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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.
A simple arithmetic calculator was first included with Windows 1.0. [5]In Windows 3.0, a scientific mode was added, which included exponents and roots, logarithms, factorial-based functions, trigonometry (supports radian, degree and gradians angles), base conversions (2, 8, 10, 16), logic operations, statistical functions such as single variable statistics and linear regression.
The RAQSCI model is a mnemonic summary of a business model used to define and structure business requirements. With elements ranked in order of importance, RAQSCI stands for:
A Sharp scientific calculator using infix notation. Note the formula on the dot-matrix line above and the answer on the seven-segment line below, as well as the arrow keys allowing the entry to be reviewed and edited. This calculator program has accepted input in infix notation, and returned the answer , ¯. Here the comma is a decimal separator.
A matrix, has its column space depicted as the green line. The projection of some vector onto the column space of is the vector . From the figure, it is clear that the closest point from the vector onto the column space of , is , and is one where we can draw a line orthogonal to the column space of .
The article on Responsibility assignment matrix cover the same ground as RACI matrix; so I would like to propose redirecting Responsibility assignment matrix to the appropriate section in this article. Greyskinnedboy 03:30, 4 March 2009 (UTC)
A formula editor is a computer program that is used to typeset mathematical formulas and mathematical expressions. Formula editors typically serve two purposes: They allow word processing and publication of technical content either for print publication, or to generate raster images for web pages or screen presentations.
In Julia, the CovarianceMatrices.jl package [11] supports several types of heteroskedasticity and autocorrelation consistent covariance matrix estimation including Newey–West, White, and Arellano. In R , the packages sandwich [ 6 ] and plm [ 12 ] include a function for the Newey–West estimator.