Question 1: Define 'random sampling' in your own words.

Answer: Random sampling is a method where every individual in the population has an equal chance of being selected, ensuring fairness and reducing bias.

Question 2: List two advantages of using random sampling in a psychological study.

Answer: 1. It minimizes selection bias, making the sample more representative of the population. 2. It increases the likelihood that the results can be generalized to the whole population.

Question 3: Describe a scenario where opportunity sampling might be used in a psychology experiment.

Answer: Opportunity sampling might be used when a researcher surveys students in their school corridor during break time because they are easily accessible.

Question 4: What is a potential problem with using convenience sampling?

Answer: Convenience sampling can lead to biased results because the sample may not represent the entire population well.

Question 5: Explain what stratified sampling involves, and give an example.

Answer: Stratified sampling involves dividing the population into subgroups (strata) based on specific characteristics, then randomly sampling from each group. For example, selecting students proportionally from different year groups.

Question 6: Imagine you are conducting a survey about students' sleep habits. Sketch a diagram showing how you would divide the population into groups for stratified sampling.

Answer: A correct sketch would show a large circle labeled 'Total Population', divided into smaller sections labeled by characteristics (e.g., Year 7, Year 8, Year 9). Each section should be proportionally sized according to the population's distribution.

Question 7: Identify which sampling method is most likely being used in this scenario: A teacher chooses the first 20 students who arrive in the morning to take part in a survey.

Answer: This is an example of opportunity sampling.

Question 8: In your own words, explain why random sampling is considered the most reliable method for selecting participants.

Answer: Because it gives all members of the population an equal chance of being chosen, reducing bias and making the sample more representative.

Question 9: Draw a simple diagram representing a cluster sampling process, where entire classes are selected instead of individual students.

Answer: A correct sketch would show a large box labeled 'School Population', divided into smaller boxes labeled 'Class 1', 'Class 2', etc. A few entire class boxes are shaded or marked to indicate selection.

Question 10: Why might a researcher choose to use quota sampling instead of random sampling?

Answer: Because quota sampling allows the researcher to ensure that specific subgroups are represented in the sample, especially when random sampling is difficult or time-consuming.