Question

An instructor teaches five different sections of Marketing Research in the same semester. He is interested in estimating the level of difficulty of his exams. Given limited resources, he decides to administer the survey on all students in two of the five sections (chosen randomly) and uses the results to generalize across all students. This is an example of cluster sampling simple random sampling convenience sampling stratified sampling

Answer 1

The type of sampling used in this scenario is cluster sampling, where the instructor randomly selects two sections of the course and includes all students in those sections in the sample.

Step-by-step explanation:

The type of sampling used in administering the survey to estimate the difficulty of exams in two randomly chosen sections of Marketing Research is cluster sampling.

Cluster sampling involves dividing the population into clusters, and then randomly selecting some of the clusters to be included in the sample. In this case, the instructor divided the sections of Marketing Research into clusters, which are the different sections of the course. Two of these sections were randomly chosen, and all the students in those sections were included in the sample.

This method is different from simple random sampling, where each individual in the population has an equal chance of being included in the sample. It is also different from stratified sampling, where the population is divided into subgroups and a proportional number of individuals are selected from each subgroup.