Data editing - Data editing is the process of checking data for errors, omissions, and inconsistencies and handling identified problems through documented procedures.
Data generating process - A data generating process, often abbreviated DGP, is the mechanism or probabilistic specification that produces observations.
Data normalization - Data normalization is the transformation of numerical data into a scale or form suitable for analysis or machine learning.
Data reduction - Data reduction is the creation of a smaller or simpler representation of data for a defined analytical purpose.
Data validation according to a list - Data validation according to a list is the checking of a data value against an explicitly defined set of acceptable values for a field.
De Finetti's theorem - De Finetti's theorem connects exchangeability with conditional independence.
De Moivre's law - De Moivre's law is a simple actuarial survival model in which lifetime is uniformly distributed between zero and a specified limiting age.
Deck imputation - Deck imputation fills a missing data item using information from a donor record.
Decoder models - Decoder models, in the language-modeling sense used here, generate sequences by predicting the next token from preceding context.
Decoder-only model - A decoder-only model is a neural sequence model built around a decoder stack without a separate encoder stack for the text input.
Decomposition of time series - Decomposition of time series separates observations recorded over time into components representing different patterns.
Deductive imputation - Deductive imputation supplies a missing value by applying logical relationships to information already available.
Deep model - A deep model is a neural network that transforms inputs through multiple hidden layers before producing an output.
Defective sample - A defective sample, in the historical statistical terminology used by the supplied glossary, is a sample made incomplete because the intended inquiry was...
Deflator - A deflator is a price measure used to remove the effect of price changes from a monetary series so that values can be compared on a common price basis.
Degrees of freedom - Degrees of freedom describe the number of independent directions or pieces of information available after relevant constraints or fitted quantities are...
Deming regression - Deming regression estimates a straight-line relationship when both measured variables contain error.
Density estimation - Density estimation uses observed data to estimate a probability density describing how values are distributed.
Dependent Dirichlet process - A dependent Dirichlet process is a Bayesian construction for a collection of related random probability distributions indexed by predictors, groups, time...
Descriptive (or summary) statistics - Descriptive, or summary, statistics organize and condense observed data so that their main features are easier to understand.
Design effect - A design effect is the ratio of an estimator's variance under a specified sampling design to its variance under a reference simple random sampling design of...
Design of experiments - Design of experiments is the planned organization of interventions, experimental units and measurements to answer a defined question efficiently and credibly.
Detectable difference - A detectable difference is a true population effect that would give a specified statistical test a chosen power under stated design and modeling assumptions.
Deterministic imputation - Deterministic imputation, in the statistical-editing sense used by the OECD glossary, fills a missing or designated field when the other accepted values and...
Deviance information criterion - The deviance information criterion, or DIC, is a Bayesian model-comparison measure that combines posterior average fit with an estimate of effective model...
Deviance (statistics) - Deviance is a likelihood-based measure of how much a fitted statistical model falls short of a saturated model that can fit the observed responses exactly.
Deviation scores - Deviation scores express observations as signed distances from their mean. For an observation x and arithmetic mean x-bar, its deviation score is x - x-bar.
Dichotomous thinking - Dichotomous thinking reduces a question to two opposing categories while overlooking meaningful degrees, uncertainty or alternative interpretations.
Dichotomous variables - Dichotomous variables are variables with two possible categories or values.
Difference scores - Difference scores are values obtained by subtracting one measurement from a corresponding second measurement.
Differential entropy - Differential entropy is an information-theoretic quantity defined for a continuous probability distribution with a density.
Digidot chart - A digidot chart combines a stem-and-leaf display with a time-order plot of the same numerical observations.
Direct sampling - Direct sampling, in the OECD glossary's survey-statistics sense, means that sampled units are actual members of the population being studied and information...
Direct utility estimation - Direct utility estimation is a reinforcement-learning approach that estimates a state's value by averaging the observed returns following visits to that state.
Directional test - A directional test is a statistical hypothesis test whose rejection region lies in one specified direction, commonly called a one-sided or one-tailed test.
Discordant pairs - Discordant pairs are pairs of observations whose order is reversed on two variables: the observation with the higher value on one variable has the lower...
Discourse model - A discourse model is a representation of the entities and relevant relationships established during an unfolding conversation or text.
Discrete distribution - A discrete distribution assigns probabilities to a finite or countably infinite set of possible outcomes.
Discrete random variable - A discrete random variable is a numerical function of a random outcome that takes values in a finite or countably infinite set.
Discrete-time proportional hazards - Discrete-time proportional hazards models describe event occurrence when follow-up is divided into intervals and each interval's event probability is...
Discrete Weibull distribution - The discrete Weibull distribution is a family of distributions for nonnegative integer outcomes, often used for discrete lifetimes or count data.
Discriminant analysis - Discriminant analysis is a family of statistical methods for distinguishing predefined groups using measured predictors.
Discrimination - Discrimination, in predictive statistics, is a model's ability to distinguish observations with different outcomes by assigning appropriately ordered...
Discriminative model - A discriminative model learns to predict an output from an input directly, rather than modeling the full process that generates the inputs.
Disordinal interaction - A disordinal interaction occurs when the direction of a difference between groups reverses across levels of another variable.
Distribution - A distribution describes how values of a variable are spread across possible outcomes or ranges.
Distributional robustness - Distributional robustness is the ability of a model or decision rule to maintain acceptable performance when the data distribution differs from the one used...
Distributional similarity - Distributional similarity is similarity inferred from how linguistic items occur across contexts in a body of text.