Final answer:
Non-random sampling techniques include convenience, judgmental, quota, and snowball sampling. In a supermarket usage questionnaire, a question asking the number of times a customer visits per month with quantifiable choices provides clear, actionable data. The examples given illustrate convenience, cluster, and systematic sampling methods.
Step-by-step explanation:
Non-Random Sampling Techniques
Non-random sampling techniques are methods of selecting samples from a population in a non-random manner. Some examples of non-random sampling techniques include:
- Convenience sampling: Selecting individuals who are easiest to reach or readily available.
- Judgmental or purposive sampling: Selecting individuals based on the judgment of the researcher, often because they are deemed representative of the population.
- Quota sampling: Dividing the population into groups and then non-randomly selecting individuals to meet pre-established quotas for each group.
- Snowball sampling: Asking initial subjects to identify other individuals who qualify for the study.
Question for Supermarket Usage Questionnaire
To effectively gather data concerning supermarket usage, the question should provide quantifiable and actionable results. Among the provided options:
"How many times in a typical month do you go to the supermarket?" with options a) 0 times b) 1-2 times c) 3-4 times d) More than 4 times would yield precise, quantitative data that is beneficial for analysis.
Sampling Methods Used in Examples
Based on the scenarios provided, the sampling methods used are:
- Non-random selection of travelers likely represents convenience sampling.
- Selection of students from specific rows for homework presentation could be a form of cluster sampling, assuming each row acts as a cluster.
- The method used to survey residents about park usage in San Antonio is systematic sampling, as every eighth house was selected.