Experiments

Cards (30)

  • Independent Variable - a factor that is directly manipulated by the experimenter in order to observe the effect of this variation on the dependant variable
  • Dependant Variable - measured by the experimenter to assess the effects of the independent variable
  • Operationalism of variables - variables must be operationalised, ie. defined in a way that they can easily be tested
  • Characteristics of experiments
    Manipulating the IV
    Controlling the extraneous variables in a controlled environment
    Measuring the DV
    Proving or disproving the null
  • Independent variable
    The experimental factor that is manipulated; the variable whose effect is being studied
  • Dependent variable
    The measurable effect, outcome, or response in which the research is interested
  • Extraneous variable
    In an experiment, a variable other than the IV that might cause unwanted changes in the DV
  • Lab experiment
    An experiment where the environment is controlled and set up by the researcher, has all 5 experiment characteristics
  • Strengths of lab experiments
    Highly controlled so a cause and effect can be established from the manipulation of the IV as extraneous variables controlled
    Standardised procedures so will be more replicable and reliable
  • Weaknesses of a lab experiment
    Lacks ecological validity so hard to generalise findings
    Demand characteristics, the participants may try to find the nature of the experiment
  • Field experiment
    An experiment conducted in the participants' natural environment
  • Strengths of field experiments
    High in ecological validity due to real setting
    Low in demand characteristics if it is covert
  • Weaknesses of field experiments
    Lack of control may mean high extraneous variables
    Hard to observe everything and measure the DV
    Cause and effect will be weaker
  • Natural (quasi) experiment
    An experiment where the IV is natural occurring and changes are observed
  • Strengths of natural experiments
    You can study an IV that is impossible or unethical to study
    High ecological validity as the IV is from real life
  • Weaknesses of natural experiments
    Low internal validity as you have to find whoever fits the IV
  • Repeated Measures
    each ppt takes part in every condition being tested. Each condition represents one level of the independent variable
  • Strengths of repeated measures
    • good control of participant variables because the same person is tested twice
    • fewer ppts are needed than with independent groups design
  • weaknesses of repeated measures
    • order effects are produced eg. ppts may do better the second time due to practice or worse due to boredom
    • may make research aims obvious -> ppts may guess the experimenters purpose
  • how can you control order effects
    Counterbalancing
    -> one half completes the tasks in one order, the other half in the other order
  • Independent Measures
    different ppts are allocated two or more experimental groups representing different levels of the independent variable.
    There may be a control group
  • strengths of independent measures
    • avoids order effect as each ppt is only tested once
    • avoids ppts guessing the experimenters aim
  • weaknesses of independent measures
    • no control of participant variables eg. group A might have an average higher IQ than group B
    • needs more ppts than a repeated measures design
  • how can you reduce participant variables in independent measure design
    randomisation of ppts means that participant variables shouldn't cluster one group
  • Matched Pairs
    ppts who are similar on key variables are paired. One member of the pair is placed in group A and the other in group B.
    This means there are two groups of ppts. Each group is given one level of the independent variable
    -> twins are often the best match, however there's a limited number
  • Strengths of matched pairs
    • controls for participant variables because of the matching
    • avoids order effects
  • weaknesses of matched pairs
    • time consuming to match ppts on key variables
    • may not control all ppt variables because you can only match on variables known to be relevant (there could be other variables that are important)
  • cofounding variables
    where the extraneous variable changes systematically with the IV
  • Situational variables
    a feature of the environment that may affect performance
  • demand characteristics
    cues in a research situation that communicate to the ppts what is expected of them and may unconsciously affect a ppt's behaviour