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A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and storage space to maintain the index data structure. Indexes are used to quickly locate data without having to search every row in a database table every time said table is accessed.
In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]
Matched betting (also known as back bet matching, lay bet matching, or double betting) is a betting technique employed by individuals to profit from free bets and incentives offered by bookmakers. Its proponents considered it risk-free in theory-based probability.
Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).
A player who makes double digits in a game in any two of the PTS, REB, AST, STL, and BLK statistics is said to make a double double; in three statistics, a triple double; in four statistics, a quadruple double. A quadruple double is extremely rare (and has only occurred four times in the NBA).
In this example a company should prefer product B's risk and payoffs under realistic risk preference coefficients. Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making (both in daily life and in settings such as business, government and medicine).
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2. Match each participant to one or more nonparticipants on propensity score, using one of these methods: Nearest neighbor matching; Optimal full matching: match each participants to unique non-participant(s) so as to minimize the total distance in propensity scores between participants and their matched non-participants.