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Chapter 2: Psychology's Scientific Method

Scientific Method

  • Science is a method, not just what you study; it's how you study it.
  • Scientists propose theories to explain the world. A theory is a system of ideas that attempts to explain observations and make predictions about future observations.
  • Scientific theories are tested and either rejected, supported, or refined using the Scientific Method.

Five-Step Scientific Method (as presented)

  • Step 1: Observe
    • Observe some phenomenon
    • Curiosity & critical thinking
    • Formulate or challenge a theory
  • Step 2: Hypothesize
    • Formulate hypotheses and predictions
    • A testable prediction derived from theory
  • Step 3: Test
    • Test through empirical research
    • Use operational definitions of variables
    • Analyze data using statistical procedures
  • Step 4: Conclusions
    • Draw conclusions
    • Replication of results
    • Reliability
  • Step 5: Evaluate the Theory
    • Evaluate the theory
    • Change the theory if needed
    • Peer review and publication
    • Meta-analysis

Descriptive, Correlational, and Experimental Research

Descriptive Research

  • Goal: Describing a phenomenon
  • Methods: Observation, surveys/interviews, case studies
  • Limitation: Does not answer why things are the way they are; can identify issues nonetheless

Correlational Research

  • Goal: Identify relationships between variables
  • Key statistic: correlation coefficient r with -1 \,\le\, r \,\le\, 1
  • Characteristics:
    • Magnitude indicates strength of the relationship
    • Sign indicates direction (positive or negative)
  • Common values (approximate):
    • 1.00: Perfect
    • .75: Very Strong
    • .50: Moderate
    • .25: Weak
    • 0: None
  • Scatter plots illustrate relationships (positive vs negative correlations)
    • Examples mentioned: longer lecture associated with more yawns; longer lecture associated with lower attentiveness; various combinations of lecture length and attention

Correlation and Causation

  • Important principle: Correlation does not equal causation.
  • Possible explanations for observed correlations:
    • Direct causation (A causes B)
    • Reverse causation (B causes A)
    • Third-variable problem (a third factor causes both A and B)
  • Examples from the material:
    • Parental harshness and child rebellion: multiple plausible explanations; correlation does not settle why behavior occurs
    • Happy mood and sociability: multiple plausible explanations; correlation does not reveal causation
  • Implication: Be cautious about causal inferences from correlational data; seek converging evidence and consider potential confounds
  • Formula example (conceptual):
    • r = \frac{\sum{i=1}^{N} (xi - \bar{x})(yi - \bar{y})}{\sqrt{\sum{i=1}^{N} (xi - \bar{x})^2}\; \sqrt{\sum{i=1}^{N} (y_i - \bar{y})^2}}
    • r ranges from -1 to +1

Experimental Research

Purpose and Key Features

  • Goal: Determine causation
  • Design features:
    • Random assignment to groups
    • Experimental group (receives manipulation)
    • Control group (no manipulation or standard treatment)
    • Independent Variable (IV): the manipulated variable
    • Dependent Variable (DV): the measured outcome
  • How it tests causation: differences between groups on the DV attributable to manipulation of the IV

Experimental Procedure Details

  • Random assignment to groups helps ensure equivalence at start
  • Experimental Group: where the hypothesized cause is manipulated
  • Control Group: treated equally except for the manipulation
  • Observed/Measured Effect: difference between groups on the DV
  • Key variables:
    • Independent Variable (IV)
    • Dependent Variable (DV)

Application Question Practice (Sample from transcript)

  • Scenario: A counseling psychologist tests a self-help book's PTSD-reducing exercises vs ordinary journaling
    • 3a) Independent variable: type of journaling (refunctional writing vs ordinary entries)
    • 3b) Dependent variable: level of PTSD symptoms
    • 3c) Control group: participants writing ordinary journal entries
    • 3d) Experimental group: participants writing refunctional entries

Sampling, Populations, and Settings

Important Concepts in Sampling

  • Population: Entire group about whom conclusions are to be drawn
  • Sample: Portion of the population actually observed
  • Representative Sample: characteristics similar to population
  • Random Sample: Each individual in the population has an equal chance of being selected
  • Biased vs representative samples: Bias compromises external validity

Validity

  • External Validity: Do results generalize to the real world? (Sample size and representativeness matter)
  • Internal Validity: Are changes in the DV due to manipulation of the IV? Are there biases, confounds?

Bias and Expectations

  • Experimenter Bias: Researchers' expectations influence outcomes
  • Research Participant Bias:
    • Demand Characteristics
    • Socially desirable responding
    • Placebo Effect
  • Solution: Double-blind experiment (neither participants nor experimenters know group assignments)

Research Settings

  • Laboratory Setting (Artificial): controlled environment; advantages include control over confounds; disadvantages include low external validity
  • Natural Setting (Real World): naturalistic observation; advantages include real-world relevance; disadvantages include less control over variables

Analyzing and Interpreting Data

Descriptive vs Inferential Statistics

  • Descriptive statistics: summarize data (mean, median, mode; measures of dispersion like range and standard deviation)
  • Inferential statistics: draw conclusions about the population from samples; bridge between sample and population; assess whether data confirm the hypothesis
  • Core concepts:
    • Mean: \bar{x} = \frac{1}{N}\sum{i=1}^{N} xi
    • Median: middle value
    • Mode: most frequent value
    • Range: max − min
    • Standard Deviation (sample): s = \sqrt{\frac{1}{N-1}\sum{i=1}^{N} (xi - \bar{x})^2}
  • Significance testing concept:
    • Alpha level: \alpha = 0.05 (common threshold)
    • Statistical significance: when p < 0.05, the observed pattern is unlikely due to chance

Inference and Evidence

  • Inferential step asks whether data confirm the hypothesis beyond chance
  • Acknowledges that statistical significance does not prove a theory; it supports or challenges it

Ethics and Responsible Research

Research Ethics (APA Guidelines)

  • Informed consent: participants understand the study and agree to participate
  • Confidentiality: protect participants' information
  • Debriefing: explain the study afterward, especially if deception was used
  • Deception: allowed only if justified and followed by debriefing
  • Institutional Review Board (IRB): oversees ethical compliance and risk assessment

Animal Research

  • Benefits to humans; used by about 5% of researchers
  • Species used: rats and mice account for ~90% of animal research
  • Standards of care include housing, feeding, and ensuring psychological and physical well-being

Critical Consumer: Evaluating Psychological Research

  • A Wise Consumer: skeptical yet open-minded
  • Cautions:
    • Avoid overgeneralizing results to individuals
    • Be cautious in applying group trends to individual experience
    • Question causal inferences
    • Look for converging evidence
    • Consider the source

Chapter 2 Objectives (Summary of what you should be able to do)

  • Explain the scientific method
  • Describe the three types of research used in psychology and the settings: Descriptive, Correlational, Experimental; and the conclusions that can be drawn from each
  • Explain research samples and settings
  • Distinguish between descriptive statistics and inferential statistics
  • Explain the need to think critically about psychological research

Key Formulas and Concepts (quick reference)

  • Correlation coefficient: r = \frac{\sum (xi - \bar{x})(yi - \bar{y})}{\sqrt{\sum (xi - \bar{x})^2}\; \sqrt{\sum (yi - \bar{y})^2}}
  • Mean: \bar{x} = \frac{1}{N}\sum{i=1}^{N} xi
  • Standard deviation (sample): s = \sqrt{\frac{1}{N-1}\sum{i=1}^{N} (xi - \bar{x})^2}
  • Population parameter concepts cited: population vs sample; representative and random sampling concepts
  • Significance level: \alpha = 0.05 ; significance criterion: p < 0.05

Additional Notes

  • The lecture-style figures and examples (e.g., longer lectures vs yawns, mood vs sociability) illustrate correlational reasoning and the care needed before claiming causation.
  • The material covers ethical safeguards (informed consent, confidentiality, debriefing, deception, IRB) and practical considerations (external vs internal validity) that affect how studies are designed and interpreted.