Pilot survey - A pilot survey is a preliminary survey conducted to test how a proposed survey works before full implementation.
Placebo-controlled study - A placebo-controlled study compares an intervention with a placebo: a comparison intervention designed to resemble it while omitting the specific active...
Plackett - Burman design - A Plackett - Burman design is a family of economical two-level experimental designs used mainly to screen many candidate factors for influential main effects.
Platt scaling - Platt scaling is a probability-calibration method that fits a logistic, or sigmoid, mapping from a classifier's score to an estimated class probability.
Platykurtic - Platykurtic describes a distribution whose kurtosis is below the normal distribution's value of 3, or equivalently whose excess kurtosis is below zero.
Pocock boundary - A Pocock boundary is a group sequential testing boundary that uses a constant critical value on the standardized test-statistic scale across a planned set...
Point biserial correlation ( r pb ) - Point biserial correlation, commonly written r_pb, measures the association between a binary variable and a numerical variable.
Point estimate - A point estimate is a single numerical value used to estimate an unknown quantity, such as a population mean, probability or model coefficient.
Poisson-Dirichlet distribution - The Poisson - Dirichlet distribution is a probability distribution over ranked sequences of nonnegative proportions that sum to one.
Poisson distribution - The Poisson distribution is a probability distribution for a count taking the values 0, 1, 2 and so on.
Policy capturing - Policy capturing is a research method for describing how people combine information when making judgments or decisions.
Poly-Weibull distribution - The poly-Weibull distribution is a continuous time-to-event distribution constructed by adding several Weibull-type hazard functions.
Pólya urn model - A Pólya urn model is a probability model in which sampling changes the probabilities of future samples through a specified reinforcement rule.
Polynomial regression - Polynomial regression models an outcome using powers of one or more numerical predictors.
Polynomial trend coefficient - A polynomial trend coefficient is a numerical weight used with other such weights to test a specified trend across ordered group means.
Pooled variance - Pooled variance is an estimate formed by combining variance information from several samples.
Population - In statistics, a population is the complete set of units, events or measurements about which a question is asked.
Population variance - Population variance measures the average squared distance of values from their population mean.
Positively skewed - A positively skewed distribution is asymmetric with a tail extending toward larger values, conventionally shown to the right on a horizontal axis.
Post-trained model - A post-trained model is a model that has undergone additional adaptation or refinement after an initial pre-training stage.
Posterior predictive distribution - A posterior predictive distribution describes possible future or replicated observations after accounting for observed data through a Bayesian model.
Posterior probability - Posterior probability is probability conditional on specified evidence after updating a prior probability through a model.
Power - In statistical hypothesis testing, power is the probability that a specified testing procedure rejects the null hypothesis under a particular alternative...
Pre-trained model - A pre-trained model is a model whose parameters have already been learned through an earlier training process before its use in a new workflow or task.
Predictive modeling - Predictive modeling is the process of building and evaluating a model that estimates an unknown target from available information.
Prevalence threshold - Prevalence threshold is a term introduced by Jacques Balayla for a particular geometric point on the curve relating prevalence to positive predictive value...
Principal component regression - Principal component regression, abbreviated PCR, predicts an outcome using selected principal-component scores derived from the predictors.
Principal response curve - A principal response curve, or PRC, summarizes treatment-related changes in several response variables over time relative to a reference treatment or control.
Principal stratification - Principal stratification is a causal-inference framework that defines groups using the joint potential values of a post-treatment variable under each...
Principle of marginality - The principle of marginality is a model-specification guideline that generally retains lower-order terms when a model includes higher-order terms built from...
Principle of maximum caliber - The principle of maximum caliber, often called MaxCal, infers a probability distribution over dynamical paths by maximizing path entropy subject to...
Prior distribution - A prior distribution represents uncertainty about unknown parameters or other model quantities before incorporating the particular data used in the current...
Prior-independent mechanism - A prior-independent mechanism is an allocation and payment rule designed without knowing the exact probability distribution of participants' private...
Prior probability - Prior probability is the probability assigned to an event or hypothesis before incorporating a specified new piece of evidence.
Probabilistic automaton - A probabilistic automaton is a state-based computational model in which transitions can occur according to specified probabilities.
Probabilistic classification - Probabilistic classification predicts probabilities for the possible classes of an observation rather than returning only a class label.
Probabilistic forecasting - Probabilistic forecasting describes a future outcome using a probability distribution or useful parts of that distribution, such as quantiles and prediction...
Probabilistic logic programming - Probabilistic logic programming combines logical rules with explicit representations of uncertainty.
Probabilistic model - A probabilistic model represents uncertain quantities with random variables and probability distributions.
Probabilistic regression model - A probabilistic regression model predicts a numerical outcome together with a representation of uncertainty.
Probabilistic soft logic - Probabilistic soft logic, or PSL, is a framework for specifying probabilistic relational models using weighted logical rules.
Probability - Probability is a numerical measure assigned to an event within a defined model of uncertainty.
Probability based disclosures - Probability based disclosures occur when released information enables a sensitive statement to be inferred with high probability even though the statement...
Probability calibration - Probability calibration concerns whether predicted probabilities agree with observed event frequencies in an appropriate population.
Probability density function - A probability density function, often abbreviated PDF, describes how probability is distributed across the values of an absolutely continuous random variable.
Probability distribution - A probability distribution specifies how probability is assigned to the possible values of a random variable.
Probability management - Probability management is an approach to representing, communicating, and combining uncertainty as reusable data rather than reducing every uncertain input...