CF

Psychology: Core Concepts and Research Methods (Flashcards)

Fields of Psychology

  • Cognitive psychology: study of mental processes (perception, memory, language); informs learning and interfaces.

  • Biological psychology: biological basis of behavior (brain, nervous system); explains drug effects and brain injuries.

  • Sociocultural psychology: social and cultural influence on thoughts and behaviors; cross-cultural differences.

  • Behavioral psychology: observable behavior learned or unlearned; involves conditioning and reinforcement.

  • Evolutionary psychology: psychological traits as evolutionary adaptations; explains mating and cooperation.

  • Humanistic psychology: growth, self-actualization, and subjective experience; applies to client-centered therapy.

  • Psychodynamic psychology: unconscious processes, early childhood experiences, and internal conflicts shaping behavior.

  • Cultural norms: shared expectations for behavior within a group; influence conformity.

Core Concepts in Research Methods and Cognitive Biases

  • Confirmation bias: tendency to favor information supporting preconceptions; affects decision-making.

  • Hindsight bias: the "knew-it-all-along" effect; overestimating predictability after an event.

  • Overconfidence: overestimating accuracy of one’s beliefs or predictions.

  • Experimental research: manipulates independent variable (IV) to observe effects on dependent variable (DV) with random assignment; allows causal inference.

  • Non-experimental research: descriptive or correlational designs; no IV manipulation or random assignment.

  • Independent variable (IV): the variable manipulated by the researcher.

  • Dependent variable (DV): the variable measured to assess the effect of the IV.

  • Random assignment: allocating participants to experimental conditions by chance.

  • Case study: in-depth examination of a single person, group, or event; has limited generalizability.

  • Correlation: statistical relationship between two variables, ranging from -1 to 1; does not imply causation.

  • Meta-analysis: quantitative synthesis combining results from multiple studies to estimate overall effect.

  • Naturalistic observation: observing behavior in real-world settings without manipulation.

  • Hypothesis: a testable, falsifiable prediction derived from theory.

  • Falsifiable: a statement that can be empirically tested and potentially disproven.

  • Operational definition: a precise, measurable definition of a variable.

  • Confounding variable: an extraneous variable providing an alternative explanation for observed effects on the DV.

  • Population: the entire group about whom conclusions are drawn.

  • Sample: a subset of the population used in a study.

  • Representative sample: a sample that reflects the population’s key characteristics.

  • Random sample: a sample drawn by chance; aims to minimize sampling bias.

  • Convenience sample: a sample selected for ease of access; often biased.

  • Sampling bias: systematic error due to non-random sampling methods.

  • Generalizability: the extent to which findings apply beyond the sample to the population.

  • Experimental group: participants who receive the experimental treatment or condition.

  • Control group: participants who do not receive the experimental treatment or receive a standard/placebo condition.

  • Placebo: an inert treatment used to control for expectancy effects in experiments.

  • Placebo effect: improvement due to participants’ expectations rather than the treatment itself.

  • Single-blind procedure: participants are unaware of their assigned condition.

  • Double-blind procedure: neither participants nor experimenters know the condition assignments.

  • Experimenter bias: researchers’ expectations influencing the results.

  • Social desirability bias: participants respond in a manner they think is viewed favorably by others.

  • Qualitative research: non-numerical data (interviews, observations) analyzed for meaning and patterns.

  • Quantitative research: numerical data analyzed statistically to test hypotheses.

  • Replication: repeating a study to verify findings and establish reliability.

  • Third variable problem: a third variable may account for the correlation between two other variables.

  • Structured interview: a standardized set of questions asked in the same order for all participants.

  • Likert scale: a psychometric scale (e.g., 1–5 or 1–7) to measure attitudes along an ordinal scale.

  • Institutional review (IRB): an ethics board responsible for reviewing research proposals to protect participants.

  • Informed consent: participants are adequately informed and agree to participate in a study.

  • No harm: ethical guideline to minimize risk of physical, psychological, and social harm to participants.

  • Confidentiality: ensuring participants’ data are private and stored securely.

  • Deception: withholding or misrepresenting information about a study’s purpose; requires debriefing.

  • Debriefing: after participation, researchers explain the study’s purpose and address any deception.

  • Histogram: graphical representation of the distribution of a continuous variable using adjacent bars.

  • Scatterplot: graphical display of the relationship between two quantitative variables.

  • Measures of central tendency: statistical summaries that describe the center of a data distribution.

  • Mean: the arithmetic average; \bar{x} = \frac{1}{n} \sum{i=1}^{n} xi

  • Median: the middle value when data are ordered.

  • Mode: the most frequently occurring value in the data set.

  • Normal curve: the bell-shaped, symmetric distribution; for standard normal, the probability density is f(z) = \frac{1}{\sqrt{2\pi}} e^{-z^2/2}.

  • Skewed curve: an asymmetrical distribution where the tail is longer on one side.

  • Bimodal distribution: a distribution with two distinct peaks or modes.

  • Range: the difference between the maximum and minimum values in a data set.

  • Standard deviation: the average distance of data points from the mean; s = \sqrt{\frac{1}{n-1} \sum{i=1}^{n} (xi - \bar{x})^2}.

  • Percentile rank: the percentage of scores in a distribution that fall at or below a given value.

  • Regression toward the mean: extreme observations tend to be closer to the mean on subsequent measurements.

  • Correlation coefficient: measure of linear association between two variables; r = \frac{ \sum (xi - \bar{x})(yi - \bar{y}) }{ \sqrt{ \sum (xi - \bar{x})^2 } \sqrt{ \sum (yi - \bar{y})^2 } }; range from -1 to 1.

  • Effect size: the magnitude of the observed effect, independent of sample size; common measure for group differences is Cohen's d: d = \frac{\bar{X}1 - \bar{X}2}{sp} where sp = \sqrt{\frac{(n1 - 1)s1^2 + (n2 - 1)s2^2}{n1 + n2 - 2}} is the pooled standard deviation.

  • Statistical significance: a result is statistically significant if the probability of obtaining it by chance is below a pre-specified threshold (e.g., \alpha = 0.05).

  • Claim: a testable assertion derived from data or reasoning.

Connections to Practice and Ethics

  • Research methods and biases: Understanding biases improves critical thinking; robust study designs ensure reliable conclusions.

  • Ethical guidelines (IRB, informed consent, no harm, confidentiality): Protect participants and uphold research integrity.

  • Data visualization (histograms, scatterplots) and descriptive statistics (mean, standard deviation, percentile ranks): Essential for interpreting results and communicating findings.

  • Conceptual links: Operational definitions connect measurement to theoretical constructs; third-variable problems highlight the need for causal control; replication reinforces reliability.

  • Real-world relevance: Cultural norms explain behavioral variations; evolutionary perspectives shed light on universal patterns; bias awareness aids decision-making in various fields.

  • Philosophical and practical implications: Balancing internal validity (experimental control) and external validity (generalizability) shapes how findings apply to real-world settings; cautious use of statistics guards against overinterpretation.

  • Numeric references and equations: Quantitative reasoning underpins evidence-based conclusions.

Notes on Completeness

  • The transcript provided items up to 68 (statistical significance) and shows a trailing item 69 which is not given; the notes above cover all listed terms and concepts with definitions, examples, and formulas where applicable.

  • If you have Page 3 or additional context for item 69 or any term not fully elaborated here, I can expand accordingly.