Chapter 9 - Sampling

Question 1

Define Populations

Answer 1

A population refers to the larger group that the researcher aims to generalise their findings to

Question 2

Define Sampling Frames

Answer 2

The sampling frame is a detailed list of all participants or elements that could be sampled

Question 3

Define Sample

Answer 3

The sample is the group of participants selected from the population to be part of the study

Question 4

What is Probability Sampling what are the types of probability sampling techniques?​

Answer 4

Probability sampling techniques include:
- simple random sampling
- systematic random sampling
- stratified random sampling
- cluster sampling
- multistage sampling

Question 5

What is Non-Probability Sampling what are the types of non-probability sampling techniques?​

Answer 5

Non-probability sampling techniques include:
- convenience sampling
- snowball sampling
- purposive sampling
- quota sampling

Question 6

What does ‘sampling error’ mean?​

Answer 6

Sampling error occurs when the selected sample does not adequately represent the population. It can be classified into two types:
- random errors (which occur by chance)
- systematic errors (which arise from flaws in the sampling process)

Question 7

When is ‘sample size’ the right size?​

Answer 7

• The right sample size is one that is large enough to allow the sample mean to approximate the population mean, minimizing sampling error.
• It should be calculated during study planning, not retrospectively, and take into account factors like power analysis and potential attrition​