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Windows: Originated in NASA World Wind: Estereografica Web [15] Stereographic projection and fault kinematics Reyuntec Public domain Cross-platform: ASP.net Free web application (english and spanish) Generic Mapping Tools [16] Map generation and analysis Lamont–Doherty and University of Hawaii: GPL: Cross-platform: C: Implemented in OpendTect ...
List of free analog and digital electronic circuit simulators, available for Windows, macOS, Linux, and comparing against UC Berkeley SPICE.The following table is split into two groups based on whether it has a graphical visual interface or not.
Parallel analysis, also known as Horn's parallel analysis, is a statistical method used to determine the number of components to keep in a principal component analysis or factors to keep in an exploratory factor analysis. It is named after psychologist John L. Horn, who created the method, publishing it in the journal Psychometrika in 1965. [1]
The primary difference between a computer algebra system and a traditional calculator is the ability to deal with equations symbolically rather than numerically. The precise uses and capabilities of these systems differ greatly from one system to another, yet their purpose remains the same: manipulation of symbolic equations.
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Interactive help is available. The program provides methods that are appropriate for matched and independent t-tests, [2] survival analysis, [5] matched [6] and unmatched [7] [8] studies of dichotomous events, the Mantel-Haenszel test, [9] and linear regression. [3]
When most lines between two parallel axes are somewhat parallel to each other, it suggests a positive relationship between these two dimensions. When lines cross in a kind of superposition of X-shapes, it's a negative relationship. When lines cross randomly or are parallel, it shows there is no particular relationship.
Analysis of parallel algorithms is usually carried out under the assumption that an unbounded number of processors is available. This is unrealistic, but not a problem, since any computation that can run in parallel on N processors can be executed on p < N processors by letting each processor execute multiple units of work.