Psychology 201 Lecture Notes Review
Psychology Class Notes
September 8th: Transfer Appropriate Processing
John Bransford
Concept of past representing the present
Importance of forming similar brain patterns now as in the past
Why practice tests are the best way to study:
Engage in retrieval practices which reinforce learning.
Levels of Processing (LOP) - Fergus Craik
Deeper processing of information leads to better performance on tests.
Rationale for Testing Students:
Assessment of student performance in the course.
Encouragement for students to attempt learning content.
Function not merely as assessment tools but also as highly effective learning tools.
Improve learning efficiency higher than traditional studying techniques.
Concept of Desirable Difficulties:
Engaging in study methods that appear challenging enhances retention.
Overview of Chapter 1:
Broad, abstract ideas presented; reliant on prior scientific findings.
Clarification: New science frequently builds upon existing research.
Research outcomes may often lead to ambiguous conclusions.
Merton’s Norms
Sociologist Robert Merton proposed four guiding norms for science:
Universalisms:
Scientific claims assessed according to predetermined criteria to ensure objectivity among all observers.
Communalisms:
Scientific knowledge is attributed collectively, not to individual scientists.
Disinterestedness:
The main objective of science is to advance understanding, steering clear of personal gains.
Organized Skepticism:
Scientists are committed to rigorously testing claims and considering how those claims could be challenged.
Importance of understanding these norms and their rationale.
Theory-Data Cycle
Concept described as somewhat idealized; the real scholarly process occurs in cultural contexts and is affected by numerous external factors.
Implications of research data: Results can bolster or contradict existing theories; however, findings may frequently yield ambiguous results.
Subjective Experience and Its Implications
Personal judgments and decisions influenced by subjective experiences:
It's situational; aesthetic questions can liberate subjective feelings.
Example: Evaluate attractiveness of individuals like Jacob Elordi versus Timothee Chalamet.
For questions that have concrete answers, relying solely on subjective experiences could lead to errors.
Example of maternal mortality:
Higher rates during physician-assisted childbirth pose questions about physician training and awareness of female anatomy in contrast with midwifery.
Joseph Lister's work on antiseptic surgery established the efficacy of infection control.
Control Groups and Personal Experience Limitations
Personal experiences may lack the rigor of control groups essential for valid comparisons.
Subject-to-subject comparisons can introduce confounding variables.
Retrospective nature of personal experience:
Individual memory of past events can be flawed or distorted, leading to uncertainty when relying on other's recollections.
The overlap between intuition and personal experience can lead to erroneous conclusions.
Trying to confirm one’s hypothesis can limit objectivity in personal analysis.
Heuristics
A heuristic is a mental shortcut or strategy that typically simplifies decision-making.
Availability Heuristic:
Estimation of frequency or probability of an event based on how easily examples come to mind.
Example Scenario
Case study with Fred:
Fred is a well-liked male who is likely to succeed based on personal characteristics.
Task: Determine whether Fred is more likely to be a lawyer or engineer.
Base-rate neglect demonstrated: More prevalent group (engineers) statistically outbalances individual characteristics, which many overlook.
Hypothesis Testing and Bias
Experiment with a number series:
Challenge in properly assessing the rule and obtaining results which reinforce assumptions.
Emphasis on the need for selecting tests that can disprove hypotheses.
Understanding Variables in Psychology Research
Definition of a variable:
Anything that can vary across different subjects or conditions and is quantifiable.
Examples of Variables in Psychology:
Age, height, incentive level, day of the week, etc.
Types of Variables
Categorization of Variables:
Quantitative vs. Categorical
Continuous vs. Discrete
Dependent Variable (DV): The outcome measured (e.g., test score).
Independent Variable (IV): The manipulated condition (e.g., type of stimuli presented).
Subject Variables: Demographic characteristics like age, gender, and ethnicity used only for categorization and cannot be manipulated.
Psychological Constructs
Theoretical concepts like aggression and creativity can only be inferred indirectly.
Definitions of Constructs
Conceptual Definitions: Abstract definitions of psychological constructs.
Operational Definitions: Concrete procedures used to measure these constructs (e.g., using an IQ test to measure intelligence).
Claims in Psychology:
Frequency claims describe levels of variables.
Association claims infer correlations without establishing causation.
Causal claims assert direct influence between variables requiring robust evidence.
Validity in Research
Validity Defined: Accuracy and truthfulness of what a study claims to measure.
Construct Validity: Aligns measurement with psychological constructs.
External Validity: Generalizability of findings across various groups and contexts.
Statistical Validity: Robustness of study results and implications of chance.
Types of Validity
Internal Validity: Differentiation between cause and effect with respect to confounding variables.
Morris’s Matrix: An analytical tool crossing psychological claims with claims of validity.
Causal Relationships
Three Criteria for Causation:
Covariance: Changes in both variables must correlate.
Temporal Precedence: Causal variable must precede outcome variable.
Internal Validity: Eliminates alternate explanations for results.
Measurement Principles
Respect for persons in research is paramount.
Measurement Types
Reliability: Consistency of measurements across time and testers.
Types of Measurement Scales:
Nominal: Classifies events into different categories (e.g., male/female).
Ordinal: Ranks variables (e.g., finishing places in a race).
Interval: Quantitative scores with equal intervals (e.g., temperature).
Ratio: Quantitative scores with a true zero point (e.g., weight).
Statistical Measures of Central Tendency
Mean, Median, Mode: Basic statistical measures conveying the average score in a dataset.
Frequency Distribution Table: Overview of data spread across intervals.
Normal Curves: Many dependent variables exhibit a bell-shaped, Gaussian distribution.
Measures of Variability
Range, Variance, Standard Deviation: Metrics describing score distribution across a dataset.
Z-scores: Standardizes raw scores based on deviations from the mean.
Conclusion on Measurement Principles
Understanding reliability and validity is crucial for accurate psychological assessments and interpretations of data.