AP Psych Unit 0

critical thinking

Thinking that does not automatically accept arguments and conclusions. Rather it examines assumptions, appraises the source, discerns hidden biases, evaluates evidence, and assesses conclusions

ex: A student reads about a new memory drug and questions whether the research was done with a control group.

hindsight bias

• The tendency to believe, after learning an outcome, that we would have foreseen it (“I-knew-it-all-along” phenomenon).

• Example: After a football game, fans insist they “knew all along” their team would win.

peer reviewers

• Independent experts who evaluate the quality and validity of a scientific study before it is published.

• Example: Psychologists submit a new study on sleep and learning to a journal, and other researchers critique its methods.

theory

• An explanation using an integrated set of principles that organizes observations and predicts behaviors or events.

• Example: The theory that sleep improves memory consolidation.

hypothesis

• A testable prediction, often implied by a theory.

• Example: People who get 8 hours of sleep will recall vocabulary words better than those who get 4 hours.

falsifiable

• The ability for a claim or hypothesis to be tested and proven wrong.

• Example: “Dreams help problem solving” is falsifiable because it can be tested by comparing performance of dreamers vs. non-dreamers.

Operational Definition

• A carefully worded statement of the exact procedures used in a research study.

• Example: Defining “sleep deprived” as “less than 5 hours of sleep per night for a week.”

replication

• Repeating the essence of a research study to see whether the basic finding extends to other participants and circumstances.

• Example: A second lab repeats a memory experiment with different age groups to confirm results.

case study

• A descriptive technique in which one individual or group is studied in depth to reveal universal principles.

• Example: Studying the brain damage of Phineas Gage to learn about personality and the frontal lobe.

naturalistic observation

• Observing and recording behavior in naturally occurring situations without manipulating or controlling the situation.

• Example: Watching chimpanzees in the wild to study their social interactions.

survey

• A descriptive technique for obtaining the self-reported attitudes or behaviors of a group, usually by questioning a random sample.

• Example: Asking high school students how many hours of sleep they get each night.

social desirability bias

• The tendency of participants to respond in ways that make them appear more favorable to others.

• Example: A teen underreports alcohol use on a survey.

self-report bias

• Inaccuracy in survey or interview responses due to memory errors, exaggeration, or intentional misreporting.

• Example: A person exaggerates their weekly exercise because they want to appear healthier.

sampling bias

• A flawed sampling process that produces an unrepresentative sample.

• Example: Surveying only psychology majors to represent all college students.

random sample

• A sample that fairly represents a population because each member has an equal chance of inclusion.

• Example: Using a random-number generator to select 100 students from the school roster.

population

• All those in a group being studied, from which samples may be drawn.

• Example: The population of interest in a high school survey is all students at the school.

correlation

• A measure of the extent to which two factors vary together, and how well either factor predicts the other.

• Example: Height and weight show a positive correlation.

correlation coefficient

• A statistical index of the relationship between two things, ranging from –1.0 to +1.0.

• Example: A correlation of +0.85 between study hours and GPA.

variable

• Any factor that can vary and is feasible and ethical to study.

• Example: Amount of sleep is a variable in a sleep–memory experiment.

scatterplot

• A graphed cluster of dots, each representing the values of two variables.

• Example: A scatterplot of stress levels and exam performance.

illusory correlation

• The perception of a relationship where none exists.

• Example: Believing that full moons cause strange behavior.

regression toward the mean

• The tendency for extreme scores or events to regress toward the average.

• Example: An athlete’s unusually high score is likely to be closer to average next game.

experiment

• A research method in which an investigator manipulates one or more variables to observe effects on behavior or mental processes.

• Example: Testing if caffeine improves memory by comparing groups who consume coffee vs. decaf.

experimental group

• In an experiment, the group exposed to the treatment.

• Example: Students who drink caffeinated coffee before a test.

control group

• in an experiment, the group not exposed to the treatment, serving as a comparison.

• Example: Students who drink decaf before the test.

random assignment

• Assigning participants to experimental and control groups by chance, minimizing differences between groups.

• Example: Flipping a coin to decide who gets caffeine.

single-blind procedure

• An experimental procedure in which participants are unaware of whether they are in the experimental or control group.

• Example: Students don’t know whether their pill has caffeine.

double-blind procedure

• An experimental procedure in which both participants and research staff are ignorant of who has received treatment or placebo.

• Example: Neither students nor proctors know which pill contains caffeine.

placebo effect

• Experimental results caused by expectations alone.

• Example: Students who believe their decaf coffee contains caffeine still perform better on a test.

independent variable

• The factor that is manipulated; the variable whose effect is being studied.

• Example: Whether the coffee is caffeinated or not.

confounding variable

• A factor other than the independent variable that might produce an effect in an experiment.

• Example: Differences in students’ prior sleep levels.

experimenter bias

• When a researcher’s expectations or preferences influence the outcome of a study.

• Example: A researcher unintentionally hints to participants about expected results.

dependent variable

• The outcome that is measured; the variable that may change when the independent variable is manipulated.

• Example: Students’ test performance.

validity

• The extent to which a test or experiment measures or predicts what it is supposed to.

• Example: A math test that actually measures math ability has validity.

quantitative research

• Research that collects numerical data and uses statistical analysis.

• Example: Measuring the number of hours slept and test scores.

qualitative research

• Research that explores subjects in depth without relying on numerical data.

• Example: Conducting interviews about students’ feelings toward school.

informed consent

• Ethical principle that participants be told enough to enable them to choose whether they wish to participate.

• Example: Researchers inform volunteers about possible risks before a study.

protection from harm

• Ethical principle requiring researchers to protect participants from physical or emotional harm.

• Example: A stress study stops if participants become too distressed.

debriefing

• The post-experimental explanation of a study, including its purpose and deceptions, to participants.

• Example: Explaining to participants that the “memory drug” was actually a placebo.

confidentiality

• Protecting participants’ personal information and keeping responses private.

• Example: Researchers do not attach names to survey answers.

descriptive statistics

• Numerical data used to measure and describe characteristics of groups.

• Example: Reporting the average test score for a class.

histogram

• A bar graph depicting a frequency distribution.

• Example: Graphing how many students scored in each test-score range.

mode

• The most frequently occurring score in a distribution.

• Example: If the most common test score is 85, that’s the mode.

mean

• The arithmetic average of a distribution.

• Example: Adding all scores and dividing by the number of students.

median

• The middle score in a distribution.

• Example: In an ordered set of test scores, the score exactly in the middle.

percentile rank

• The percentage of scores in a distribution that a particular score is above.

• Example: A student in the 90th percentile scored higher than 90% of test-takers.

skewed distribution

• A representation of scores that lack symmetry around their average value.

• Example: Income data often skews right because a few very high earners raise the mean.

range

• The difference between the highest and lowest scores.

• Example: If the highest test score is 100 and the lowest is 60, the range is 40.

standard deviation

• A computed measure of how much scores vary around the mean score.

• Example: A small standard deviation means students’ test scores were close to the average.

normal curve

• A symmetrical, bell-shaped curve that describes the distribution of many data types.

• Example: IQ scores form a normal distribution with most around 100.

inferential statistics

• Numerical methods that allow researchers to generalize from sample data to the probability of something being true for a population.

• Example: Using a sample of students’ scores to estimate average performance of all students.

meta-analysis

• A statistical procedure that combines the results of many different research studies.

• Example: Analyzing dozens of therapy studies to see if treatment reduces depression.

statistical significance

• A statistical statement of how likely it is that a result occurred by chance.

• Example: A p-value less than 0.05 means the result is statistically significant.

effect size

• A statistical measure of the strength of a relationship between two variables.

• Example: An effect size showing therapy reduces depression symptoms by a large margin.