Sampling (20) Flashcards
(38 cards)
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.
Quota Sampling
The researcher decides how many of each category of person should be included in the sample, but then, instead of selecting them at random from a sampling frame, the researcher goes out looking for the right number of people in each category until the quota is filled. Thus if in a sample of 500 people, the quota of women aged between 30 and 40 is 22, the researcher will look out for 22 such women and, when they have been found and interviewed, that is the quota filled.
Advantages of Quota Sampling
+Insures some degree of representativeness of all the strata in the population.
+Relatively easy to administer
+Quick and Cost-effective
+Accounts for population proportions
+A useful method when probability sampling techniques are not possible
Disadvantages of Quota Sampling
- Lacks randomness, there is a danger that bias might creep into the selection of the sample; researchers may only stop and question people who look ‘suitable’ or ‘cooperative’ or visit homes that look ‘respectable’. So not representative.
- There is a potential for selection bias, which can result in a sample that is unrepresentative of the population
Non-Representative Sample
Sample that isn’t representative
Snowball Sampling
This sampling technique involves finding and interviewing a person who fits the research needs and then asking them to suggest someone else who might be willing to be interviewed.
The original small nucleus of people grows by adding people to it in stages, much as a snowball can be built up by rolling it along the snow on the ground. The sample can grow as large as the researcher wants.
Snowball Sampling Advantages
+Is mainly used when researchers experience difficulty in gaining access to a particular group of people whom they wish to study because there is no sampling frame available or because the research population engage in deviant or illegal activities that are normally carried out in isolation or in secret.
+Snowball sampling may help you discover characteristics about a population that you weren’t aware existed. For example, the casual illegal downloader vs. the for-profit downloader.
Snowball Sampling Disadvantages
- The researcher has no control over who is nominated for the research and because samples tend to be small, there is a real risk of the sample not being representative.
- It usually impossible to determine the sampling error or make inferences about populations based on the obtained sample.
Volunteer Sample
Sociologists may advertise for research volunteers in magazines and newspapers, on university noticeboards or on the internet. However, both snowball and volunteer sampling may fail to produce representative samples. The people who take part in the research may not be typical of the research population that the sociologist is interested in.
Advantages of Volunteer Sampling
- More ethical because participants have approached researcher
- May have an interest in the subject so they are less likely to give biased information