Sampling (20) Flashcards
Sampling
A group of individuals with the same social characteristics of the target population selected from a wider population
Target Population
The whole group that is being studied
Sampling Frame
Members of the target population from which the sample is drawn
Population
The total number of people in a group or area
Why do they use Sampling?
It is impractical to talk to everyone in a group so a small representative section is talked to represent the whole group.
Representative Samples
Samples are a smaller group that shares the same social characteristics of the large group being studied.
Random Sampling
The simplest and most basic type of sample.
Like drawing names from a hat or raffle tickets from a tombola drum.
In random sampling, everyone in the population has the same chance of getting chosen.
Advantages of Random Sampling
+Can produces a representative sample
+Everyone in the sampling frame has an equal chance of being chosen
Disadvantages of Random Sampling
- Requires complete/up to date sampling frame
- Any problems with the frame may cause problems
- Participants may be geographically spread out making the research impractical and risking representativeness
Stratified Random Sampling
Choosing people at random but from predefined categories designed to reflect the characteristics of the target population. Groups are created to reflect social class, gender, ethnicity, age groups and anything else considered relevant.
Advantages of Stratified
+If the target population comprised ten per cent from black and minority ethnic groups (BME) then ten per cent of the sample should be drawn from this group. This will improve representativeness. Adequate representation of all subgroups can be ensured
+Is superior to simple random sampling because the process of stratifying reduces sampling error and ensures a greater level of representation.
+When there is homogeneity within strata and heterogeneity between strata, the estimates can be as precise (or even more precise) as with the use of simple random sampling.
Disadvantages of Stratified
- Requires the knowledge of strata membership. The requirement to be able to easily distinguish between strata in the sample frame may create difficulties in practical levels.
- Research process may take longer and prove to be more expensive due to the extra stage in the sampling procedure.
- The choice of stratified sampling method adds certain complexity to the analysis plan
Systematic Random Sampling
This chooses people for a sample by drawing the nth person from the sampling frame.
Every third, fifth or tenth name is chosen for example.
Advantages of Systematic Random Sampling
+Easy to Execute and Understand. They are easy to construct, execute, compare, and understand. Able to work within tight budget constraints.
+Control and Sense of Process. A systematic method also provides researchers and statisticians with a degree of control and sense of the process. This might be particularly beneficial for studies with strict parameters or a narrowly formed hypothesis, assuming the sampling is reasonably constructed to fit those parameters.
+Low Risk Factor. The primary potential disadvantages of the system carry a distinctly low probability of contaminating the data.
Disadvantages of Systematic Random Sampling
-Assumes Size of Population Can Be Determined or can be reasonably approximated.
-Need for Natural Degree of Randomness
A population needs to exhibit a natural degree of randomness along with the chosen metric. If the population has a type of standardized pattern, the risk of accidentally choosing very common cases is more apparent.
-Greater Risk of Data Manipulation because researchers might be able to construct their systems to increase the likelihood of achieving a targeted outcome rather than letting the random data produce a representative answer. Any resulting statistics could not be trusted.