Sampling and population

• The population refers to the large group of individuals who share specific characteristics that a researcher is interested in studying. It is sometimes referred to as the "target population" as it refers to a particular subset of the general population
• Populations are usually too large to study so we select a sample from it that is representative of everyone in it
• How many main ways of obtaining a sample are there?

  5
• Ideally, the sample drawn from the population would be representative of the target population so that the generalisation of the findings becomes possible, giving the research high external validity
• Define bias

  In terms of sampling, it refers to under-representing or over-representing certain groups within the sample. For example, too many younger people or too few males
• Define generalisation

  The extent to which findings from a specific sample can be applied to the population
• Opportunity sampling is selecting anyone who is willing and available to take part at the time. For example, approaching people on the street.
• Opportunity sampling is the most common form of sampling technique used in psychological research
• Strengths of Opportunity sampling

  convenient as less time and money consuming

  no target population so don't need to divide population
• Limitations of Opportunity sampling

  can be bias and unrepresentative of target population as it could be drawn from a specific location so it cant be generalised or researchers have complete control over participants so they may avoid certain participants as they don't like the look of them
• Opportunity sampling has low internal validity
• Random sampling is a form of sampling that all members of the target population have an equal chance of being selected.
• Random sampling strengths

  it's unbiased so co-founding and extraneous variables are equally divided between groups, increasing internal validity
• weaknesses of Random sampling

  time consuming and a list of target population may be hard to obtain so you could have an unrepresentative sample

  Participants may also refuse to partake
• Systematic sampling is where every nth member of the target population is selected. E.g. every 3rd house on the street
• strengths of Systematic sampling

  method is objective, once system for selection is established, researcher has no influence over who is chosen so there is no bias and generalisability is high
• Limitations of Systematic sampling

  time consuming

  Participants may refuse to partake
• Stratified sampling is where the composition of the sample reflects the proportion of people in certain subgroups within the target population
• Strengths of Stratified sampling

  produces representative sample as its designed to accurately reflect the composition of the population

  easily generalisable
• Weaknesses of Stratified sampling

  not perfect

  can't reflect all ways people are different

  Representation of the target population isn't possible
• Volunteer sampling is when participants select themselves to be part of the sample, self-selection
• Strengths of volunteer sampling

  easy to collect sample so less time consuming

  Participants are more engaged

  Researchers have minimal impact
• Weaknesses of volunteer sampling

  asking for participants may attract certain profiles (such as one who wants to please the researcher), this affects generalisability
• An example of Random sampling would be picking out 25 sweets from a bag at random then recording how many of each colour you get
• An example of opportunity sampling is tipping out the first 25 sweets from a bag - these are the people who are available and willing to take part in the research
• An example of volunteer sampling is putting up a poster at school asking for participants to self-select and take part in your research. You have to imagine green sweets are the most helpful and willing to take part, followed by yellow. The orange, red and purple sweets definitely won't want to take part. You are still looking to recruit 25 participants but if you can't manage to get to 25 you will still have to run your experiment with as many as you can.
• An example of systematic sampling is tipping out all of the sweets in a bag and placing them in one line. Then select every third sweet and record it
• An example of stratified sampling is creating a sample of 25 sweets similar to the target population, in terms of percentage of each colour. If 15% of the sweets in your target population are green, you need to ensure that your sample of 25 only has 15% of green sweets.

  15% of 25 = 3.75, therefore you would need 4 sweets to represent your target population