🧠

Psychology Research & Data Interpretation

Sep 21, 2025

View transcript

Overview

This lecture reviewed psychological research methods and data interpretation, covering key experimental designs, statistical concepts, and ethical guidelines crucial for exam success in AP Psychology.

Test Format & Unit Importance

  • The test includes 75 multiple-choice questions (90 min) and 2 free-response questions (AAQ, EBQ; 17 min).
  • Unit covers about 56% of the exam: research methods, design, and data interpretation are heavily weighted.
  • Multiple-choice tests concept application, research methods, and data interpretation.

Psychological Approaches

  • Psychodynamic: Behavior explained by unconscious mind, early experiences.
  • Behavioral: Observable behavior shaped by environment (classical/operant conditioning).
  • Cognitive: How mental processes like thoughts and perceptions impact behavior.
  • Humanistic: People strive for self-actualization, supported by unconditional positive regard.
  • Biological: Examines genetics, neurochemistry, brain structures.
  • Evolutionary: Behaviors shaped by traits aiding survival/reproduction.
  • Sociocultural: Social norms and culture influence behavior.
  • Biopsychosocial: Integrates biological, psychological, and sociocultural factors.

Research Methods & Sampling

  • Population: Whole group the study targets; sample: subset actually studied.
  • Random sampling: Each person has equal chance to be chosen—allows generalization.
  • Convenience sample: Using easily accessed participants; risks sampling bias, limits generalizability.
  • Random assignment: Randomly places participants in experimental or control groups to control confounds.

Non-Experimental & Experimental Methods

  • Case study: In-depth on one/few individuals (e.g., patient HM).
  • Naturalistic observation: Observe behavior in natural settings, no interference.
  • Correlational study: Examines relationship between variables; correlation ≠ causation.
    • Third variable problem: Unmeasured variable may explain correlation.
    • Directionality problem: Unsure which variable causes the other.
  • Meta-analysis: Combine results from multiple studies.
  • Cross-sectional: Compare different groups at one point in time.
  • Longitudinal: Study same group over many years.
  • Experiment: Manipulates independent variable (IV) to see effect on dependent variable (DV); only method for cause-effect.

Key Experimental Concepts

  • Reliability: Study can be replicated for consistent results.
  • Operational definition: Specific descriptions of variables and procedures.
  • Validity: Study measures what it intends to measure.
  • Confounding variables: Uncontrolled factors that may affect DV.
  • Control group: Does not receive treatment; often given placebo.
  • Single-blind: Participants unaware of group; reduces subject bias.
  • Double-blind: Both participants and researchers unaware; reduces experimenter bias.
  • Placebo effect: Improvement due to expectations, not treatment.

Survey & Data Collection

  • Survey: Collects self-reported attitudes/behaviors; not a research method, but a technique.
  • Likert scale: Survey scale (e.g., never to always).
  • Self-report/social desirability bias: Respondents may answer inaccurately to look good.

Data Interpretation & Statistics

  • Quantitative data: Numbers; qualitative: words/experiences.
  • Measures of central tendency: Mean (average), median (middle), mode (most frequent).
  • Range: Difference between largest and smallest.
  • Normal distribution: Bell curve with most data near mean.
  • Skewed distribution: Data pulled left (negative) or right (positive) by outliers; median preferred measure.
  • Standard deviation: How spread out data is from mean.
  • Z-scores: Express score's distance from mean in SD units.
  • Empirical rule: 68% (±1 SD), 95% (±2 SD), 99.7% (±3 SD) in normal dist.
  • Percentile rank: % of scores at or below a value.

Inferential Statistics & Effect Size

  • Statistical significance (p < 0.05): Results unlikely due to chance.
  • Effect size: Magnitude of difference between groups; large = strong impact; small = weak impact.
  • Descriptive stats: Summarize data; inferential stats: Generalize findings to population.

Ethics in Research

  • Institutional Review Board (IRB): Approves studies for ethics.
  • Informed consent: Participants agree to study; assent for minors.
  • Protection from harm: No lasting physical/psychological harm.
  • Confidentiality/anonymity: Identities kept private.
  • Deception: Allowed if debriefed later.
  • Confederates: Actors used to influence participant behavior.

Cognitive Biases

  • Confirmation bias: Seek info that supports beliefs.
  • Hindsight bias: "Knew it all along" after outcome is known.
  • Overconfidence: Overestimate accuracy of one's knowledge or abilities.

Key Terms & Definitions

  • Population — entire group targeted by a study.
  • Sample — subset of population studied.
  • Random sampling — every member has equal selection chance.
  • Random assignment — randomly placing participants in groups.
  • Independent variable (IV) — variable manipulated in experiment.
  • Dependent variable (DV) — outcome measured in experiment.
  • Operational definition — clear, specific description of a variable.
  • Reliability — consistency of results.
  • Validity — accuracy in measuring intended variable.
  • Confounding variable — external factor affecting results.
  • Placebo effect — improvement from expectation, not treatment.
  • Statistical significance — results unlikely due to chance (p < 0.05).
  • Effect size — degree of difference between groups.

Action Items / Next Steps

  • Review and memorize key statistical concepts (mean, median, mode, SD, z-score, effect size).
  • Practice identifying research methods in sample scenarios.
  • Prepare for FRQ practice and review ethical guidelines.
  • Read over any FRQ questions provided before the next live review session.

Full transcript