Statistical sampling Flashcards
What is random (simple) sampling
A sample where each individual has a equal chance of being chosen
How would you form a random sample from a population of n individuals
- Give all individuals a unique integer from 1 to n
- Generate a random number (with a calculator)
- Continue until the sample size is reached (discard duplicates)
- Chose the people assigned the generated numbers
What are the benefits of random sampling
- Equal chance of selection, so reduces bias
- Requires less population knowledge to be completed
- Simplest form of sampling
What are the potential problems with random sampling
- Data is not necessarily representative of the population
- Time consuming to allocated numbers and then choose
- Ineffective with smaller populations
What is systematic sampling
A sample that selects individuals at fixed periodic intervals
How would you form a systematic sample from a population
Choose every nth individual, depending on the size of the population and of the desired sample size.
What are the benefits of systematic sampling
- Simple and convenient to use
- Creates a sample of members evenly distributed in the sample, so reduces bias
- Works effectively for large populations
What are the potential problems with systematic sampling
- Requires the knowledge of an approximate population total
- Interacts with periodic traits (ie. systematic errors are either ignored or exaggerated)
- It creates a fractional chance of selection, which means that most individuals are systematically missed, with no chance of selection
What is stratified sampling
A sample with subgroups (strata) in the same proportion as the whole population
How would you form a stratified sample from a population
- Calculate the proportion of the population made up by the subgroups (number in subgroup / total population)
- Multiply this proportion by the desired sample size
- Use random sampling to select this number of individuals from each group.
What are the benefits of stratified sampling
- Representative of the whole population
- Reduces bias
- Using random sampling to fill each category if simple to do
What are the potential problems with stratified sampling
- Requires detailed knowledge about individuals in the population to calculate the proportions
- The random sampling evolved is time consuming
- Individuals overlapping categories may cause issues
What is cluster sampling
A sample made up of a pre-existing sub group (cluster) that is representative of the whole population.
How would you form a cluster sample
Choose a cluster of individuals that are representative of the whole population to use as a sample.
(eg. people on the same flight at an airport - as long as the sample doesn’t need to be representative of destinations)
What are the benefits of cluster sampling
- Requires minimal knowledge about the total population size
- Requires minimal effort to construct a sample
- Can be used on very large populations to save time
What are the potential problems with cluster sampling
- Can result in unconscious bias if the cluster isn’t representative of the population
- Results can only apply to the specific demographic of the cluster
- Only available in populations with unbiased clusters dependent on the reason for the sample (eg. if location specific, can’t use postcode clusters)
What is opportunity sampling
A sample made up of individuals chosen as the opportunity arises
How would you form a sample with opportunity sampling
Select individuals that are available and willing to take part, not considering if the sample is exactly representative of the population.
What are the benefits of opportunity sampling
- Convenient and easy to carry out
- Data is immediately available
- Can be used for very large populations
What are the potential problems with opportunity sampling
- Sample is not representative of the whole population
- Prone to unconscious bias
- Researcher bias can occur, where only certain people are targeted
What is quota sampling
A sample made up of individuals that fit into predetermined sub groups (strata), selected until the groups are filled.
How would you form a sample with quota sampling
- Calculate the number of individuals required from each group to be part of the sample (ie. by calculating the proportion if the total population is known)
- Use another sampling method (eg. opportunity, random) until each quota is filled, then ignore individuals in the filled groups
What are the benefits of quota sampling
- Convenient way of creating a sample
- Sample is representative of the population
- Saves time as pre-counting the categories isn’t needed
What are the potential problems with quota sampling
- May lead to researchers bias as individuals are targeted to fill the quotas
- cross over between groups may make the sample less representative
- If quotas filled by opportunity sampling, bias may arise
