research methods

• random sample - a sample in which any member in the target population has an equal chance of being selected
• opportunity sampling - a sample is chosen from a population that is available at the time of the study
• volunteer sampling - when ps sign themselves up to be part of the research by responding to a flyer
• snowball sampling - a few potential ps are contacted and asked if they know of any others with the same desired set of characteristics
• strengths of random sampling

  • avoids researcher bias
  • most accurate representation of the target population
• weaknesses of random sampling

  • time consuming which may be harder to gather funding for
  • not always appropriate or practical
• strengths of opportunity sampling

  • cheap which is useful for getting funding for research
  • depending on the location chosen likely to be representative
• weaknesses of opportunity sampling

  • researcher bias
  • response bias
• weaknesses of volunteer sampling

  • response bias
  • likely to not access the full target population
• strengths of snowball sampling

  • easy way to reach desired ps
  • useful for when researching rare characteristics
• weaknesses of snowball sampling

  • sampling bias
  • issues with ethics and anonymity
• respect

  • informed consent
  • right to withdraw
  • confidentiality
• integrity

  • free from deception
• competence - ethical consideration but not any guidelines
• responsibility

  • protection from harm
  • debrief
• independent variable - the variable that is manipulated by the researcher to see how it affects the dependent variable
• dependent variable - the variable that is measured in an experiment
• extraneous variables - variables that are not directly related to the independent variable but may affect the dependent variable
• alternative/experimental hypothesis - there will be a significant difference of the effect of the iv on the dv
• null hypothesis - the iv will have no significant effect on the dv
• one tailed hypothesis - a hypothesis that predicts a single outcome in one direction
• two tailed hypothesis - the hypothesis predicts that there could be two outcomes
• repeated measures design - participants are tested on the same task in different conditions
• counterbalancing - to eliminate order-effects researchers can alter the order that ps complete tasks in during repeated measures design, if using this in an essay must mention counterbalancing
• strengths of repeated measures design

  • difference between ivs unlikely to affect dv
  • counterbalancing reduces order effects
  • needs fewer ps, useful when researching rare ps
• weaknesses of repeated measures design

  • higher chance of demand characteristics
  • order effects are still present
  • study takes ling which means ps may get bored leading to sample attrition
• independent measures design - participants are randomly assigned to one of two conditions, one of which is the experimental condition
• strengths of independent measures design

  • lower demand characteristics
  • can't get order effects as ps only complete one condition
• weaknesses of independent measures design

  • differences in ps will distort the iv
  • requires more ps which is more expensive which reduces the chance of research funding
• matched pairs design - two participants are matched on a variable of interest and then tested on the same variable
• strengths of matched pairs

  • control for extraneous variables
  • removed order effect
• weaknesses of matched pairs

  • cannot control for every characteristic to be the same so some extraneous variables still present
• field experiments - where behaviour is measured in the setting where it would naturally occur
• quasi experiment - where the iv naturally occurring and cannot be manipulated
• inductive reasoning - reasoning from the particular to the general
• principles of science

  • control
  • falsification
  • objectivity
  • quantifiable measures
  • replicability
  • standardisation
• correlation - investigate whether two co-varibles are related and how strongly so
• positive correlation - high values of one variable are associated with high values of the other
• negative correlation - high values of one variable are associated with low variables of the other
• correlational hypothesis - there will be a significant positive/negative correlation between variables, don't mention difference