types of sampling

Question 1

outline how you would take a stratified sample

Answer 1

→ dividing the target population into important sub-categories
→ selecting members of these sub categories in the population they occur in which is your target population

Question 2

what are the cons of stratified sampling

Answer 2

→ time consuming - knowing the sub groups and dividing the pop into categories and then selecting the pps to match these
→ the research requires knowledge of the sub groups and categories of the population
→ the identified strata cannot reflect all the differences between the people of the wider community

Question 3

outline an example of how to do a stratified sample

Answer 3

→ if the target population consisted of 75% women and 25% men and we wanted a sample of 20, we would have 15 women and 5 men

Question 3

what are the strengths of stratified sampling

Answer 3

→ sample is more representative of the target population
→ easy to generalise as the sample is more representative
→selection is unbiased as it is based on the sub groups in society

Question 4

how is random sampling carried out

Answer 4

→ selecting people, in a way that everyone has a fair chance of being selected
→ this is achieved by using a random number generator to randomly chose a partner

Question 5

identify 5 types of sampling methods

Answer 5

→ opportunity sampling
→ randomly sampling
→ systematic sampling
→ stratified sampling
→ volunteer sampling

Question 6

what are the strengths of random sampling

Answer 6

→ no research bias - researcher has no influence of who is picked - more likely to be representative
→ results are fairly representative - be more generalised to the target population

Question 7

cons of random sampling

Answer 7

→ time consuming and impractical - need to have a list of all the members of the population (sampling frame) and then contacting them
→ volunteer bias - pps can refuse to take part so can end up with an unrepresentative → researchers need an adequate sample size to cope with the problem
→ non-representative - as all of one gender / imbalance of genders could be selected randomly which would not be a true sample of the target population

Question 8

how is volunteer sampling carried out

Answer 8

→ people volunteer (choose) to take part
→ selecting themselves as pps of a study often by replying to adverts (through a newspaper ad or a notice on a noticeboard)

Question 9

pros of volunteer sampling

Answer 9

→ random - variety of people with a variety of occupations
→ willingness of pps - they are choosing to take part so pps are less likely to jeopardise the study and its results
→ not much effort is required to obtain the same (not time consuming )

Question 10

cons of volunteer sampling

Answer 10

→ volunteer bias - the study may attract a particular profile of a person which means that generalisability is then affected and the extent to which the findings of a study can be application to other settings
→ volunteers are often eager to please, which causes demand characteristics which means they may behave how they think the researcher wants the to
→ motivations like money could be driving the pps so pps may not take the study seriously influencing the results

Question 11

how is systematic sampling carried out

Answer 11

a pre-determined system is used whereby every nth member is selected from the sample frame
→ this numerical selection is applied consistently

Question 12

how can sampling lead to problems with bias

Answer 12

→ some types of sampling allows the researcher to have influence over who takes part in the research
→ this can lead of bias as the researcher may pick people they know or people from a particular group they prefer, making the sample unrepresentative thus the findings cannot be generalised and lacks validity

Question 13

pros of systematic sampling

Answer 13

→ no researcher bias - researcher cannot personally pick pps they would like to take part in the study → there is no control of who is randomly chosen as pps so the researcher cannot chose those who they think will support the hypothesis / no investigator effects
sample is more likely to be reasonably representative → the results can be generalised to the target population

Question 14

cons of systematic sampling

Answer 14

→ finding the target population and putting them in order takes time as it would require the gathering of the names of all members of the target population
→ it is possible that by chance every pp picked may be a specific type of pp e.g. every nth member selected from the list may be a male → therefore the sample might not be representative of the target population
→ selection process can interact with a hidden period trait, if every 10th person is a 19 year old shop worker then they are the only people in the sample
→ may be non-representative as all of one gender could be selected systematically → not a true example of the population

Question 15

how is opportunity sampling carried out

Answer 15

→researcher chooses pps who are members of the target population and are willing and able to take part
→ this is done by approaching and asking members of the target population if they would like to take part]→ the researcher continues until they have the desired amount of pps

Question 16

pros of opportunity sampling

Answer 16

→ easiest and most convenient method as you can use the first pps you find which means it it less time and effort consuming to acquire your sample than other techniques
→ natural experiments use opportunity sampling as the researcher has no control over who is being studied

Question 17

cons of opportunity sampling

Answer 17

→less representative than other methods as it will only reflect those who are in the same vicinity as where the researcher sought the pps → it will only reflect members of the target population who were present at the time → if it is less representative than the findings it will be less generalisable to the target population
→ the sample may be biased as the investigator has full control over who they choose to be a part of the sample (researcher bias) → they may pick pps that they think will support their hypothesis / decrease validity