Let's identify the sampling techniques used in each scenario:

1. A researcher investigates the average salary of people by surveying all workers at 20 randomly selected supermarkets in Texas.

   • Sampling Technique: Cluster Sample
     • In this scenario, the researcher has divided the population into clusters (supermarkets) and then randomly selected a few clusters (20 supermarkets) to survey every worker within those clusters. This method is known as cluster sampling.

2. You put 100 names in a hat and pick 5 out.

   • Sampling Technique: Simple Random Sample
     • This is an example of simple random sampling, where each individual in the population (the 100 names) has an equal chance of being selected, and the selection is entirely random.

3. Every 30th printer is tested for readability.

   • Sampling Technique: Systematic Sample
     • This scenario describes systematic sampling, where a regular interval (every 30th printer) is used to select samples from the population.

4. A teacher surveys 20 students in his class.

   • Sampling Technique: Convenience Sample
     • This is an example of convenience sampling because the teacher is surveying students who are readily available (his own class), rather than randomly selecting students from the entire school or district.

5. A marketing expert is planning a survey in which 100 people will be randomly selected from each age group: 20–29, 30–39, and 40–49.

   • Sampling Technique: Stratified Sample
     • This scenario describes stratified sampling, where the population is divided into distinct subgroups (age groups) and a random sample is taken from each subgroup to ensure representation from each group.

Would you like further details or have any questions about these sampling techniques? Here are some related questions you might be interested in:

1. What are the advantages and disadvantages of each sampling technique?
2. How do you determine which sampling technique is most appropriate for a study?
3. Can a study use more than one sampling technique?
4. How does sample size affect the reliability of the results?
5. What are some common pitfalls to avoid when selecting a sampling method?

Tip: When selecting a sampling technique, consider the study's objectives, the population's characteristics, and practical constraints such as time and resources.