PSYC 381 - Research Methods - Chapter 1: Scientific Method

PSYC 381 - Research Methods - Chapter 1: Scientific Method

Source Attribution

  • Source: Adapted from Nestor, Research Methods in Psychology, 3e. O SAGE Publications 2019.

Philosophical Basis for Knowledge

  • Definition: Exploration of different ways of knowing about the world.
  • Common Epistemological Forms:
    • Experience
    • Observation
    • Intuition
    • Faith
    • Authority
    • Tradition
    • Reason
    • Science

Limitations of Epistemological Pursuits

  • Understanding: No epistemological form is perfect; all can lead us astray.
  • Common Errors:
    • Experience: Cognitive biases; Overgeneralization
    • Intuition: Ego-based commitments; faulty heuristics
    • Authority: Rigid adherence to established opinions
    • Reason: Illogical reasoning
    • Observation: Inaccurate observation; confirmation bias
    • Faith: Ideological rigidness
    • Tradition: Excessive devotion
    • Science: Pseudoscience

Pseudoscience

  • Definition: Practices and results that sound scientific but do not adhere to genuine scientific methodologies.
  • Appeal:
    • Often based in personal experience
    • Appeals to sense of rightness/truth
    • Requires minimal or anecdotal evidence
    • Confirms pre-existing beliefs rather than refuting them

Detecting Pseudoscience

  • Challenges: Pseudoscience is hard to detect due to several facets.
  • Common Warning Signs:
    • Tendency for “loopholes” limiting falsification of claims
    • Lack of self-correction
    • Emphasis on confirming evidence over falsification
    • Places burden of proof on skeptics rather than proponents
    • Heavy reliance on testimonials as evidence
    • Evades peer-review processes
    • Lacks connectivity with established scientific thought
    • Overuse of complex jargon
    • Does not specify boundary conditions

Doctrine of Falsification

  • Key Points:
    • Scientists must aim to disprove their hypotheses.
    • Science is characterized by self-correction.
    • Theories should undergo rigorous testing.
    • Empirical analysis of data is mandatory.
    • Methodologies must be systematic.
    • Tangible evidence is essential.

Foundations of Research

  • Importance: The rules guiding methodological research practices.
  • Systemization of methods: Critical for scientific inquiry.
  • Origins of Methodology:
    • Natural philosophy
    • Empiricism
    • Experimentation

Formulating Research Questions

  • Definition: Questions answerable through empirical data; considered scientific questions.
  • Contrast with Non-Scientific Questions:
    • Example: Difference between "is" and "ought" questions.
  • Quantitative vs. Qualitative Methods:
    • Research questions based on theory favor quantitative methods.
    • Research questions arising spontaneously prefer qualitative methods.

Research Terminology

  • Theory: A logically interrelated set of propositions describing empirical reality.
  • Data: Empirical evidence reflecting real-world phenomena.
  • Hypothesis: A testable, predictive statement discussing the relationship between variables.
    • Must be testable.
    • A priori (before data collection) vs. post hoc (after data collection).
  • Variables:
    • Definition: Attributes or properties that can take different values.
    • Types:
    • Independent Variables
    • Dependent Variables
    • Confounding Variables
    • Control Variables

Understanding Variables

  • Definitions:
    • Variable: Any observation that can assume various values.
    • Attribute: A specific value of a variable.

Examples of Variables

  • Example 1:
    • Variable: Biological Sex
    • Attributes: Female; Male
  • Example 2:
    • Variable: Level of Agreement
    • Attributes: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree

Types of Variables

  • Independent Variables: Factors assumed to influence other variables.
  • Dependent Variables: Factors assumed to change due to independent variables.
  • Confounding Variables: Other variables that may interfere with the relationship between independent and dependent variables.

Mapping Variables Relationships

  • Types of Relationships:
    • No Relationship: Example with GPA
    • Positive Relationship: Example: Salary Expectation vs Years in School
    • Negative Relationship: Example: Paranoia vs Self-Esteem
    • Curvilinear Relationship: Example: Severity of Illness vs Dosage Level

Understanding Population and Sample in Research

  • Population: The complete set of elements assessing a research question.
  • Sample: A subset of the population selected for investigation.
  • Representative Samples: Critical for the generalizability of results.
    • Different types of samples: Random sample vs. other types.
    • Sample Bias: A consideration in sampling methodology.

Validity and Reliability in Research

  • Validity:
    • The ultimate goal of research.
    • Achieved when conclusions about empirical reality are accurate.
    • Example: Correctly identifying weather conditions (e.g., stating that the weather is warm when the thermometer shows 85 degrees).
  • Reliability:
    • Refers to the consistency of a measure.
    • A necessary condition for validity.

The Goal of Measurement

  • Understanding: Validity and reliability are intertwined. Measurements must be reliable to be valid.
  • Reliability Without Validity: Possible to have reliable data without accuracy.
  • Requirement for Validity: For a measure to be valid, it must always be reliable.