The images you uploaded contain questions related to classifying different types of sampling methods. Here's a breakdown:

(a) The question asks about a cluster sample for a conference survey.

• Cluster sampling involves dividing the population into groups (clusters) and then randomly selecting entire groups for the survey.
  • The correct answer is likely: "The organizers form groups of 8 attendees based on the day the attendees registered. Then, the organizers randomly choose 7 groups and select all of the attendees in these groups." This describes selecting entire clusters (groups).

(b) The question asks about a systematic sample of students.

• Systematic sampling involves selecting every nth individual from an ordered list.
  • The correct answer is: "The counselors take a list of the students and select every 5th student until 90 students are selected." This represents systematic sampling by selecting every 5th student.

(c) The question asks about a convenience sample of microscopes.

• Convenience sampling involves selecting individuals or items that are easiest to access.
  • The correct answer is: "The microscopes in the first shipment that were received are easily accessible. So, he selects all 80 of the microscopes in this shipment." This describes selecting items based on convenience.

Would you like further details or clarification on any of these sampling methods?

Here are some additional questions related to the content:

1. What are the differences between simple random sampling and cluster sampling?
2. How do stratified sampling and cluster sampling compare?
3. What are the advantages and disadvantages of using systematic sampling?
4. How does convenience sampling potentially introduce bias into results?
5. What types of sampling are most useful for large populations?

Tip: Always ensure that the sampling method chosen matches the research goals to reduce bias and improve the accuracy of results.