Question 1

A census samples all the elements in a population.

Accepted Answer

A census involves collecting data from every member of the population, as opposed to a sample survey which collects data from a subset of the population.

Question 2

Which of the following is NOT part of the sampling design process?

Accepted Answer

Refining the research question is part of the research design process, not the sampling design process.

Question 3

It is often impractical to undertake a census in business and management research due to ________.

Accepted Answer

Conducting a census is time-consuming and often impractical due to the extensive time required to collect data from every member of a population.

Question 4

You only need to consider your sampling strategy if you plan to undertake questionnaire research.

Accepted Answer

Sampling strategy is important in any research involving data collection from a subset of a population, not just questionnaire research, to ensure the sample is representative and the findings are valid.

Question 5

Administering a structured interview to passers-by at a theme park is an example of ________.

Accepted Answer

Convenience sampling involves selecting a sample based on ease of access and proximity, such as interviewing passers-by at a theme park.

Question 6

Another word for "non-probability" sampling is "representative" sampling.

Accepted Answer

Non-probability sampling does not aim to create a representative sample of the population, as it does not use random selection methods.

Question 7

Which of the following is NOT a benefit from sampling?

Accepted Answer

The answer of Which of the following is NOT a...

Question 8

Which of these is the correct definition of probability sampling?

Accepted Answer

Probability sampling is a sampling technique where every case in the population has a known and equal chance of being selected, ensuring that the sample is representative of the population.

Question 9

You can still generalise findings generated by non-probability samples, but not on statistical grounds.

Accepted Answer

Non-probability samples do not allow for statistical generalization because they do not provide every individual in the population an equal chance of being selected, but findings can still be generalized based on theoretical or logical reasoning.

Question 10

"Mansur's research objective is to find out whether a new maintenance procedure helps ensure quality of manufacturing output." Which sampling strategy could he use?

Accepted Answer

Mansur could use any of the sampling strategies to find out whether a new maintenance procedure helps ensure quality of manufacturing output.

Question 11

Which of these is a probability sampling technique?

Accepted Answer

Systematic sampling is a probability sampling technique where every nth element in a list is selected, ensuring each member of the population has a known and equal chance of being chosen.

Question 12

Which of these is a non-probability sampling technique?

Accepted Answer

Purposive sampling is a non-probability sampling technique where the researcher selects participants based on specific characteristics or qualities, rather than random selection.

Question 13

Populations containing less than 50 elements are unlikely to be suitable for probability sampling.

Accepted Answer

Probability sampling is more effective with larger populations, as it ensures a more representative sample and reduces sampling error. With very small populations, it may not be feasible to achieve randomness and representativeness.

Question 14

What is a sampling frame?

Accepted Answer

A sampling frame is a complete list of all elements in the population from which a sample is drawn.

Question 15

Why is the UK telephone directory a poor sampling frame for typical UK householders?

Accepted Answer

The UK telephone directory is often out of date, incomplete due to unlisted numbers, and biased as it may not represent all demographics equally.

Question 16

Not making inferences beyond your sampling frame is placing clear limits on ________.

Accepted Answer

Not making inferences beyond your sampling frame limits the generalisability of your findings because it restricts the applicability of your results to only the population from which the sample was drawn.

Question 17

Which of these is NOT a concern in deciding on a representative sample size?

Accepted Answer

Willingness to take part is not a concern in deciding the sample size; it is more related to response rate and participation, not the statistical determination of sample size.

Question 18

A sample size of 30 is a good rule of thumb for enabling statistical analysis to be undertaken.

Accepted Answer

A sample size of 30 is often considered sufficient for the Central Limit Theorem to apply, allowing for normal distribution approximation and reliable statistical analysis.

Question 19

What is the "central limit theorem"?

Accepted Answer

The central limit theorem states that the distribution of the sample mean will approach a normal distribution as the sample size becomes larger, regardless of the population's distribution.

Question 20

"A process of deriving conclusions about a population on the basis of data describing a probability sample". What is bring described here?

Accepted Answer

Statistical inference is the process of using data from a sample to make conclusions about a larger population.

Quiz 7: Selecting Samples