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experiment: A research method in which a researcher manipulates one variable to determine whether it causes changes in another variable. Experiments are used to establish cause-and-effect relationships.

independent variable: The variable that is manipulated or changed by the researcher in an experiment. It is the suspected cause.

dependent variable: The variable that is measured in an experiment. It changes in response to the independent variable and is the suspected effect.

control variable: Any variable that is kept constant in an experiment so it does not interfere with the results.

population: The entire group of people or subjects that a researcher wants to study.

representative sample: A sample that accurately reflects the characteristics of the population being studied.

representativeness: The degree to which a sample accurately mirrors the population.

experimental group: The group in an experiment that receives the treatment or independent variable.

control group: The group in an experiment that does not receive the treatment and is used for comparison with the experimental group.

random sampling: A process in which every member of a population has an equal chance of being selected for a study. This increases representativeness.

randomly assigned: The process of placing participants into groups by chance to reduce bias and make groups similar.

biases: Systematic errors or influences that distort results and reduce the accuracy of research.

bias of selection: A type of bias that occurs when participants are chosen in a way that makes the sample unrepresentative.

self-selection bias: Bias that occurs when people choose whether or not to participate, often creating unrepresentative groups.

pre-screening advertising bias: Bias created when the wording or advertisement for a study attracts a certain type of participant.

healthy user bias: A bias in which healthier individuals are more likely to participate in research, skewing results.

single-/double-blind design: A single-blind study means participants do not know which group they are in. In a double-blind study, neither the participants nor the researchers know, reducing expectancy effects and experimenter bias.

placebo: An inactive substance or fake treatment given to the control group to measure psychological effects of expectations.

correlational research: A research method that examines relationships between variables without manipulating them. Correlation does not prove causation.

confounding/third/extraneous variable: A variable other than the independent variable that may affect the dependent variable and confuse results.

surveys: Research methods that collect self-reported information from participants through questionnaires or interviews.

longitudinal studies: Studies that follow the same participants over a long period of time to observe changes.

cross-sectional studies: Studies that compare different groups of people at one point in time.

clinical research: Research focused on diagnosing, understanding, or treating psychological disorders and behaviors.

case studies: An in-depth investigation of one person or a small group to gather detailed information.

generalizable: Able to apply research findings from a sample to the larger population.

conceptual definition: A general explanation of a concept or variable in theory.

operational definition: A precise explanation of how a variable is measured or manipulated in a study.

internal validity: The degree to which an experiment accurately shows a cause-and-effect relationship without interference from confounding variables.

external validity: The degree to which research findings can be generalized to other settings, situations, or populations.

reliability: The consistency or repeatability of research results or measurements.

inter-rater reliability: The degree to which different observers or raters agree in their measurements or observations.

naturalistic observation: A research method in which behavior is observed in a natural environment without interference.

qualitative research: Research that focuses on descriptive, non-numerical data such as interviews, observations, and personal experiences.

Statistics

descriptive statistics: Statistical methods used to organize, summarize, and describe data.

inferential statistics: Statistical methods used to draw conclusions or make predictions about a population based on sample data.

central tendency: A measure that identifies the center or average of a distribution. The main measures are mean, median, and mode.

mean: The arithmetic average of a set of numbers found by adding them and dividing by the total number.

mode: The most frequently occurring score in a distribution.

bimodal: A distribution with two modes or two most frequently occurring scores.

median: The middle score in a distribution when the scores are arranged from lowest to highest.

normal curve: A symmetrical, bell-shaped distribution in which most scores cluster around the mean.

range: The difference between the highest and lowest scores in a distribution.

variability: The extent to which scores differ from one another in a distribution.

standard deviation: A measure of how spread out scores are from the mean in a distribution.

percentile: A score that indicates the percentage of scores below a given score.

positive skew: A distribution in which the tail extends to the right because of a few unusually high scores.

negative skew: A distribution in which the tail extends to the left because of a few unusually low scores.

correlation coefficient: A numerical measure ranging from -1.00 to +1.00 that indicates the strength and direction of a relationship between two variables.

Pearson correlation coefficient: The most common correlation coefficient, symbolized by r, used to measure linear relationships between variables.

positive correlation: A relationship in which two variables increase or decrease together.

negative correlation: A relationship in which one variable increases while the other decreases.

sample size: The number of participants or observations included in a study.

null hypothesis: A prediction stating that there will be no effect, difference, or relationship between variables.

alternative hypothesis: A prediction stating that there will be an effect, difference, or relationship between variables.

alpha: The significance level used in hypothesis testing, often set at 0.05, representing the probability of rejecting the null hypothesis incorrectly.

Type I error: A false positive; rejecting the null hypothesis when it is actually true.

Type II error: A false negative; failing to reject the null hypothesis when it is actually false.

p-value: The probability that the results occurred by chance. A small p-value suggests the findings are statistically significant.

Ethics in Research

deception: Misleading participants about the true purpose of a study when necessary for research validity. Ethical guidelines require that participants be debriefed afterward.

Stanley Milgram: A psychologist famous for his obedience experiments, which studied how far people would go in obeying authority figures.

confederates: People secretly working with researchers while pretending to be participants.

Institutional Review Boards (IRBs): Committees that review research studies to ensure ethical treatment and protection of participants.

informed consent: The process of giving participants enough information about a study so they can voluntarily decide whether to participate.

debriefing: Explaining the true purpose and details of a study to participants after it ends, especially if deception was used.

confidentiality: Protecting participants’ private information and keeping research data secure.

Important Connection: In experiments, the independent variable is manipulated while the dependent variable is measured. A Type I error is a false positive, while a Type II error is a false negative. Ethical research requires informed consent, confidentiality, and debriefing, and is overseen by IRBs.

Important Connections: Experimental groups receive the treatment, while control groups often receive a placebo for comparison. Random sampling helps create a representative sample, while random assignment helps create equivalent groups.

Important Connections: Correlational research can show relationships between variables, but it cannot prove causation because confounding variables may exist. Positive and negative correlations are measured using a correlation coefficient, often Pearson’s r.

Important Connections: Internal validity focuses on controlling variables within the study, while external validity focuses on whether findings can be generalized.Reliability refers to consistency of results, while validity refers to whether the study actually measures what it claims to measure. Measures of central tendency include the mean, median, and mode.