Research methods

Scientific attitude / skepticism

Questioning claims and looking for evidence.

Critical thinking

Carefully analyzing evidence before making a conclusion.

Overconfidence

Being more confident than you should be.

Barnum effect

Believing a vague description specifically describes you.

Hindsight bias

Believing you knew an outcome after it happened.

Theory

An explanation of why something happens.

Hypothesis

A testable prediction.

Operational definition

Exactly how a variable is measured or manipulated.

Replication

Repeating a study to check whether results are consistent.

Case study

Studying one person or small group in depth.

Naturalistic observation

Watching behavior in a natural setting without interfering.

Survey

Asking people questions to collect information.

Generalizability

How well findings apply to a larger population.

Wording effect

How a question is phrased influences responses.

False consensus effect

Overestimating how many people agree with you.

Social desirability bias

Giving answers that make you look good.

Sampling bias

Choosing a sample that doesn't represent the population.

Population

The entire group researchers want to study.

Simple random sampling

Randomly selecting individuals from the population.

Cluster random sampling

Randomly selecting entire groups and studying everyone in them.

Stratified random sampling

Dividing people into categories and randomly selecting individuals from each.

Correlation

A relationship between two variables.

Positive correlation

Both variables move in the same direction.

Negative correlation

Variables move in opposite directions.

Correlation coefficient

A number from -1 to +1 showing the strength and direction of a linear relationship.

Scatterplot

A graph of dots showing the relationship between two variables.

Correlation vs. causation

A relationship doesn't prove one variable causes another.

Illusory correlation

Believing two things are related without sufficient evidence.

Ex post facto study

Comparing existing groups after differences or events have already occurred.

Experiment

Manipulating a variable to test cause and effect.

Experimental group

The group receiving the treatment being tested.

Control group

The comparison group that doesn't receive the treatment being tested.

Random assignment

Placing participants into experimental groups by chance.

Single-blind procedure

Participants don't know which treatment condition they're in.

Double-blind procedure

Neither participants nor researchers interacting with them know who receives which treatment.

Placebo effect

Changes caused by expectations rather than an active treatment.

Independent variable

What the researcher manipulates.

Dependent variable

What the researcher measures.

Confounding variable

An outside factor that could affect the results.

Validity

How accurately a study measures or tests what it claims to.

Demand characteristics

Clues that cause participants to change behavior because they guess the study's purpose.

Experimenter bias

Researcher expectations unintentionally influence results.

Quantitative research

Research using numerical data.

Qualitative research

Research using descriptions or experiences.

Research ethics

Rules protecting participants and ensuring responsible research.

Informed consent

Participants understand important study details and voluntarily agree.

Debriefing

Explaining the study's purpose and procedures afterward.

Deception

Intentionally withholding or misleading participants about some study details.

Psychological stress

Emotional distress researchers must minimize.

Culture in research

Considering cultural differences and avoiding cultural bias.

Scientific integrity

Conducting and reporting research honestly.

Descriptive statistics

Numbers used to summarize data.

Histogram

A graph showing frequencies of numerical values in intervals.

Positive skew

A distribution with a long tail to the right.

Negative skew

A distribution with a long tail to the left.

Normal curve

A symmetrical bell-shaped distribution with most scores near the mean.

Effect size

How large a difference or relationship is.

Inferential statistics

Using sample data to draw conclusions about a population.

Statistical significance

Evidence that results are unlikely under the null hypothesis.

P-value

Probability of results at least as extreme as those observed.

Null hypothesis

The assumption that there is no effect or relationship.

Type I error

Rejecting a true null hypothesis, also called a false positive.

Type II error

Failing to reject a false null hypothesis, also called a false negative.