Research Methods

• Process of scientific study

  • Observation of subjects
  • Formulation of a theory
  • Construction of a testable hypothesis
  • Empirical testing of the hypothesis
  • Replication and validation
  • Falsifiability
• Empirical


  Information gained through direct observation rather than reasoned argument or belief
• Objective


  Data should not be affected by the expectations of the researcher. Data collection should be systematic and free from bias. Without objectivity there is no way of knowing if our findings are valid.
• Controlled


  All extraneous variables need to be controlled in order to be able to establish cause (IV) and effect (DV).
• Replication


  Scientists record their methods and standardise them carefully so that the same procedures can be followed in the future (replicated). Repeating a study is the most important way to demonstrate the validity of an observation or experiment. If the outcome is the same, then this indicates that the original findings are valid.
• Hypothesis testing


  A statement is made at the beginning of an investigation that serves as a prediction and is derived from a theory. There are different types of hypotheses (null and alternative), which need to be stated in a form that can be tested (i.e. operationalized and unambiguous).
• Predictability


  We should be aiming to be able to predict future behavior from the findings of our research.
• The philosopher Thomas Kuhn suggested what distinguishes scientific disciplines from non-scientific disciplines is a shared set of assumptions and methods known as a paradigm. He argued that Psychology lacked a universally accepted paradigm and was therefore best seen as pre-science. Natural sciences on the other hand have a number of principles at their core. Eg biology has the theory of evolution. By contrast, psychology has many conflicting approaches.
• Paradigm shift


  Occurs when paradigms are challenged more and more over time until there is so much evidence that the old paradigm can no longer be accepted such that new paradigms will take its place. In psychology there was a paradigm shift from the psychoanalysis of the psychodynamic approach to the behaviourist approach and then again to the cognitive approach and then to the biological approach.
• Reliability


  Whether something is consistent. In the case of a study, whether it is replicable.
• Types of reliability


  • Internal reliability - assesses the consistency of results across items within a test
  • External reliability - refers to the extent to which a measure varies from one use to another
• Internal reliability


  Assessed using the split half method - measures the extent to which all parts of the test contribute equally to what is being measured
• External reliability


  • Assessed using inter-rater reliability - extent to which two or more observers are observing and recording behaviour in the same way
  • Assessed using test-retest reliability - involves presenting the same participants with the same test or questionnaire on two separate occasions and seeing whether there is a positive correlation between the two
• Validity


  Whether something is true (measures what it sets out to measure)
• Types of validity


  • Internal validity - the extent to which a test is consistent within itself
  • External validity - whether it is possible to generalise the results beyond the experimental setting (i.e: onto the wider population)
• Internal validity


  Factors that affect it include participant variables, lack of experimental control, situational variables, and researcher bias
• Types of internal validity

  • Content validity - the extent to which the questions/measurements in the study measure what we think we are measuring
  • Face validity - simple way of assessing whether a test measures what it claims to measure
  • Split-half method - comparing two halves of a test, questionnaire, or interview
• External validity


  Types include ecological validity, mundane realism, population validity, temporal validity, and concurrent validity
• Aim


  The researcher's area of interest - what they are looking at
• Hypothesis


  A precise, testable statement of what the researchers predict will be the outcome of the study
• Types of hypotheses


  • Alternative hypothesis - states that there is a relationship between the two variables being studied
  • Null hypothesis - states that there is no relationship between the two variables being studied
  • Nondirectional hypothesis - predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified
  • Directional hypothesis - predicts the nature of the effect of the independent variable on the dependent variable
• Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct.
• We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.
• How to write a hypothesis

  1. Identify the key variables in the study

  2. Operationalise the variables being investigated

  3. Decide on a direction for your prediction

  4. Write your hypothesis
• Representative sample


  A sample that that closely matched the target population as a whole in terms of key variables and characteristics
• Target population


  The group that the researchers draws the sample from and wants to be able to generalise the findings to
• Sampling techniques


  • Random sampling
  • Stratified sample
  • Systematic sample
  • Opportunity sample
  • Volunteer sample
• Pilot study


  A small scale study conducted to ensure the method will work according to plan. If it doesn't then amendments can be made.
• Experimental designs


  • Independent groups design - each participant only takes part in one condition of the IV

  Repeated measures design - each participant takes part in all conditions of the IV

  Matched pairs design - pairs of participants are matched on important characteristics and one member allocated to each condition of the IV
• Operationalising variables


  Clearly describing the variables (IV and DV) in terms of how they will be manipulated (IV) or measured (DV)
• Independent variable


  The variable that the experimenter manipulates (changes)
• Dependent variable


  The variable that is measured to tell you the outcome
• Extraneous variable


  Variables that if not controlled may affect the DV and provide a false impression that an IV has produced changes when it hasn't
• Confounding variable


  An extraneous variable that varies systematically with the IV so we cannot be sure of the true source of the change to the DV
• Control of extraneous variables


  • Order effects

  Participant variables

  Situational variables

  Investigator effects
• Order effects


  Can occur in a repeated measures design and refers to how the positioning of tasks influences the outcome e.g. practice effect or boredom effect on second task. These can be controlled using counterbalancing.
• Participant variables


  Participants in one group may differ in a significant way from participants in another group. This risk can be reduced via random allocation or by matched pairs.
• Situational variables


  Factors in the environment that may affect the DV. These can be reduced by using a standard procedure.
• Investigator effects


  These result from the effects of a researcher's behaviour and characteristics on the participants and the study.
• Systematically with the IV so we cannot be sure of the true source of the change to the DV