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Pages in category "Multiple-criteria decision analysis" The following 32 pages are in this category, out of 32 total. This list may not reflect recent changes .
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).
When the computer calculates a formula in one cell to update the displayed value of that cell, cell reference(s) in that cell, naming some other cell(s), causes the computer to fetch the value of the named cell(s). A cell on the same "sheet" is usually addressed as: =A1 A cell on a different sheet of the same spreadsheet is usually addressed as:
A pivot table is a table of values which are aggregations of groups of individual values from a more extensive table (such as from a database, spreadsheet, or business intelligence program) within one or more discrete categories. The aggregations or summaries of the groups of the individual terms might include sums, averages, counts, or other ...
It features Excel Web Access, the client-side component which is used to render the worksheet on a browser, Excel Calculation Service which is the server side component which populates the worksheet with data and perform calculations, and Excel Web Services that extends Excel functionalities into individual web services.
The analysis of competing hypotheses (ACH) is a methodology for evaluating multiple competing hypotheses for observed data. It was developed by Richards (Dick) J. Heuer, Jr., a 45-year veteran of the Central Intelligence Agency, in the 1970s for use by the Agency. [1]
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.
Although the 30 samples were all simulated under the null, one of the resulting p-values is small enough to produce a false rejection at the typical level 0.05 in the absence of correction. Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a "discovery".