Experiments

• 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