Sampling

• A target population is the wider group that the researchers draws the sample from and who they want to generalise the findings to.
• A target population can be a large group/ cohort or wider community or culture.
• A target population is an entire group with specified characteristics.
• The different types of sampling methods are random sampling, stratified sampling, systematic sampling, opportunity sampling and volunteer (self-selected) sampling.
• A target population refers to the entire group of individuals that a researcher wants to study, while a sample refers to the specific group of individuals that are selected to participate in the study.
• A target population is usually too large to study in its entirety, so sampling methods are used to select smaller samples in which to study.
• An unrepresentative sample is one that does not reflect the distribution of characteristics of the target group, so cannot be generalised to the target population, and is therefore biased.
• A representative sample is a smaller group selected from the target population who have similar characteristics, which would allow us to generalise.
• Having a representative sample increases the generalisability of the results.
• Having a unrepresentative sample adds bias to the findings and limits the ability to generalise.
• Opportunity Sampling-

  This type of sampling consists of selecting anyone who is available and willing to take part in the study.
• An opportunity sample is more likely to be biased as participants are selected by the researcher themselves.
• University Students are often used of this type of sampling as they are willing and most available.
• Strength-

  Opportunity Sampling is convenient.

  As it saves time, effort and is less costly.
• Weakness-

  Likely to unrepresentative of target population, as drawn from specific areas.
• Opportunity samples may not be representative which could lead to bias. All females could be selected, as they are the only ones available at the time.
• Researcher also has complete control over the selection of their ppts.

  This means that they may get ride of certain ppts if they don't fit the guidelines of their experiment.
• Random sampling gives every member of the target group an equal chance of being selected for the sample (e.g. by assigning a number to each member or by using a random number generator).
• Random sampling is a good technique as it gives everyone a fair chance of being selected, however this can still be biased.
• Random sampling can be biased, as participants with similar characteristics can still be selected.
• Random samples require naming or numbering the target population and then using some raffle method to choose those to make up the sample. Random samples are the best method of selecting your sample from the population of interest.
• Strength-

  Free from research bias.

  Researcher has no influence on who is selected.

  Therefore they won't select people who will better their hypothesis.
• The advantages are that your sample should represent the target population and eliminate sampling bias
• The disadvantage is that it is very difficult to achieve (i.e., time, effort, and money).
• Weaknesses-

  Difficult and time consuming to conduct.

  To complete a list of the target population is difficult to obtain.
• Ppts may refuse to take part in the study, which results in further bias.

  May not be representative for whole population.
• Stratified Sampling-

  During stratified sampling, the researcher identifies the different types of people that make up the target population and works out the proportions needed for the sample to be representative.
• A list is made of each variable (e.g., IQ, gender, etc.) that might have an effect on the research. For example, if we are interested in the money spent on books by undergraduates, then the main subject studied may be an important variable.
• For example, students studying English Literature may spend more money on books than engineering students, so if we use a large percentage of English students or engineering students, our results will not be accurate.
• We have to determine the relative percentage of each group at a university, e.g., Engineering 10%, Social Sciences 15%, English 20%, Sciences 25%, Languages 10%, Law 5%, and Medicine 15%. The sample must then contain all these groups in the same proportion as the target population (university students).
• Subgroups are called strata.
• Population is randomly sampled in each state.
• The advantage is that the sample should be highly representative of the target population, and therefore we can generalize from the results obtained.
• No researcher bias.

  Once groups have been divided into strata, ppts make up the numbers randomly.
• This produces a representative sample and shows the generalised findings of the population.
• The disadvantage of stratified sampling is that gathering such a sample would be extremely time-consuming and difficult to do. This method is rarely used in Psychology.
• Requires detailed knowledge of the populations characteristics, which may not be available.
• Very time consuming dividing a sample into strata, randomly selecting them from each.
• Systematic Sampling-

  Systematic sampling is a method where every nth individual is selected from a list or sequence to form a sample, ensuring even and regular intervals between chosen subjects.
• Participants are systematically selected (i.e., orderly/logical) from the target population, like every nth participant on a list of names.