A cluster sample is a sampling technique used in statistics where the population is divided into groups, or clusters, and a random selection of these clusters is made. Instead of sampling individuals from the entire population, researchers focus on entire clusters, which can simplify data collection and reduce costs. Each cluster should ideally represent the population as a whole. For example, if a researcher wants to study the eating habits of students in a city, they might divide the city into different neighborhoods as clusters. They would then randomly select a few neighborhoods and survey all the students within those selected neighborhoods, ensuring a diverse representation of the entire student population.