Sampling

Question 1

Random sampling definition and pros and cons

Answer 1

• when all participants have an equal chance of being selected
• this is good cause its free from research bias (no influence over who is selected)
• This is bad cause its time consuming and can be difficult to conduct, and there is no guarantee that people selected are representative

Question 2

Stratified sample definition and pros and cons

Answer 2

• The researcher identifies the different types of people that make up the target population and work out the proportion needed for the sample to be representative (strata)
  
  • This is good cause it avoid research bias and it is designed to be representative of the population
  • This is bad cause stratification os not perfect (if we do not identify all of the key features we need to be Careful about generalizing)

Question 3

Systematic sample definition and pros and cons

Answer 3

• Every nth members of the target population is selected and a sampling frame is produced
  
  • This is good cause it avoids research bias as once the system has been established the researcher has no influence over who is chosen. And representative
  • This is bad cause it can also be difficult to achieve and time consuming. There is also no guarantee it will be truly representative

Question 4

Opportunity sample definition and pros and cons

Answer 4

• Those people who are available at the time and willing too take part
  
  • This is good cause it’s a quick and easy way of choosing participants and is convenient
• This is bad cause researcher bias - could approach people who look helpful. Unrepresentative of the target population

Question 5

Volunteer sample definition and pros and cons

Answer 5

• Participants put themselves forward to be part of a sample (self-selection)
  
  • This is good cause its easy and requires minimal input, so is less time consuming
  • This is bad cause volunteer bias (if u sign up you are prolly a specific type of person)