Sampling Technique

• Random sampling

  Every mem of target population has = probability of being selected, assign number, generate random number

  +Unbiased and representative sample where everyone has same chance of being selected.

  -Time-consuming, getting names of everyone in target population

  -Hard to carry out with large pop, sometimes impossible to get all details.
• Opportunity sampling

  Select anyone willing and available to take part, researcher chooses who to approach.

  +Quick and cost effective

  +Suitable were res needs no cont over whos being studied (non specific people)

  -Biased sample, often used on uni students, not representative of target pop.
• Volunteer Sampling

  Parts select themselves (self-selection), e.g. responding to newspaper AD

  +Cost effective (only have to make AD)

  +Reach wide variety of participants (many see AD and respond)

  -Pot not representative (only helpful people or people interested in topic), may be more obedient (DC)/motivated to take part-affects result.
• Systematic Sampling

  Every ‘nth’ person selected from sampling pool, target pop put in certain way (age, gender)

  +No research bias as ‘nth’ person selected.

  -May produce an unrepresentative sample if ‘nth’ has similar characteristics.

  -Not every ‘nth’ agrees to participate.
• Stratified Sampling

  Sample reflects prop of subgroups (strata) in target pop (e.g. prop of males to females) Step 1: ID strata (gender) Step 2: prop needed to create rep sample random selected.

  +Most representative sampling tech, reflects the exact proportion of target pop

  -Difficult and time cons to ID subgroup, getting names, details, calculation

  -People selected may be unwilling to take part.

  -Hard to carry out with large target pop.