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  2. Elementary algebra - Wikipedia

    en.wikipedia.org/wiki/Elementary_algebra

    If the son's age was made known, then there would no longer be two unknowns (variables). The problem then becomes a linear equation with just one variable, that can be solved as described above. To solve a linear equation with two variables (unknowns), requires two related equations. For example, if it was also revealed that: Problem in words

  3. Linear equation - Wikipedia

    en.wikipedia.org/wiki/Linear_equation

    Conversely, every line is the set of all solutions of a linear equation. The phrase "linear equation" takes its origin in this correspondence between lines and equations: a linear equation in two variables is an equation whose solutions form a line. If b ≠ 0, the line is the graph of the function of x that has been defined in the preceding ...

  4. Outline of linear algebra - Wikipedia

    en.wikipedia.org/wiki/Outline_of_linear_algebra

    This is an outline of topics related to linear algebra, the branch of mathematics concerning linear equations and linear maps and their representations in vector spaces and through matrices. Linear equations

  5. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    In three-dimensional Euclidean space, these three planes represent solutions to linear equations, and their intersection represents the set of common solutions: in this case, a unique point. The blue line is the common solution to two of these equations. Linear algebra is the branch of mathematics concerning linear equations such as:

  6. XSLT elements - Wikipedia

    en.wikipedia.org/wiki/XSLT_elements

    anywhere in a tag, for example xsl:value-of.select and xsl:variable.name. name() the name of the tag being processed. Useful if the matching criteria contains |s (pipe symbols). any conditional or match criterion, for example xsl:if.test, xsl:when.test, xsl:template.select and xsl:for-each.select. @ an attribute within the XML.

  7. Proofs involving ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Proofs_involving_ordinary...

    The normal equations can be derived directly from a matrix representation of the problem as follows. The objective is to minimize = ‖ ‖ = () = +.Here () = has the dimension 1x1 (the number of columns of ), so it is a scalar and equal to its own transpose, hence = and the quantity to minimize becomes

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