U1 AOS3

• Aim


  What you want to test out
• Control group


  Not exposed to the independent variable, provides a baseline measure for comparison
• Experimental group


  Exposed to the independent variable, determines whether the IV made a change in the DV
• Allocation


  When participants are assigned to the different groups in an experiment
• Research hypothesis


  A testable prediction about the relationship between two or more variables
• Research Population


  The entire group of research interest that the sample is taken from
• Population vs. Sample


  • Population - The entire group of research interest
  • Sample - Smaller group of research participants taken from the larger population
• Convenience sampling


  • Surveying people at the entry of Chadstone shopping centre
  • Advertising study on social media and drawing sample from people who respond
• Convenience sampling


  Involves selecting participants who are readily available without any attempt to make the sample representative of a population
• Random sampling


  Ensures every member of the research population has an equal chance of being selected to be part of the sample
• Stratified sampling


  Involves dividing the population into groups/strata based on specific categories and then selecting a sample from each strata in the same proportion that they occur in the population
• Representative sample


  Reflects the characteristics of the wider research population
• Biased sample


  A sample that does not adequately represent the key characteristics of its population
• Allocation


  The process of assigning participants to different groups in an experiment
• For any two variables which are measured in a correlational study, there are three possible relationships between them — positive, negative and zero (no relationship)
• Positive correlation


  Two variables change in the same direction - as one variable increases, the other variable tends to increase (and vice versa)
• Negative correlation


  Two variables change in opposite directions - as one variable increases, the other variable tends to decrease (and vice versa)
• Zero correlation


  There is no relationship between two variables
• Quantitative data


  Information that is expressed numerically, information about the 'quantity' or amount of what is being studied
• Examples of quantitative data include raw data that have not been analysed in any way, such as lengths or weights of prematurely born infants, and percentages of participants who respond with 'Yes' or 'No' to survey questions
• Simulation


  Realistic way to investigate behaviour and/or mental process of someone in that environment
• Simulation has the limitation of artificiality - difficult to generalise the results to a real life setting as participants may behave differently knowing that they are in a simulation
• Types of data


  • Quantitative
  • Qualitative
• Quantitative data


  Information that is expressed numerically, about the quantity or amount of what is being studied
• All types of mental experiences and behaviours can be described in quantitative terms as amounts or numbers
• Objective data


  Information that is observable, measurable, verifiable and free from the personal bias of the researcher
• Subjective data


  Information that is based on personal opinion, interpretation, point of view or judgment
• Discrete data


  A type of quantitative data that includes non-divisible figures and statistics you can count
• Continuous data


  A type of quantitative data that represents precise measurements of nearly any numeric value
• Descriptive statistics


  Measures of central tendency
• Extraneous variables


  Variables that aren't the IV or DV but can have an unwanted influence on the IV
• Examples of participant variables

  • Learning ability
  • Mood
  • Weight
  • Athletic ability
  • Age
  • Gender
  • Intelligence
  • Personality
  • Memory ability
• Examples of situational variables


  • Use of non-standardised instructions
  • Use of non-standardised procedures
  • Experimenter effects
• Controlling extraneous variables


  1. Random allocation

  2. Random sampling

  3. Use of standardised procedures

  4. Randomisation
• Confounding variable


  A variable other than the IV that may have an unwanted effect on the DV which can be confused with that of the IV
• Internal validity


  The extent to which a measure accurately measures what it is supposed to be measuring
• External validity


  The extent to which the results of a study can be generalised to other situations and people
• Conclusion


  A decision about what the results obtained from a research investigation mean
• Generalising conclusions to the research population

  Stating how the findings of the experiment/study conducted on the sample can apply to other people in the research population
• Ethical concepts


  • Respect
  • Justice
  • Integrity
  • Beneficence
  • Non-maleficence