Populations and sampling

Populations and sampling

1. Population: A group of people who are the focus of the researcher's intrests

2. Sample: A group who take part in a research investigation. They are drawn from the target population and are presumed to be representative of that population so the results can be generalsied

3. Random sample

   • All members of the target population have an equal chance of being selected
   • 1.) Obtain list of everyone's name from target population
     • 2.) All names are assigned a number
       • 3.) Sample generated by a lottery method
   • Free from research bias as the researcher has no influence over who is selected
   • Time-consuming and difficult to obtain a list of the entire target population
   • Sample may still be unrepresentative
   • Selected participants may refuse to take part

4. Systematic sample

   • Where every nth member of the target population is selected
     • Sampling frame is produced where the entire target population are arranged a particular order and the interval may be determined randomly to reduce bias. Researcher then works through this until the sample is complete.
   • Avoids researcher bias as the researcher has no influence over who is chosen
   • Fairly representative
   • Selected participants may refuse to take part

5. Stratified sample

   • Sophisticated form of sampling where the composition of the sample reflects the proportions of people in strata within the target population
   • 1.) Researcher identifies the different strata that make up the population
     • 2.) The proportions needed for the sample to be representative are calculated
       • 3.) The participants that make up each stratum are selected using random sampling
   • Avoids researcher bias as the participants that make up each strata are randomly selected and beyond the influence of the researcher
   • Representative sample produced as it is designed to accurately reflect the composition of the population so generalising is possible.
   • The identified strata cannot reflect all differences between people so complete representation is not possible
   • Selected participants may refuse to take part

6. Opportunity sample

   • Researchers select anyone who is willing and available around the time of their study
   • A convenient method as it saves the researcher time, effort and money
   • The sample is unrepresentative of the population as it is drawn from one specific area e.g. one street so results cannot be generalised
   • Researcher bias as the researcher has complete control over the selection of participants and may avoid certain people

7. Volunteer sample

   • Participants select themselves to be part of the sample
   • A researcher may advertise in a newspaper to gather sample
   • Minimal effort required by the researcher so it is less time-consuming
   • Participant bias is an issue as asking for volunteers may attract a certain profile of person, which might affect how far findings can be generalised

8. Bias: Where certain groups may be over/under represented within the sample selected which limits the extent to which generalisations can be made to the target populations

9. Generalisation: The extent to which findings from a particular investigation can be broadly applied to the population