Sampling Techniques

Question 1

Explain Systematic Random sampling

Answer 1

• Involves taking every ‘nth’ participant from sampling frame
• e.g every 5th name on register
• researcher will randomly select a random number to start and pick every 5th name until required num of participants are chosen

Question 2

Explain stratified random sampling

Answer 2

• if researcher want sample to reflect age and gender of population
• involves dividing population into strata or subgroups
• Sample is drawn randomly from each stratum in proportion to their numbers in the population

Question 3

2 Strengths of random sampling methods

Answer 3

1. Bias is reduced as researcher has no influence over who is selected
2. samples are selected that aim to be representative of the population

Question 4

2 Weaknesses of random sampling

Answer 4

1. Difficult and time consuming to conduct compared to non random as a sampling frame may be hard to obtain
2. Participants selected may refuse to take part so a completely representative sample may not be possible

Question 5

Explain Snow ball Non-random sampling

Answer 5

• used when it’s hard to access a group e.g drug users,gang members
• Researcher contacts one member of the population,gradually gaining their confidence and trust until they refer the researcher to other in the group

Question 6

Explain Quota Non-Random sampling

Answer 6

• Used by market researchers who interview people on the street
• Have to interview an exact quota of people from certain categories in proportion to their numbers in wider sample

Question 7

Explain Opportuntiy Non-Random Sampling

Answer 7

• Researcher selects participants who are most easily available at time of study

Question 8

2 Strengths of Non-random sampling

Answer 8

1. Convenient methods as they save time and effort in comparison to probability sampling methods
2. maybe the only way a researcher can obtain a sample

Question 9

2 weaknesses of Non-random sampling

Answer 9

1. biased as researcher has control over who is selected
2. a representative sample cannot be selected so findings cannot be generalised to wider population