as maximum diversity sampling or maximum heterogeneity sampling) is a sampling method in which researchers attempt to collect data from the widest range of perspectives possible about a certain topic.

Some researchers believes it is desirable to have at least 10 respondents for each item being tested in a factor analysis, Further, up to 300 responses is not unusual for Likert scale development according to other researchers.

n = N*X / (X + N – 1), where, X = Zα/22 *p*(1-p) / MOE2, and Zα/2 is the critical value of the Normal distribution at α/2 (e.g. for a confidence level of 95%, α is 0.05 and the critical value is 1.96), MOE is the margin of error, p is the sample proportion, and N is the population size.

Sample size refers to the number of participants or observations included in a study. This number is usually represented by n. The size of a sample influences two statistical properties: 1) the precision of our estimates and 2) the power of the study to draw conclusions.

Hence, there is no such thing as a magic number when it comes to sample size calculations and arbitrary numbers such as 30 must not be considered as adequate.