Hampel test - A Hampel test, commonly called the Hampel identifier, flags observations that lie unusually far from a median relative to a robust estimate of spread based...
Harmonic mean - The harmonic mean of positive numbers is the reciprocal of the arithmetic mean of their reciprocals.
Hartley's test - Hartley's test, also called the F-max test, tests whether several normally distributed populations have equal variances by comparing the largest sample...
Haseman - Elston regression - Haseman - Elston regression is a family of statistical-genetics methods connecting similarity in quantitative traits with genetic sharing between pairs of...
Hawthorne effect - The Hawthorne effect refers to a change in behavior or responses arising because people know they are being observed or studied.
Hazard rate - A hazard rate is the instantaneous rate at which an event occurs at time t among units that have not yet experienced it.
Hazard ratio - A hazard ratio compares the instantaneous event rates of two groups among members who remain event-free at a particular time.
Healthy user bias - Healthy user bias occurs when people who choose a preventive intervention differ from nonusers in other health-related behaviors or characteristics that...
Heavy-tailed distribution - A heavy-tailed distribution assigns substantial probability to extreme values because its tail is not exponentially bounded.
Heckman correction - The Heckman correction is a statistical method for estimating an outcome relationship when outcomes are observed for a nonrandomly selected subset of a...
Heterogeneity of variance - Heterogeneity of variance means that the populations or conditional distributions being compared have different variances.
Heterogeneous subsamples - Heterogeneous subsamples are distinct subsets within a dataset whose characteristics or statistical relationships differ.
Heteroskedasticity-consistent standard errors - Heteroskedasticity-consistent standard errors estimate regression-coefficient uncertainty while allowing error variance to differ across observations.
Hidden Markov model - A Hidden Markov model (HMM) is a probabilistic model for a sequence of observations generated by an unobserved sequence of states.
Hierarchical log-linear model - A hierarchical log-linear model describes expected counts in a contingency table through a linear model for their logarithms, with a hierarchy rule for...
Hierarchical (sequential) sums of squares - Hierarchical (sequential) sums of squares measure how much residual squared error decreases as terms enter a linear model in a specified order.
High-dimensional statistics - High-dimensional statistics studies estimation, prediction, and inference when the number of variables or model parameters is large relative to the...
High frequency data - High frequency data are observations recorded at short time intervals relative to the process being studied.
Higher order interaction - A higher order interaction is a statistical interaction involving three or more predictors or factors.
Hodrick - Prescott filter - The Hodrick - Prescott filter is a time-series smoothing method that separates a series into a smooth trend and a residual commonly called the cycle.
Hoeffding's independence test - Hoeffding's independence test is a nonparametric procedure for assessing whether two random variables are independent, using ranks from paired observations.
Holm - Bonferroni method - The Holm - Bonferroni method is a step-down multiple-testing procedure that controls the family-wise error rate: the probability of rejecting at least one...
Homogeneity of regression - Homogeneity of regression usually means equality of the covariate regression slopes across groups in a common-slope analysis of covariance model.
Homogeneity of variance - Homogeneity of variance is the condition that the populations or model-error distributions being compared have the same variance.
Homogeneity of variance in arrays - Homogeneity of variance in arrays is the condition that the variance of an outcome Y is the same at different values of a predictor X.
Horvitz - Thompson estimator - The Horvitz - Thompson estimator estimates a finite population total by summing each sampled unit's observed value divided by its probability of inclusion.
Hosmer - Lemeshow test - The Hosmer-Lemeshow test is a grouped goodness-of-fit test commonly used with binary logistic regression.
Hot deck imputation - Hot deck imputation fills a missing value using an observed value from a suitable donor record in the same current dataset or survey collection.
Hotelling's t-squared statistic - Hotelling's t-squared statistic, conventionally written T-squared or T^2, measures a multivariate departure while accounting for covariance among variables.
Huber regression - Huber regression fits a regression model using a loss that is quadratic for small residuals and linear for sufficiently large residuals.
Hurdle model - A hurdle model describes an outcome using one component for whether it is zero or positive and another for its size once it is positive.
Hybrid Bayesian network - A hybrid Bayesian network is a Bayesian network containing both discrete and continuous random variables.
Hypergeometric distribution - The hypergeometric distribution gives the number of items of a specified type in a fixed-size simple random sample drawn without replacement from a finite...
Hyperprior - A hyperprior is a prior distribution placed on a parameter that controls another prior distribution.
Hypertabastic survival models - Hypertabastic survival models are parametric time-to-event models built from the hypertabastic probability distribution introduced by Tabatabai and...
Hypothesis - A hypothesis is a candidate claim, explanation, or model considered in relation to evidence.
Hypothesis class approximation error - Hypothesis class approximation error is the limitation imposed by restricting prediction to a particular family of functions.
Hypothesis prior - A hypothesis prior is the probability assigned to a candidate hypothesis before conditioning on the particular evidence being analyzed.
Hypothesis space - A hypothesis space is the set of candidate prediction functions that a learning method is allowed to consider.
Hypothesis testing - Hypothesis testing is a statistical procedure for assessing evidence against a specified null hypothesis using a test statistic and a reference distribution.
Idempotent matrix - An idempotent matrix is a square matrix P that satisfies P*P = P, where the multiplication is ordinary matrix multiplication.
Identifiability analysis - Identifiability analysis examines whether a model's parameters or other quantities can be uniquely determined from the observations the model permits.
Impartial culture - Impartial culture is a probability model for preferences in which each participant independently selects a complete strict ranking uniformly from all...
Implicit models - Implicit models, in probabilistic modeling, specify a procedure for generating samples rather than relying on an explicitly evaluable probability mass or...
Imputation variance - Imputation variance is the component of an estimate's variability associated with replacing missing or unusable observations by imputed values.
Index number - An index number expresses a quantity, price, or other measure relative to a specified reference, commonly set to 100.
Indexed random variable - An indexed random variable is a member of a family of random variables identified by an index, such as X[i], X-t, or Y[i,j].