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1
Q

Sampling

A

A group of individuals with the same social characteristics of the target population selected from a wider population

2
Q

Target Population

A

The whole group that is being studied

3
Q

Sampling Frame

A

Members of the target population from which the sample is drawn

4
Q

Population

A

The total number of people in a group or area

5
Q

Why do they use Sampling?

A

It is impractical to talk to everyone in a group so a small representative section is talked to represent the whole group.

6
Q

Representative Samples

A

Samples are a smaller group that shares the same social characteristics of the large group being studied.

7
Q

Random Sampling

A

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.

8
Q

Advantages of Random Sampling

A

+Can produces a representative sample

+Everyone in the sampling frame has an equal chance of being chosen

9
Q

Disadvantages of Random Sampling

A
  • 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
10
Q

Stratified Random Sampling

A

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.

11
Q

Advantages of Stratified

A

+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.

12
Q

Disadvantages of Stratified

A
  • 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
13
Q

Systematic Random Sampling

A

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.

14
Q

Advantages of Systematic Random Sampling

A

+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.

15
Q

Disadvantages of Systematic Random Sampling

A

-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.

16
Q

Quota Sampling

A

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.

17
Q

Advantages of Quota Sampling

A

+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

18
Q

Disadvantages of Quota Sampling

A
  • 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
19
Q

Non-Representative Sample

A

Sample that isn’t representative

20
Q

Snowball Sampling

A

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.

21
Q

Snowball Sampling Advantages

A

+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.

22
Q

Snowball Sampling Disadvantages

A
  • 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.
23
Q

Volunteer Sample

A

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.

24
Q

Advantages of Volunteer Sampling

A
  • More ethical because participants have approached researcher
  • May have an interest in the subject so they are less likely to give biased information
25
Q

Disadvantages of Volunteer Sampling

A
  • 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.
  • Could take a long time to get enough people to do an experiment
  • Rules out certain occupations and types of people - unrepresentative
26
Q

Purposive Sampling

A

A different take on sampling. Researchers find participants to suit their purpose.
In order to disprove findings of other research by finding the ‘exception to their rule’.
To improve the representativeness of a study by finding people to make up for bias in the original sample.

27
Q

Advantages of Purposive Sampling

A
  • Purposive sampling is one of the most cost-effective and time-effective sampling methods available
  • Purposive sampling may be the only appropriate method available if there are an only limited number of primary data sources who can contribute to the study
  • This sampling technique can be effective in exploring anthropological situations where the discovery of meaning can benefit from an intuitive approach
28
Q

Disadvantages of Purposive Sampling

A
  • Vulnerability to errors in judgment by researcher
  • Low level of reliability and high levels of bias.
  • Inability to generalize research findings
29
Q

Opportunity Sampling

A

Means making the most of situations or opportunities in which the research population is likely to be found.

30
Q

Opportunity Sampling Advantages

A

+Less Time Consuming

+Easiest Method to use

31
Q

Opportunity Sampling Disadvantages

A

-Participants may not be a representative sample of the target population

32
Q

Access to the Group

A

It can be more difficult to acquire a certain type of group due to topics of research or the nature of that population.

33
Q

Gatekeeper

A

People who control whether researchers can have access to ppts (Managers for example, Prison Boards)

34
Q

Interpretivism Criticisms of Sampling Procedures

A

Representativeness is largely a positivist concern
Reject that any idea of rear any sample is representative
Interpretivism is concerned with individual meanings, thoughts and motives
In this context, every individual is unique

35
Q

Pilot Studies

A

Bias can be discovered before it seriously undermines the research is through the employment of pilot studies.
Small-scale dress rehearsals for the main research involving a sub-sample of the sample that the main research intends to use.
Pilot studies are useful because they act as an early warning system for problems that have arisen out of the operationalisation of the hypothesis or the choice of the sample.
Whether questions are clearly understood and interpreted in the same way and make sure that the questions do not upset or lead the participants

36
Q

Higher educational opportunities for South Asian Women - Bagguley and Hussain (2007)

A

The research team interviewed a total of 114 young women. Potential respondents were approached in a variety of ways. Purposive sampling was initially used in that undergraduates and current sixth-formers were approached in the public social areas of their institutions. Bangladeshi students
and recent graduates were contacted through local community centres. The samples were then further boosted through snowball sampling. A small sample of ‘widening participation’ and careers-service staff in universities were also interviewed about their policy and practice in relation to South Asian women.

37
Q

Sharp and Atherton (2007)

A

Researched the experiences of policing in the community from the perspective of young people in black and BME groups.
A snowball sample was used to gain initially by the researchers’ contacts with local youth groups and organisations.
These initial contacts then suggested further participants. They found snowballing was functional to the research since it involved participants themselves explaining the research and its purpose to others. It would have been very difficult to find enough young people willing to co-operate without this approach.

38
Q

Sampling in the Modern Day

A

Samples are generally selected using the software, which can remove bias in selection.
Sampling can only be automated once sampling lists and target populations have been identified, and this can be where the challenges of sampling for research arise, for example, in identifying secretive or deviant groups members.