AP Psychology vocabulary

Vocabulary flashcards covering key concepts in AP Psychology research design, statistics, measurement, and ethics based on all provided lecture notes.

Independent vs. Dependent Variable

1. The independent variable is changed; the dependent variable is the outcome .

Example: Hours studied (independent) and test score (dependent).

Culture

The shared ways of thinking, behaving, and living of a group.

Illusory Correlation

Thinking two things are connected when they aren’t.

Scatterplot

graph showing how two things are related

Range

The difference between the highest and lowest score.

1. Example: Highest grade is 100 and lowest is 70, so the range is 30.

Random Assignment

1. Randomly placing participants into different groups.

2. Example: Flipping a coin to decide who goes into each group.

Confounding Variable

1. An outside factor that affects the results of a study.

2. Example: One classroom is quieter than another during testing.

Placebo and Placebo Effect

1. A placebo is a fake treatment; the placebo effect happens when people improve because they think the treatment is real.

2. Example: Someone feels better after taking a sugar pill.

Experiment

1. study used to find cause and effect.

2. Example: Testing whether extra sleep improves test scores.

3rd Variable Problem

1. A hidden factor that may explain a relationship between two variables.

2. Example: Hot weather causes both ice cream sales and swimming to increase.

Experimental Group vs. Control Group

1. The experimental group gets the treatment; the control group does not.

2. Example: One group drinks caffeine before a test and the other group doesn’t.

Standard Deviation

1. A measure of how spread out scores are.

2. Example: Test scores that vary a lot have a high standard deviation.

Debriefing

1. Explaining the purpose of a study after it is finished.

2. Example: Researchers tell participants what was really being tested..

Confirmation Bias

1. Looking for information that supports what you already believe.

2. Example: I only read reviews that agree with my opinion about a movie.

Confederate

1. person working with researchers who pretends to be a participant.

2. Example: Someone in an experiment intentionally gives wrong answers to see how others react.

Descriptive vs. Inferential Statistics

1. Descriptive statistics summarize data; inferential statistics make predictions from data.

2. Example: Finding the average score versus predicting future scores.

Percentile Rank

1. The percentage of scores at or below a certain score.

2. Example: Scoring in the 90th percentile means you scored higher than 90% of people.

Bimodal Distribution

1. A distribution with two common peaks.

2. Example: A class where many students got A’s and many got F’s.

Statistical Significance

1. Results that are unlikely to happen by chance.

2. Example: A study finds a new teaching method consistently improves grades.

Effect Size

1. measure of how strong a result is.

2. Example: Comparing how much two study methods improve scores.

Single Blind vs. Double Blind

1. Single-blind means participants don’t know their group; double-blind means neither participants nor researchers know.

2. Example: A medicine study where nobody knows who got the real medicine.

Four Major Ethical Guidelines

ethical standards that protect participants in research of: respect, honesty, responsibility, and fairness.

Mean, Median, Mode

1. Three ways to find the center of a data set.

2. Example: Calculating the average grade in a class.

Informed Consent vs. Informed Assent

1. Consent is permission from adults;

   •. assent: is agreement from minors.

2. Example: A student agrees to participate and a parent signs the permission form.

Normal Curve

1. A bell-shaped graph where most scores are near the average.

2. Example: Most students score around the middle on a test.

Hindsight Bias

1. Thinking you knew what would happen after it already happened.

2. Example: After losing a game, I say, “I knew we were going to lose.”

Operational Definition

1. A clear explanation of how something is measured in a study.

2. Example: Defining exercise as running for 30 minutes each day.

Reliability vs. Validity

1. Reliability means consistent results;

•validity: means measuring what you’re supposed to measure.

1. Example: A scale gives the same weight every time and measures weight correctly.

Naturalistic Observation

1. Watching behavior in a natural setting.

2. Example: Observing students during lunch without interacting with them.

Survey

1. Collecting information by asking people questions.

2. Example: Using a Google Form to ask students about homework.

Sample vs. Population

Sample: part of group

Population: whole group

1. Representative Sample

1. sample that reflects the population being studied.

2. Example: Including students from every grade level in a survey.

Random Sampling

1. Giving everyone an equal chance of being selected.

2. Example: Picking names from a hat.

Meta-Analysis

1. Combining results from many studies into one analysis.

2. Example: Reviewing dozens of studies about stress.

Falsifiability

1. Whether an idea can be tested and proven wrong.

2. Example: Testing if students who study more get higher grades.

Theory

An explanation for why something happens.

Case Study

1. in-depth study of one person or small group.

2. Example: Studying one person with a rare memory condition.

Correlation

1. A relationship between two variables.

2. Example: More studying is related to higher test scores.

Overconfidence

1. Being more sure of yourself than the facts support.

2. Example: I think I’ll get an A on a test without studying.

Generalizability

1. How well study results apply to a larger group.

2. Example: A study of many schools can apply to most students.

Replication

1. Repeating a study to see if the same results happen again.

2. Example: Another scientist repeats an experiment and gets similar results.

Hypothesis

A testable guess about what will happen.