Notes on Scientific Reasoning and Research Methods in Psychology

Science, superstition, and scientific reasoning

  • The core question: How can we reach reliable knowledge about the world? By distinguishing superstition from scientific understanding through testing and evidence.
  • Example contrast: Superstitions in sports and politics (e.g., athletes like Djokovic bouncing the ball before serves; leaders using charms or spiritual leaders) are discussed as patterns people observe, but they are not scientifically validated explanations.
  • Spirituality and culture nuance: Spiritual beliefs can be separate from Christian religious frameworks; cultures (e.g., Korea) have long histories and varied beliefs about spirituality, authority, and ritual. The speaker notes that belief does not equal scientific truth.
  • Key takeaway about belief: Strong assertions or charisma alone are not sufficient to establish truth; claims must be tested scientifically.
  • Experiential claims: Personal experience can feel convincing, but individual experience is not automatically generalizable to others or to broader phenomena.
  • Humility in science: Acknowledge that one’s own experiences may be limited or non-generalizable; be open to testing and revision.
  • Big picture: Scientific knowledge comes from approach-based research, not just anecdote or authority; it aims to uncover unknowns and clarify uncertain information.

What is science? Definition and core features

  • Science is described as:
    • A body of knowledge or truth about the world, organized systematically, that reveals general norms.
    • A discipline or branch of knowledge with common, recurring characteristics.
  • The single most important common feature across definitions: systematic approach.
  • Systematic observation as a foundation of science:
    • Observation should be planned, repeatable, and rule-governed, not casual.
    • It involves data collection and using methods that can be scrutinized and replicated.
  • Practical implication: To gain knowledge, one must use a systematic method rather than relying on random observations or anecdotes.

Systematic observation and data collection

  • Systematic observation is the keyword for being scientific; it involves a deliberate, organized approach.
  • Observation can be broadly defined as data collection, not just watching people:
    • Methods include surveys, interviews, and other data-gathering techniques.
  • Narrow vs broad observation:
    • Narrowly defined observation: naturalistic or lab-based observation of specific behaviors in controlled contexts.
    • Broad data collection: includes various forms of data gathering beyond simple watching.

Attachment theory example: Naturalistic vs lab observation

  • Attachment theory studies use different observation styles:
    • Naturalistic observation in daily settings (watching children and caregivers in real contexts).
    • Lab-based observation in controlled settings.
  • Classic attachment study setup described:
    • Toddlers and their caregivers are observed in a room with toys and books.
    • The “Strange Situation” involves leaving the caregiver and observing toddler reactions upon return.
    • This setup is typically done with researchers unseen, e.g., behind a mirror, to avoid influencing behavior.
  • Takeaway: Both naturalistic and lab observations are valuable; they are specific, controlled ways to gather data about behavior and attachment.

Data collection and the preparation for data collection

  • This semester focuses on preparing for data collection; the next semester will involve actual data collection.
  • Data collection underpins systematic observation and subsequent analysis; without good data collection, conclusions are weak.

Experiments: design, manipulation, and comparison

  • An experiment is a type of study that involves manipulation of the independent variable (IV) and observation of its effect on the dependent variable (DV).
  • Key components:
    • Independent variable (IV): the factor deliberately changed or manipulated.
    • Dependent variable (DV): the outcome measured.
    • Experimental group: participants exposed to the IV.
    • Control group: participants not exposed to the IV or exposed to a baseline condition.
  • Purpose: to determine whether the IV causes changes in the DV, under controlled conditions.
  • Note on terminology: the term “experiment” can refer broadly to any experimental approach or a more specific, tightly controlled set of procedures.

Memory, perception, and false memory

  • Cognitive psychology recognizes that memory is fallible and can be influenced by context and framing.
  • Example discussed: memory for events like a car crash can be affected by additional wording or associations, leading to false memories when combined with suggestive cues.
  • Important implication: data gathered from memory reports must be interpreted with caution, and multiple sources or controlled conditions are necessary to draw reliable conclusions.

Reproducibility, replication, and the nature of evidence

  • Reproducibility is a core requirement in psychology:
    • Findings should be replicated by independent researchers to establish reliability.
    • If results cannot be reproduced, the original finding is undermined, and the claim loses credibility.
  • The role of replication: without replication, surprising or peculiar findings risk being discarded or forgotten.
  • What science can and cannot do:
    • In psychology (and science in general), we do not claim absolute proof or disproof of hypotheses.
    • Scientific conclusions are probabilistic, supported by evidence, and open to revision with new data.
  • Conceptual stance: even when a hypothesis is supported, scientists phrase conclusions in terms like “supported by evidence” rather than “proved.”

Case study: Milgram obedience study and interpretation of percentages

  • Milgram’s classic obedience study examined how far people would go in delivering electric shocks to another person under authority instructions.
  • Reported figures discussed:
    • Approximately 0.65 (or 65\%) of participants delivered the maximum shock level (450 volts).
    • Approximately 0.35 (or 35\%) stopped short of the maximum (i.e., did not comply fully).
  • Critical interpretation:
    • The key takeaway is that a majority complied with the harmful instruction, but a substantial minority did not.
    • The question arises: where are the individuals who refused, and why did they refuse? What does this say about situational vs. dispositional factors?
  • Important epistemological point: such percentages support a probabilistic conclusion (e.g., “people do follow unacceptable orders sometimes”), not an absolute universal law about human nature.

Epistemology and the limits of scientific claims

  • The talk emphasizes that science does not offer universal laws with no exceptions (e.g., gravity is a law with no exceptions is a different kind of claim than behavior under social pressure).
  • In psychology, laws are often probabilistic and contingent on context, samples, and experimental design.
  • The emphasis is on what the data show, how robust the findings are, and how they generalize (or fail to generalize) across settings.

Ethical, philosophical, and practical implications

  • Ethical consideration: experiments involving deception, harm, or distress (e.g., Milgram) require careful ethical scrutiny and justifications.
  • Philosophical implications: the difference between belief, experience, and evidence; how to avoid conflating powerful anecdotes or charismatic leadership with scientific truth.
  • Practical implications: researchers must test claims, seek replication, and communicate uncertainty clearly to avoid overgeneralization.

Connections to broader principles and practical takeaways

  • Systematic observation is essential for reliable knowledge; data collection methods must be explicit and replicable.
  • Distinguish between broad, exploratory observations and narrowly defined, controlled measurements.
  • When evaluating claims, prioritize evidence from controlled studies, replication, and awareness of biases (e.g., memory distortion).
  • Remember that science builds probabilistic knowledge; conclusions are updated as new data emerge, not absolute truths.
  • In everyday discourse, separate strong assertions and confidence from scientific credibility; use humility and critical testing to advance understanding.

Key formulas and numerical references (LaTeX)

  • Milgram’s maximum shock level and compliance:
    • Maximum voltage: 450\,\text{V}
    • Percentage complying to maximum: 65\% = 0.65
    • Percentage not reaching maximum: 35\% = 0.35
  • General principle: probability-based conclusions rather than absolute proofs; express support as a fraction or percent, e.g.,
    • Support for a hypothesis: p = \text{(number of supportive results)} / \text{(total trials)} (conceptual)
  • Notation for variables used in experiments:
    • Independent variable: IV
    • Dependent variable: DV

Summary of takeaways

  • Science aims to move beyond anecdote and superstition through systematic observation, data collection, and controlled experimentation.
  • Both broad data gathering and narrowly defined observations have roles in psychological research.
  • Replication and cautious interpretation are essential; science rarely offers absolute proofs.
  • Psychological findings (e.g., obedience) are probabilistic and sensitive to context; ethical considerations are important when designing studies.
  • Personal experience and charisma are not substitutes for evidence; humility and critical testing are central to scientific progress.