Key Words

• Target Population - The group you want to study
• Sampling - This is the process of selecting a representative group from the population for studying
• Sample - This is the group of people who take part in the investigation
• Participants - The people who take part in an investigation
• Generalisability - Refers to the extent to which we can apply the findings of our research to the target population we are interested in
• Non-directional (two-tailed) hypotheses - There is 'a difference' but we don't say which way
• Random sampling - Members of a 'population' have an equal chance of being selected (e.g. being drawn out of a hat)
• Systematic sampling - Participants are selected by taking every nth person from a list
• Operationalisation - This is the process of making variables physically measurable or testable
• The Null hypothesis - This hypotheses states that the IV has no effect on the DV, so the sentence starts with 'there is no difference'
• Stratified sampling - A mini reproduction of the population, they use ratios and randomly select from stratas
• Opportunity sampling - Anyone who happens to be available at the time and at the place, who fulfils criteria of sample get asked to take part
• Directional (one-tailed) hypotheses - A hypothesis that states the direction in which the results are to go
• Correlation - A correlation is a relationship between two variables
• Positive Correlation - Shows that as one variable increases the second variable increases (or as one variable decreases, the second variable decreases)
• Negative correlation - Shows that as one variable increases the second variable decreases
• The alternate hypothesis (one-tailed or directional) - There will be a positive/negative relationship
• The alternate hypothesis (two-tailed or non-directional) - There will be a relationship between
• Laboratory experiments - Are carried out under controlled conditions, here we have an artificial environment with tight control over variables
• Field experiments - Are carried out in a natural environment with the independent variable manipulated by researchers (natural environment for the participants e.g. school or hospital)
• Quasi-experiments - Membership determined by conditions beyond the control of the experimenter, focused on the participant's characteristics (for example if the performance of males and females is being compared, participants cannot be randomly allocated to conditions
• Natural experiments - Where the independent variable is naturally occuring, for example studying an island before TV and then after TV was introduced in terms of levels of aggression in children
• Ethics - These are a set of guidelines which psychologists carrying out research should follow
• Primary data - First hand data, collected by the researcher to study their aim
• Secondary data - Data had been collected by someone else for their aim, second hand data, data may have been published in some form (e.g. government and public sector reports, websites and books)
• Meta-analysis - This combines the results from multiple studies to increase power, improve estimates of the size of the effect and/or to resolve uncertainty when reports disagree
• Matches pairs design - An experimental design where pairs of participants are matched on important characteristics and one member allocated to each condition of the IV
• Independent measures design - An experimental design where each participant takes part in both/all conditions of the IV
• Self selected sampling - volunteers
• Null hypothesis (correlational) - There is 'no relationship' between the variables
• Situational variables - These extraneous variables are related to the testing of the situation, like noise, lighting or temperature in the environment. They tend to affect all participants
• Participant Variables - These extraneous variables are related to individual characteristics of each participant that may impact how he or she responds, these factors include background differences, prior knowledge, health status, mood, anxiety, intelligence and awareness and other characteristics that are unique to each person
• Ranomization (allocation) - The process of using chance to decide the order in which participants experience the experimental or control condition when a repeated measures design is used e.g. names in a hat (this happens post sampling)
• Order effects - Practice and fatigue (or boredom), which is a weakness of repeated measures design, balanced across conditions through counter balancing
• How do you do counter balancing?

  Used with repeated measures design; Split participants into 2 groups.

  Group 1 completes IV A and then IV B

  Group 2 completes IV B and then IV A
• Why do you do counter balancing?


  To balance the order effects across conditions or to allow order effects to be distributed evenly across both conditions
• How do you match people in a Matched pairs design?

  Pick an important variable, you pre-test participants and then rank them. You pair the top two participants and then the 3rd and 4th. You then allocate one person from each pair to each IV group
• Why do you do a matched pairs design?


  A matched pairs design reduces individual differences/extraneous variables in the form of participant variables
• Objective means when no bias is possible
• Subjective means when bias is possible