Research methods

• Empirical method


  The only source of knowledge comes through our senses (not inherited) and is gained through experience
• Objective


  All sources of bias are minimized and personal or subjective ideas are eliminated
• Control


  All extraneous variables need to be controlled in order to be able to establish cause and effect
• Predictability/determinism


  We should be aiming to be able to predict future behaviour from the findings of our research
• Features of science


  Empirical methods

  Objectivity

  Replicability

  Hypothesis testing/ theory
• Scientific research methods


  Lab experiment, field experiment, observation, natural experiment and quasi-experiment
• Non-scientific research methods


  Case study, questionnaire, interviews, content analysis and correlations
• Aim


  general statement of the purpose of an investigation
• Hypothesis


  testable statement about the expected outcome of the investigation
• Operationalisation


  Making the variables testable
• importance of operationalisation


  a hypothesis can only be tested if the variables being studied can be measured
• Independent variable


  the variable the researcher changes in order to test its effect on the DV
• Dependent variable


  the variable measured by the experimenter
• Null hypothesis


  A statement which predicts no difference or relationship in the results
• Experimental/alternative hypothesis


  A statement that predicts a difference or a relationship in results
• Directional hypothesis (one-tailed)


  Specifies the direction of results/correlation
• Non-directional hypothesis


  Does not state the direction of results and is used when there is no previous research or previous research has found contradictory results
• Repeated measures design


  same pps. used in both conditions of IV

  
• Strength of repeated measures design

  No participant variablesas individual differences are eliminated and less pps. needed

  
• Weakness of repeated measures design (d.c.)

  demand characteristics due to pps. take part in all conditions

  
• Weakness of repeated measures design (o.e.)


  order effectse.g. boredom may occur (control using counterbalancing)

  
• Independent groups design


  Participants randomly allocated to 2 different groups
• Strength of independent groups design


  Lower chance of demand characteristics, no order effects due to only doing one condition
• Weakness of independent groups design

  Participant variables confound results cos there's different participants in different conditions, more pps. are required

  
• Matched pairs design


  pairs of pps. closely matched and randomly allocated to one condition/other

  
• Strength of matched pairs


  avoids order effects and demand characteristics, reduced individual differences, same material can be used in both conditions

  
• Weakness of matched pairs

  Can't fully match participants, time consuming and requires more pps.

  
• Extraneous variable


  a variable other than the IV that might have an effect on the DV (e.g. weather or noise) - should be controlled so they don't become confounding

  
• Confounding variable


  extraneous variables which do affect the DV i.e. 'confound' the results e.g. participants personalities

  
• Situational variable


  Aspects of the situation that interact with aspects of the person to produce behaviour (e.g environment, noise or time of day)

  
• Operationalism


  defining the variable so it can be measured numerically and specifies how variable will be tested
• Participant variable


  Individual differences between the pps. in the conditions of the IV

  
• Counterbalancing


  Used to balance out impact of order effects in repeated measures design (involves making sure each condition comes first/second in equal amounts) i.e. allows for order effects to be distributed evenly across both conditions

  
• Random allocation


  Allocating pps. to experimental groups/conditions so pps. have an equal chance to take part in each condition (allows even distribution of pp. characteristics across conditions to avoid extraneous variables)

  
• use of random allocation

  addresses problem of pp. variables in an independent groups design
• Standardisation


  Using exactly the same formalised procedures and instructions for all participants so individual experience does not become a confounding variable and i.e. enable replication

  
• use of standardisation


  addresses issue of experimenter bias as standardised procedures includes standardised instructions that are the same for all pps. i.e. deals with investigator effects
• Randomisation


  Making materials/order of conditions random to avoid researcher bias influencing design of the study
• use of randomisation


  avoidsresearcher biasinfluencing thedesignof the study i.e.control investigator effects
• pilot study


  small scale trial run of a study which takes place before the study