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In business and project management, a responsibility assignment matrix [1] (RAM), also known as RACI matrix [2] (/ ˈ r eɪ s i /; responsible, accountable, consulted, and informed) [3] [4] or linear responsibility chart [5] (LRC), is a model that describes the participation by various roles in completing tasks or deliverables [4] for a project or business process.
At each intersection, a relationship is either absent or present. It then gives information about the relationship, such as its strength, the roles played by various individuals or measurements. The matrix diagram enables you to analyze relatively complex situations by exposing interactions and dependencies between things.
N 2 chart example. [1] The N 2 chart or N 2 diagram (pronounced "en-two" or "en-squared") is a chart or diagram in the shape of a matrix, representing functional or physical interfaces between system elements. It is used to systematically identify, define, tabulate, design, and analyze functional and physical interfaces.
A sample DSM with 7 elements and 11 dependency marks. The design structure matrix (DSM; also referred to as dependency structure matrix, dependency structure method, dependency source matrix, problem solving matrix (PSM), incidence matrix, N 2 matrix, interaction matrix, dependency map or design precedence matrix) is a simple, compact and visual representation of a system or project in the ...
The example above is the simplest kind of contingency table, a table in which each variable has only two levels; this is called a 2 × 2 contingency table. In principle, any number of rows and columns may be used. There may also be more than two variables, but higher order contingency tables are difficult to represent visually.
A matrix organization. Matrix management is an organizational structure in which some individuals report to more than one supervisor or leader—relationships described as solid line or dotted line reporting, also understood in context of vertical, horizontal & diagonal communication in organisation for keeping the best output of product or services.
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Confusion matrix is not limited to binary classification and can be used in multi-class classifiers as well. The confusion matrices discussed above have only two conditions: positive and negative. For example, the table below summarizes communication of a whistled language between two speakers, with zero values omitted for clarity. [20]