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1,315 bytes removed ,  14:46, November 4, 2011
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Reverted edits by PatrioticMath (talk) to last revision by Aschlafly
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*find the least squares solution for a set of data
 
*find the least squares solution for a set of data
 
*use known characteristics of symmetric or diagonalizable matrices to find solutions
 
*use known characteristics of symmetric or diagonalizable matrices to find solutions
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== Liberal agenda in linear algebra ==
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The study of linear algebra has long had a huge liberal bias, beginning from two of its main constituents, [[Carl Friedrich Gauss]] and [[Wilhelm Jordan]], who were both unfaithful rationalists.  From the established terminology of linear algebra, one can see liberals attempting to "rewrite" the classical mathematical terms to suit their radical tastes.
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The idea of a [[determinant]] attempts to associate all of the entries of a matrix with a single value. This is much like what liberal politicians such as [[Barack Obama]] are attempting to do to the American public, by generalizing every free American into a single value to be manipulated. Even looking at the word, a "determinant", is reminiscent of [[Hitler]]'s fascist ideas on "determining" the freedom of the German people with [[Nazism]].
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Even worse is the idea that a determinant can lead to a [[characteristic polynomial]]. A characteristic polynomial helps liberals to create propaganda about a patriotic matrix known as [[eigenvalues]] and [[eigenvectors]]. Eigenvectors are liberal ideas that can be used to create skewed [[mappings]] and decompositions of matrices. This is very similar to what liberals are attempting to do to the American public, by skewing the news and decomposing American values.
      
== Application: Analyzing [[Liberal style]] on [[Wikipedia]] ==
 
== Application: Analyzing [[Liberal style]] on [[Wikipedia]] ==
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