Sampling Flashcards
Simple random sampling
Every sample has equal chance of being selected
Simple random sampling method
In sampling frame each item has identifying number. Use random number generator, or ‘lottery sampling’ (names in a hat).
Simple random sampling method advantages
- Bias free
- Easy and cheap to implement
- Each number has a known equal chance of being selected
Simple random sampling method disadvantages
- Not suitable when population size is large
- Sampling frame needed
Systematic sampling
Required elements are chosen at regular intervals in ordererd lists e.g. every 4th element
k= pop size(N)/ samp size(n)
starting at random between 1 and k
Systematic sampling advantages
- Simple and quick to use
- Suitable for large samples/populations
Systematic sampling disadvantages
- Sampling frame needed
- Can introduce bias if sampling frame is not random
Stratified sampling
Population divided into groups (strata) and a simple random sample carried out in each group. Same proportion sampled from each strata Samp size(n) / pop size (N) Used when sample is large and population naturally divides into groups
Stratified sampling advantages
- Reflects the population structure
- Guarantees proportional representation of groups within population
Stratified sampling disadvantages
- Sampling frame needed
- Within the strata, the problems are the same as for any simple random sample
- Population must be clearly classified into distinct strata (no overlap)
Quota sampling
Population divided into groups according to characteristics. A quota of items/people is set to try and reflect the group’s proportion in the whole population. Interviewer selects the actual sampling units
Quota sampling advantages
- Allows small sample to still be representative of population
- No sampling frame required
- Quick, easy, inexpensive
- Allows for easy comparison between different groups in population
Quota sampling disadvantages
- Non random sampling can introduce bias e.g. interviewer bias
- Population must be divided into groups, which can be costly or inaccurate
- Increasing scope of study increases number of groups, adding time/expense
- Non-responses are not recorded
Opportunity sampling
Sample taken from people who are available at time of study, who meet criteria.
Opportunity sampling advantages
- Easy to carry out
- Inexpensive
Opportunity sampling disadvantages
- Non random sampling can introduce bias e.g. interviewee bias
- Unlikely to provide a representative sample
- Highly dependant on individual researcher
Cluster sampling
Cluster sampling is a probability sampling technique where researchers divide the population into multiple groups (clusters) for research. Researchers then select random groups with a simple random or systematic random sampling technique for data collection and data analysis.
Population definition
The whole set of items that are in interest
Sample definition
Some subset of the population to represent the population
Census definition
A survey carried out to all items in a population
Outlier definition
A point that differs significantly from the others
Sampling frame definition
A list of all items to be sampled
Sampling fraction definition
The proportion of the available items that are actually sampled.
Bias definition
A model which is not representative of the population which is likely to include some prejudice
Sampling error definition
The difference between your estimate of the parameter and the actual value
Census advantages
Takes everyone opinions into account
Census disadvantages
Time consuming and costly
Cluster sampling advantages
- Easy to carry out
- Simple random for selecting clusters
Cluster sampling disadvantages
- Differences in location
- Might not be convenient (makes sense for shops)
