CDE4121 Lecture Notes - Lecture 3: Stratified Sampling, Convenience Sampling, Cluster Sampling
MODULE 3: PLANNING A RESEARCH DESIGN & SAMPLING METHODS
Factors defining Research Design:
• What is the study about?
• Why is the study being made?
• Where will the study be carried out?
• What type of data is to be collected?
• Where can the required data be found?
• What period of time will be needed for the study?
• Which technique of data collection will be used?
• How will be the data be analysed?
Scientific Reasoning:
Sampling Methods:
1. Population - aggregate of all elements, sharing some common set of characteristics, which comprises the
universe for the purpose of research
2. Census - complete enumeration of the elements of a population or study objects. When you talk to everyone
in the population
3. Sample - subgroup of the elements of the population selected for participation in the study
Probability Sampling:
• Every member of the population has a known chance of being selected as part of a sample
• Results are considered adequate in representing the entire population
Non-Probability Sampling:
• No way of knowing the chance of a member in the population being chosen as part of a sample
• Selection of sampling units is left primarily to the researcher
Simple Random Sampling (probability):
• Each member of a population has an equal opportunity of being selected for the sample
• e.g. Myer Card Holders (select members from a hat; use randomising software to select members)
Systematic Sampling (probability):
• Sampling every n th member of the population
• 1 st sample chosen randomly
• Additional members chosen by selecting the n th subject
• e.g. Myer Card Holders (28th member and then every 10th member selected)
Stratified sampling (probability):
• Population is partitioned into sub-groups (strata)
• Groups based on some characteristic (e.g. age, gender, location)
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