Vocabulary

Ambulatory assessment: An overarching term to describe methodologies that assess the behavior, physiology, experience, and environments of humans in naturalistic settings.
Cause-and-effect: Related to whether we say one variable is causing changes in the other variable, versus other variables that may be related to these two variables.
Confidence interval: An interval of plausible values for a population parameter; the interval of values within the margin of error of a statistic.
Confounds: Factors that undermine the ability to draw causal inferences from an experiment.
Correlation: Measures the association between two variables, or how they go together.
Daily Diary method: A methodology where participants complete a questionnaire about their thoughts, feelings, and behavior of the day at the end of the day.
Day reconstruction method (DRM): A methodology where participants describe their experiences and behavior of a given day retrospectively upon a systematic reconstruction on the following day.
Dependent variable: The variable the researcher measures but does not manipulate in an experiment.
Distribution: The pattern of variation in data.
Ecological momentary assessment: An overarching term to describe methodologies that repeatedly sample participants’ real-world experiences, behavior, and physiology in real time.
Ecological validity: The degree to which a study finding has been obtained under conditions that are typical for what happens in everyday life.
Electronically activated recorder, or EAR: A methodology where participants wear a small, portable audio recorder that intermittently records snippets of ambient sounds around them.
Empirical methods: Approaches to inquiry that are tied to actual measurement and observation.
Ethics: Professional guidelines that offer researchers a template for making decisions that protect research participants from potential harm and that help steer scientists away from conflicts of interest or other situations that might compromise the integrity of their research.
Experience-sampling method: A methodology where participants report on their momentary thoughts, feelings, and behaviors at different points in time over the course of a day.
Experimenter expectations: When the experimenter’s expectations influence the outcome of a study.
External validity: The degree to which a finding generalizes from the specific sample and context of a study to some larger population and broader settings.
Full-cycle psychology: A scientific approach whereby researchers start with an observational field study to identify an effect in the real world, follow up with laboratory experimentation to verify the effect and isolate the causal mechanisms, and return to field research to corroborate their experimental findings.
Generalizability: Related to whether the results from the sample can be generalized to a larger population.
Generalize: Generalizing, in science, refers to the ability to arrive at broad conclusions based on a smaller sample of observations. For these conclusions to be true the sample should accurately represent the larger population from which it is drawn.
Hypotheses: A logical idea that can be tested.
Independent variable: The variable the researcher manipulates and controls in an experiment.
Internal validity: The degree to which a cause-effect relationship between two variables has been unambiguously established.
Linguistic inquiry and word count: A quantitative text analysis methodology that automatically extracts grammatical and psychological information from a text by counting word frequencies.
Lived day analysis: A methodology where a research team follows an individual around with a video camera to objectively document a person’s daily life as it is lived.
Longitudinal study: A study that follows the same group of individuals over time.
Margin of error: The expected amount of random variation in a statistic; often defined for 95% confidence level.
Operational definitions: How researchers specifically measure a concept.
Parameter: A numerical result summarizing a population (e.g., mean, proportion).
Participant demand: When participants behave in a way that they think the experimenter wants them to behave.
Placebo effect: When receiving special treatment or something new affects human behavior.
Population: A larger collection of individuals that we would like to generalize our results to.
P-value: The probability of observing a particular outcome in a sample, or more extreme, under a conjecture about the larger population or process.
Quasi-experimental design: An experiment that does not require random assignment to conditions.
Random assignment: Assigning participants to receive different conditions of an experiment by chance.
Random assignment: Using a probability-based method to divide a sample into treatment groups.
Random sampling: Using a probability-based method to select a subset of individuals for the sample from the population.
Sample: The collection of individuals on which we collect data.
Statistic: A numerical result computed from a sample (e.g., mean, proportion).
Statistical significance: A result is statistically significant if it is unlikely to arise by chance alone.
Systematic observation: The careful observation of the natural world with the aim of better understanding it. Observations provide the basic data that allow scientists to track, tally, or otherwise organize information about the natural world.
Theories: Groups of closely related phenomena or observations.
White coat hypertension: A phenomenon in which patients exhibit elevated blood pressure in the hospital or doctor’s office but not in their everyday lives.