Sampling methods
Random sampling
Involves selection of participations from a population where each individual has equal likelihood of being chosen- Good for quantitative research
Advantages-
reduces bias- Selection is random
Highly representative- Results can be generalized to the population
Easy to implement- Selection process is straight forward
Disadvantages
Time consuming and expensive- Especially if looking at large populations
Difficult to access a full population list- A complete list of individuals is often needed, which can be hard to get
Risk of underrepresentation- Pure randomness can lead to uneven representation of certain groups
Systematic sampling
Involves every nth individual being selected from a list- structured method but is still random and unbiased
Advantages-
Simple and efficient- Researchers don’t have to select each individual randomly
Eliminates selection bias- Ensures an unbiased selection process
Ensures even distribution- Participants are spread out across the population
Less time consuming- Requires few resources
Disadvantages-
Hidden patterns may affect results- If population has a secret pattern it can affect results
Requires a complete list of population- Full population must be known beforehand
Not as random as simple random sampling- Selection method is structured, can introduce unintentional bias
Stratified sampling
Divides a population into subgroups based on characteristics (age, gender, income) then a random sample is taken from each subgroup/ ensures all groups are properly represented
Advantages-
More representative- Ensures all subgroups are properly included
Reduces sampling bias- Avoids overrepresentation or underrepresentation of certain groups
More accurate comparisons- Helps compare differences between groups
Ensures small groups are represented- Good for studying minority groups
Disadvantages-
Time-consuming- Requires identifying and categorizing the population into strata
Requires full population data- Must have prior knowledge of characteristics
Not useful if unclear- If people don’t clearly fit into groups, stratification becomes unclear
Quota sampling
Involves dividing population into groups based on specific characteristics and then selecting participants non randomly until each quota is filled
Advantages-
Quick and cost effective- Faster than probability sampling since it dosen’t require a full population list
Ensures representation- Guarantees that key sub groups are included
Useful when random sampling is not possible- works when researchers do not have access to a full list of the population
Disadvantages-
Not random- since selection is based on convenience, it may introduce bias
Lower generalizability- Results may not accurately reflect the broader population
Risk of researcher bias- Researcher may pick participants who fit their expectations
Snowballing sampling
The researcher contacts a small group of respondents who then refer others from their network to participate in the research
Advantages-
Useful for hard to reach groups- Helps study hidden populations
Cost and time efficient- Researcher don’t have to find all participants themselves
Builds trust- Comes from personal networks so participants may feel more comfortable sharing information
Disavantages-
Selection bias- Participants are not randomly selected which can lead to an overrepresentation of certain groups
Limited generalizability- Sample wont reflect the larger population
Ethical concerns- Participants may feel pressured to recruit others, raising privacy concerns
Sample size considerations
Size of the sample can have a significant impact on the reliability, generalisability and validity of research
Larger samples provide more reliable and general resul