PedestrianA pedestrian is a person traveling on foot, whether walking or running. In modern times, the term usually refers to someone walking on a road or pavement, but this was not the case historically. The meaning of pedestrian is displayed with the morphemes ped- ('foot') and -ian ('characteristic of'). This word is derived from the Latin term pedester ('going on foot') and was first used (in English language) during the 18th century. It was originally used, and can still be used today, as an adjective meaning plain or dull.
WalkabilityIn urban planning, walkability is the accessibility of amenities by foot. It is based on the idea that urban spaces should be more than just transport corridors designed for maximum vehicle throughput. Instead, it should be relatively complete livable spaces that serve a variety of uses, users, and transportation modes and reduce the need for cars for travel. The term "walkability" was primarily invented in the 1960s due to Jane Jacobs' revolution in urban studies.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
Pedestrian crossingA pedestrian crossing (or crosswalk in American English) is a place designated for pedestrians to cross a road, street or avenue. The term "pedestrian crossing" is also used in the Vienna and Geneva Conventions, both of which pertain to road signs and road traffic. Marked pedestrian crossings are often found at intersections, but may also be at other points on busy roads that would otherwise be too unsafe to cross without assistance due to vehicle numbers, speed or road widths.
Cycling infrastructureCycling infrastructure is all infrastructure cyclists are allowed to use. Bikeways include bike paths, bike lanes, cycle tracks, rail trails and, where permitted, sidewalks. Roads used by motorists are also cycling infrastructure, except where cyclists are barred such as many freeways/motorways. It includes amenities such as bike racks for parking, shelters, service centers and specialized traffic signs and signals. The more cycling infrastructure, the more people get about by bicycle.
Bayesian statisticsBayesian statistics (ˈbeɪziən or ˈbeɪʒən ) is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous experiments, or on personal beliefs about the event. This differs from a number of other interpretations of probability, such as the frequentist interpretation that views probability as the limit of the relative frequency of an event after many trials.
Bayesian probabilityBayesian probability (ˈbeɪziən or ˈbeɪʒən ) is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification of a personal belief. The Bayesian interpretation of probability can be seen as an extension of propositional logic that enables reasoning with hypotheses; that is, with propositions whose truth or falsity is unknown.
InfrastructureInfrastructure is the set of facilities and systems that serve a country, city, or other area, and encompasses the services and facilities necessary for its economy, households and firms to function. Infrastructure is composed of public and private physical structures such as roads, railways, bridges, tunnels, water supply, sewers, electrical grids, and telecommunications (including Internet connectivity and broadband access).
Bayesian networkA Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). It is one of several forms of causal notation. Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms.
Big dataBig data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.
