Sampling

• Target population is every member of the group that the researcher plans to study. Researchers conduct their study on smaller samples from the target population. The results from the study are then assumed to apply to all members of the target population (generalisation).
• Random sampling is when each member of the target population has a mathematically equal chance of being in the experiment's sample.
• Conducting a random sample:

  • Gather a list of the entire target population.
  • Enter names in a computer database.
  • Randomly generate the names to obtain a sample.
• Strengths of random sampling:

  • Avoids researcher bias - Researcher cannot choose the participants they want to study, avoiding the possibility of them picking participants they feel are likely to give a preferred result.
• Limitations of random sampling:

  • Unrepresentative - By chance, there may be too many of one gender with little to no participants for the other.
  • Time consuming and difficult to gather a full list for the large target population.
• Systematic sampling is when participants are chosen from a list of the target population. This is when every nth person is chosen to form the sample (eg 5th, 10th or 100th name).
• Conducting a systematic sample:

  • Obtain a full list of the entire target population.
  • Read down the list selecting every nth participant to form the sample.
  • Continue until the sample required is chosen.
• Strengths of systematic sampling:

  • Avoids researcher bias - They cannot choose the participant they want in their sample.
  • If there is an existing target population (eg student register of a school) it can be very quick.
• Limitations of systematic sampling:

  • Unrepresentative by chance.
  • Target population being large may make obtaining a full list difficult.
• Opportunity sampling is when the researcher directly asks members of the target population to take part in the research. This is likely to be participants the researcher has easy access to and is familiar with.
• Conducting an opportunity sample:

  • Researcher asks directly for participants to take part in the research.
  • Any individual who agrees is added to the sample until the number of participants required is met.
• Strengths of opportunity sampling:

  • Faster to obtain a sample, reducing the time taken to conduct the study and reducing the cost involved compared to more complex sampling methods.
• Limitations of opportunity sampling:

  • Researcher bias - May select participants in which they feel as though are more likely to produce a preferred result.
  • Unrepresentative - Participants chosen had immediate access to researcher (eg studies conducted in universities are likely to have a young population so will not be generalisable to the rest of the population).
• Volunteer sampling is when participants offer to take part in a study after finding out about the research. This could be after seeing an advertisement in a newspaper or online.
• Conducting a volunteer sample:

  • Advertisements are placed where they are likely to be seen by the members of the target population (eg gym for fitness enthusiasts).
  • The advert would include contact details and the researcher would enrol the volunteer into the sample when they are contacted by the volunteer.
• Strengths of volunteer sampling:

  • Large number of volunteer especially if the news or website is widely read.
  • Easy to gather a sample as participants put themselves forward to take part, rather than finding out individually and being asked.
• Limitations of volunteer sampling:

  • Sample may not be generalisable to the target population due to volunteer bias where the types of participants who volunteer to take part are likely to have different characteristics to the target population and are more likely to be friendlier and have more free time available.
• Stratified sampling is when participants are selected from within a group. The characteristics of participants within the sample are in the same proportion as found within the target population.
• Conducting a stratified sample:

  • Strata / subgroups are identified along with their proportion in the target population (eg gender, ethnicity and education level).
  • Random sampling is then used to select the number of participants required from within each subgroup (eg 10% graduates and 90% non-graduates in the target population would result in 1 graduate and 9 non-graduates in a sample of 10)
• Strengths of stratified sampling:

  • Representative of the larger target population meaning the results would be generalisable to the target population.
  • Avoiding researcher bias as participants are chosen randomly from within each stratum.
• Limitations of stratified sampling:

  • Not every characteristic can be included in the sample and the researcher decides which strata are important, resulting in bias.
  • Time consuming.