Comprehensive Psychology Study Notes (Transcript-Based)

Humanistic Psychology

Personal growth and becoming your best self, with free choice and focusing on your own experiences and potential.

Cognitive Psychology

Studies how we think, perceive, remember, solve problems, and process information.

Behavioral Psychology

Learning from rewards and punishments — behavior shaped by consequences.

Biological Psychology

Looks at how the brain, chemicals, and genes control behavior.

Evolutionary Psychology

Analyzes traits and behaviors as adaptations shaped by natural selection to enhance survival and reproduction.

Psychoanalytic Psychology

Hidden desires and childhood issues shaping behavior.

Sociocultural Psychology

Explores how culture, norms, peers, and societal context shape behavior and mental processes.

Cultural Norms

Rules and expectations for behavior in a society.

Confirmation Bias

When you only notice or look for info that proves what you already believe.

Hindsight Bias

Perceiving events as having been predictable after they occur (the 'I knew it all along' effect).

Overconfidence

Overestimating one’s accuracy or knowledge.

Experimental Methodologies

Manipulate variables to test cause-and-effect relationships (change one thing to see if it causes another thing to happen)

Non-Experimental Methodologies

Observation, surveys, correlational studies; no manipulation of variables.

Case Study

In-depth examination of one person or a single group.

Correlation

Relationship between variables; does not imply causation (shows a connection between things, but doesn’t prove one causes the other)

Meta-Analysis

Statistical technique that combines results from multiple studies.

Naturalistic Observation

Observing subjects in their natural environment without interference.

Hypothesis

Testable prediction about a relationship between variables.

Falsifiable

The ability for a hypothesis to be proven wrong by data.

Operational Definitions

Clear, measurable definitions of variables (ex: happiness will be measured by the score on a 1–10 self-report survey.)

Replication

Repeating a study to assess reliability.

IV (Independent Variable)

The factor deliberately manipulated.

DV (Dependent Variable)

The outcome measured.

Confounding Variable

An outside variable that could affect results.

Population

Entire group to which results are intended to generalize.

Sample

The smaller group of people you actually test, taken from the bigger population.

Representative Sample

A small group that truly represents the bigger group.

Random Sampling

Everyone in the group has the same chance of being picked (example: putting all students’ names in a hat and drawing at random.)

Convenience Sampling

Picking people just because they’re easy to reach, but they don’t fully represent the whole group (example: only surveying your own classmates instead of students from many schools.)

Sampling Bias

Systematic error due to non-representative sampling (A mistake that happens when your sample doesn’t represent the whole group)

Generalizability

Extent to which findings apply to the broader population.

Experimental Group

Receives the treatment in an experiment.

Control Group

Does not receive the treatment in an experiment.

Placebo

Inactive treatment used to control for expectations (e.g., sugar pill).

Single-Blind

Participants do not know whether they are in the experimental or control group.

Double-Blind

Neither participants nor researchers know who is in which group.

Experimenter Bias

When researchers’ beliefs accidentally affect the results — prevented by double-blind studies (example: If a researcher expects a new drug to work, they might (without realizing it) treat those patients differently. In a double-blind study, neither the researcher nor participants know who gets the drug, so bias is reduced.)

Social Desirability Bias

Participants respond in ways they believe are socially acceptable.

Qualitative Data

Descriptive data in words.

Quantitative Data

Numerical data.

Structured Interviews

Pre-set questions asked in a fixed order.

Likert Scales

Attitude or opinion scales (e.g., 1–5).

Peer Review

Evaluation of research by other scientists.

Directionality Problem

Uncertainty about which variable causes the other in correlational studies (example: do kids watch more TV because they have lower grades, or do they have lower grades because they watch more TV)

Third Variable Problem

A separate variable explains the observed relationship between two other variables (ex: example: Ice cream sales and sunburns rise together — but the real cause is hot weather (the third variable))

Survey

Self-reported responses collected from participants.

Wording Effects

Question phrasing influences responses.

Self-Report Bias

Inaccuracies in self-reported data due to memory, social desirability, or other factors.

Institutional Review Board (IRB)

Committee that reviews and approves studies for ethical compliance.

Informed Consent

Participants understand risks and agree to participate voluntarily.

Informed Assent

Minor participants’ agreement (with parental consent) to participate.

Protection from Harm

Researchers must minimize risk and avoid lasting harm to participants.

Confidentiality

Keeping participants’ identities private.

Deception

May be used in research if necessary and harmless; participants must be debriefed afterward.

Confederates

Actors who secretly help carry out the study, posing as participants.

Debriefing

Post-study explanation of the study’s purpose and procedures.

Central Tendency

Measures of the center of a data set (Mean, Median, Mode).

Range

Difference between the highest and lowest values in a data set

Normal Curve

A bell-shaped distribution of data where most scores fall near the mean; about 68% of scores fall within 1 standard deviation, 95% within 2, and 99% within 3.

Skewness

Asymmetry of a distribution (toward high or low values).

Bimodal Distribution

Distribution with two distinct peaks.

Percentile Rank

The percentage of people who scored the same or lower than a certain score (example: If you’re in the 70th percentile on a test, that means you scored better than 70% of the people who took it)

Regression to the Mean

Very high or low scores usually get closer to average if you test again (example: If you score unusually high on one quiz, your next score will probably be closer to your usual average, not that extreme)

Variation

Spread of scores around the center.

Standard Deviation

Typical distance of scores from the mean

Scatterplot

Graphical representation of the relationship between two variables.

Correlation Coefficient (r)

Strength and direction of a linear relationship between two variables, ranging from -1 to +1.

Effect Size

Tells you how big or strong a difference or relationship is (example: Two study methods both improve grades, but if one raises scores by 2 points and the other by 20 points, the second has a much larger effect size)

Statistical Significance (p < .05)

Probability that the observed result occurred by chance is less than 5%; a commonly used threshold for significance.

Participants

Individuals who take part in a study.

Appropriate Representation of Participants

Ensuring diversity/accuracy in the sample.

Variables (non-experimental)

Variables observed but not manipulated.

Qualitative Measurement Instruments

Tools for descriptive data (e.g., interviews, open-ended questions).

Quantitative Measurement Instruments

Tools for numerical data (e.g., surveys, scales)

Mean

Average

Median

Middle score

Mode

Most frequently occurring score.

Quantitative Inferential Data

Numerical data used to make predictions/generalizations.

Qualitative Inferential Data

Descriptive data interpreted for themes/patterns.

Variables (non-experimental)

Factors that are observed but not manipulated by the researcher. Example: studying stress levels and hours of sleep without changing either.

Central Tendency

A way to describe the “center” of a data set. Includes mean (average), median (middle score), and mode (most frequent score).

Measurement Instruments

The tools used to collect data.

Qualitative → interviews, open-ended questions, observations.

Quantitative → surveys, scales, tests, numerical measures.

Qualitative Inferential Data

Descriptive info used to find patterns/themes and make interpretations (e.g., analyzing interview transcripts).

Quantitative Inferential Data

Numerical info used to make predictions/generalizations about a population (e.g., statistical test results).