Research Methods

• • Independent variable manipulated outside lab
  • Dependent variable measured quantitatively
  • Strengths:
  • Higher ecological validity
  • Less demand characteristics
  • Limitations:
  • Harder to control extraneous variables
  • High mundane realism
  • Natural Experiments:
  • Researcher does not manipulate independent variable
  • Independent variable changes naturally
  • Variables affecting dependent variable not controlled
  • Strengths:
  • Allows research in areas controlled experiments cannot
  • High external validity
  • Limitations:
• Experimental Method:

  • Laboratory Experiments:
  • Researcher has high control over all variables
  • Control environmental factors like noise and temperature
  • Standardised procedure for control
  • Independent variable changes between conditions
  • Allows clear measurement of dependent variable
  • Strengths:
  • Cause and effect conclusions more possible
  • High internal validity
  • Research is replicable
  • Limitations:
  • Demand characteristics may affect validity
  • Lack of ecological validity
  • Field Experiments:
  • Conducted in naturalistic settings
• • Difficult to establish cause and effect
  • Lack of reliability
• Observational Techniques:

  • Covert Observation:
  • Participants observed without knowledge
  • Observing natural behavior
  • Overt Observation:
  • Participants aware of being observed
  • Behavior observed and recorded
  • Participant Observation:
  • Researcher joins group being observed
  • Builds rapport with participants
  • Non-participant Observation:
  • Researcher remains separate from participants
  • More objective observation
• Self-report Techniques:

  • Questionnaires:
  • Open questions for qualitative data
  • Closed questions for quantitative data
  • Structured Interviews:
  • Prepared list of questions
  • Easy comparison of answers
  • Unstructured Interviews:
  • Topic-based conversation
  • Allows for specific questions and more information
  • Semi-Structured Interviews:
  • Combination of set questions and extra questions
  • Allows for more information gathering
• Correlations analyze the relationship between co-variables without manipulating them
• Variables are measured and compared to look for a relationship
• Variables can be pre-existing, like school attendance and number of GCSEs achieved
• Scattergraphs show outcomes of correlations: positive, negative, or zero
• Correlation coefficient represents the direction and strength of the relationship between variables, ranging from -1 to +1
• Strength of correlations can be weak, moderate, or strong
• Strengths of Correlational Analysis:
• Show relationships between variables
• Allow predictions to be made
• Limitations of Correlational Analysis:
• Do not show causation
• May be affected by extraneous relationships with other variables
• Difference between correlations & experiments:
• Experiments involve deliberate manipulation of variables to establish cause and effect
• Correlations do not manipulate variables and cannot establish cause and effect
• Content Analysis:
• Method to analyze qualitative data by turning it into quantitative data
• Involves coding qualitative data to transform it into quantitative data
• Reliability can be tested through test-retest and inter-rater reliability
• Strengths of Content Analysis:
• Reliability is established as it is easily replicable
• Allows statistical analysis to be conducted
• Limitations of Content Analysis:
• Researcher bias can occur
• May lack validity due to extraneous variables
• Thematic Analysis:
• Method to analyze qualitative data by identifying common themes
• Themes emerge from the data without hypothesis-testing
• Strengths of Thematic Analysis:
• Provides flexibility in approaching the data
• Allows researchers to explore data without preconceptions
• Limitations of Thematic Analysis:
• May lack validity as data is not collected under controlled conditions
• Case Studies:
• Detailed investigations of a small group or individual