# Quiz

Test you understanding of key chapter concepts by working through this quiz. You can check your answer by clicking on the arrow to the right or on what you think the correct answer is.  The correct answer will then be revealed to you for that question.

1.  Sampling is necessary because:

1. All populations are extremely large.
2. Populations tend to be homogenous.
3. Populations tend to be heterogeneous.
4. All of the above are true.

C. Populations tend to be heterogeneous.

2.  A sample will be more representative of the population it is drawn from if:

1. It contains equal proportions of the different elements in the population.
2. It is larger.
3. It mirrors the extent and proportions of the variability found in the population.
4. It is selected on a random basis.

C. It mirrors the extent and proportions of the variability found in the population.

3.  The ‘sample frame’ is comprised of all the subjects chosen from the population to constitute the sample.

1. True.
2. False.

B. False.

4.  Any difference between the planned, or target sample and the realised, or actual sample will be primarily due to:

1. The actual response rate.
2. Non-random responses.
3. Random responses.
4. The confidence interval.

A. The actual response rate.

5.  The establishment and use of a ‘sampling interval’ to select the desired sample is most commonly used in:

1. Cluster sampling.
2. Stratified random sampling.
3. Convenience sampling.
4. Systematic random sampling.

D. Systematic random sampling.

6.  If you stand in the street, or in a shopping mall, and stop people as they pass by to ask them if they would be prepared to complete a questionnaire you would be using a:

1. Random sampling strategy.
2. Convenience sampling strategy.
3. Cluster sampling strategy.
4. Key informants sampling strategy.

B. Convenience sampling strategy.

7.  Quota sampling is a probability-based type of sampling.

1. True.
2. False.

B. False.

8.  The random selection of subjects to be included in a sample primarily helps to minimise:

1. Sampling error.
2. Poor response rates.
3. Disproportionate representation.
4. Sample bias.

D. Sample bias.

9.  If a sample delivers valid data then this automatically makes it suitable for generalising these results back to the wider population.

1. True.
2. False.

B. False.

10. If you want to ensure your sample is representative of a population that has unequal proportions of men and women and you want to generalise your sample results back to this population the most appropriate sampling strategy to use would be:

1. Stratified random.
2. Simple random.
3. Systematic random.
4. None of the above.