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The Personality Triad

  • Emotions

  • Thoughts

  • Behaviours

What is Personality?

  • Personality is an individual's characteristic patterns of thought, emotion, and behaviour, coupled with the psychological mechanisms behind those patterns.

  • Key components:

    • Characteristic patterns: consistent ways a person thinks, feels, and acts across time and situations.

    • Psychological mechanisms: internal processes that generate and regulate those patterns.

Major Approaches to Personality

  • Trait approach: How are people different from each other?

  • Biological approach: How do anatomy and genetics affect personality?

  • Psychoanalytic approach: What goes on in the unconscious parts of the mind?

  • Phenomenological approach: What is the nature of human experience?

  • Learning and cognitive approaches: What are the psychological processes that underlie personality?

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Why Personality Psychology Is Unique

  • Focus on individual differences rather than treating people as generally the same.

  • Emphasizes that people vary on many dimensions and that those differences have relevance for behavior and experience.

Personality Data & Assessment

  • Psychology is not a hard science; there are no perfect indicators of personality—only clues, which are inherently ambiguous.

  • Quote to remember: "There are no perfect indicators of personality: there are only clues, and clues are always ambiguous." — David Funder

Four Kinds of Clues (Personality Data)

  • Self-Report Data (S-R Data)

  • Informant-Report Data (I-R Data)

  • Life Data (L-D Data)

  • Behavioural Data (B-D Data)

Self-Report Data

  • Definition: data obtained by asking the person directly (e.g., Likert-style items, true/false).

  • Advantages:

    • Large amounts of information

    • Access to thoughts, feelings, intentions

    • Some self-reports are true by definition (e.g., self-esteem)

    • Causal force (participants’ reports can influence how they are treated)

    • Simple and easy to collect

  • Disadvantages:

    • Bias (social desirability, faking)

    • Error (random or systematic)

    • Sometimes too simple or easy, leading to superficial answers

  • Key takeaway: Self-reports are valuable for internal states but must be interpreted with caution due to biases and limits on self-knowledge.

Informant-Report Data

  • Definition: information provided by someone who knows the target well (family, friends, coworkers).

  • Advantages:

    • More information from outside the target (beyond self-views)

    • Real-world bias can be informative

    • Contextual and definitional truth can emerge from others’ observations

    • Potential causal influence if informants’ perceptions affect the target

  • Disadvantages:

    • Limited view of private experiences

    • Susceptible to personal biases and errors

Life Data

  • Definition: data derived from the residue of personality in real-life records (school records, bank statements, medical files).

  • Advantages:

    • Objective and verifiable

    • Intrinsically important and psychologically relevant

  • Disadvantages:

    • Multidetermination: many factors influence life outcomes, making causal inferences harder

Behavioural Data

  • Definition: direct observations of behavior across contexts (e.g., daily diary, Electronically Activated Recorder (EAR), physiological measures).

  • Advantages:

    • Range of contexts observed

    • Appearance of objectivity

  • Disadvantages:

    • Can be difficult and expensive to collect

    • Interpretation can be uncertain and context-dependent

Personality Assessment

What does a personality test look like?

  • Construct: a label used for a set of behaviors or features (e.g., "Anxiety" refers to nervousness, low tolerance for uncertainty, overthinking, etc.).

  • Items: the questions or prompts used on a survey; many are statements that participants endorse (agree with) rather than direct questions.

Good measures are…

  • Reliability

    • Data are consistent across time and/or contexts

    • Reliability depends on whether the trait is stable (trait) or fluctuates (state)

    • Use attention checks to ensure participant engagement

    • Reliability is independent of validity

  • Validity

    • Construct validity: the degree to which a measure actually assesses the intended construct

    • Validity is not guaranteed by reliability alone; a measure must be both reliable and valid to be useful

  • Generalizability

    • Do results apply to other kinds of people beyond the assessed sample?

    • Most psychology research is conducted on WEIRD populations (Western, Educated, Industrialized, Rich, Democratic)

    • Good measures should strive for broader applicability

Case Method

  • Advantages:

    • Describes a whole phenomenon

    • Can lead to large-scale insights

    • Sometimes the only viable option

  • Disadvantages:

    • Generalizations may be unknown

Research Designs

Experimental Method

  • Goal: establish causation

  • Independent Variable (IV): the influential variable that you manipulate

  • Dependent Variable (DV): the outcome that changes as a result of the IV

  • Example: Misattribution of Arousal

    • IV: Fear

    • DV: Attraction to confederate

  • Advantages:

    • Direct manipulation of variables of interest

  • Disadvantages:

    • Demand characteristics

    • Manipulation errors

    • Low generalizability to real-world settings

Correlational Method

  • Goal: determine the relationship between variables

  • Example dataset: Neuroticism and marital disputes

    • Variables: Neuroticism score (X), Conflicts initiated per week (Y)

    • Observed pattern: higher X tends to be associated with more Y

  • Data representation:

    • Scatterplot shows relationship between X and Y

    • Correlation coefficient r quantifies strength and direction

  • Important concept: Third-variable problem

    • A separate variable may cause the observed relationship between X and Y

Correlation Coefficients and Confidence

  • Example: If the correlation between neuroticism and marital conflict is r = 0.34

    • Interpretation: higher neuroticism tends to be associated with more marital conflict

  • Confidence Interval:

    • A CI provides a range where the true population value likely lies

    • Common confidence level: 95\%

    • Example: r = 0.34\quad (95\% CI = [0.17, 0.42])

Interpreting Correlations

  • Psychology often deals with small relationships because many factors influence behavior.

  • Rule of thumb for effect sizes (in terms of absolute value of r):

    • Small: |r| \approx 0.10

    • Medium: |r| \approx 0.20

    • Large: |r| \approx 0.30

  • Note: Small effects can still be meaningful when accumulated over time or across many behaviors.

Null Hypothesis Significance Testing (NHST)

  • Purpose: to determine whether an observed effect is unlikely under the null hypothesis

  • The p-value: the probability of obtaining data as extreme as observed if the null hypothesis is true

  • Common misinterpretations:

    • The p-value is not the probability that the null hypothesis is true

    • It is not a measure of effect size

    • It does not directly indicate the probability of making a Type I error; it relates to the data under the null

  • Types of errors:

    • Type I error: incorrectly concluding there is an effect when there is none

    • Type II error: failing to detect an effect when one exists

p-values and Hypothesis Testing

  • A p-value below a threshold (e.g., 0.05) leads to rejecting the null hypothesis, but this does not prove the effect or its importance

Replication and Reproducibility

  • Replication: the study is conducted again to see if findings hold

    • Conceptual replication: tests same hypothesis with different methods

    • Direct replication: repeats the exact original study

  • Replication crisis in psychology (2010s): many famous findings did not replicate

  • Contributing factors:

    • Questionable Research Practices (QRPs)

    • Small sample sizes

    • One-and-done mentality (lack of replication emphasis)

  • Remedies and improving rigor:

    • Open science practices

    • Preregistration of methods and analyses

    • Data sharing and transparency

Notation and Formulas Summary

  • Correlation coefficient: r measures strength and direction of a linear relationship

    • Example: r = 0.34 indicates a positive, modest relation

  • Confidence interval for a correlation: 95\%\ CI = [L, U], e.g., [0.17, 0.42]

  • Effect size guidelines (in terms of absolute value of r):

    • Small: |r| \approx 0.10

    • Medium: |r| \approx 0.20

    • Large: |r| \approx 0.30

Practical and Ethical Implications

  • Data quality and interpretation depend on the type of data used and the context

  • Generalizability concerns emphasize the need for diverse samples beyond WEIRD populations

  • The replication crisis underscores the ethical obligation to report methods transparently and to verify results through replication

  • Use of multiple data sources (triangulation) can strengthen inferences but also requires careful integration

Key Takeaways for Exam Preparation

  • Understand the four kinds of clues and what each can and cannot reveal about personality

  • Be able to distinguish reliability and validity and explain why both are needed

  • Know the difference between experimental and correlational designs, and the associated strengths and limitations

  • Be familiar with NHST concepts, common misinterpretations of p-values, and the role of replication in science

  • Recognize WEIRD bias and the importance of generalizability in psychological research

  • Be comfortable interpreting a correlation coefficient and a confidence interval in context

  • Appreciate the ethical dimension of behavioral science research, including preregistration and data sharing