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In linear algebra, Cramer's rule is an explicit formula for the solution of a system of linear equations with as many equations as unknowns, valid whenever the system has a unique solution. It expresses the solution in terms of the determinants of the (square) coefficient matrix and of matrices obtained from it by replacing one column by the ...
A linear system in three variables determines a collection of planes. The intersection point is the solution. ... Cramer's rule is an explicit formula for the ...
Cramer's rule is a closed-form expression, in terms of determinants, of the solution of a system of n linear equations in n unknowns. Cramer's rule is useful for reasoning about the solution, but, except for n = 2 or 3, it is rarely used for computing a solution, since Gaussian elimination is a faster algorithm.
Consider the system of equations x + y + 2z = 3, x + y + z = 1, 2x + 2y + 2z = 2.. The coefficient matrix is = [], and the augmented matrix is (|) = [].Since both of these have the same rank, namely 2, there exists at least one solution; and since their rank is less than the number of unknowns, the latter being 3, there are infinitely many solutions.
Sieverts's law, in physical metallurgy, is a rule to predict the solubility of gases in metals. Named after German chemist Adolf Sieverts (1874–1947). Smeed's law is an empirical rule relating traffic fatalities to traffic congestion as measured by the proxy of motor vehicle registrations and country population. After R. J. Smeed.
The number of distinct terms (including those with a zero coefficient) in an n-th degree equation in two variables is (n + 1)(n + 2) / 2.This is because the n-th degree terms are ,, …,, numbering n + 1 in total; the (n − 1) degree terms are ,, …,, numbering n in total; and so on through the first degree terms and , numbering 2 in total, and the single zero degree term (the constant).
Cramer's rule (See [2] or section 4.1. [3]) The inverse to a Manin matrix M can be defined by the standard formula: M − 1 = 1 det c o l ( M ) M a d j , {\displaystyle M^{-1}={\frac {1}{{\det }^{col}(M)}}M^{adj},} where M adj is adjugate matrix given by the standard formula - its (i,j)-th element is the column-determinant of the (n − 1) × ...
Cramer's rule on the other hand needs to make no decisions at all (all that matters is that the denominator is nonzero, which is the condition for a unique solution to exist in the first place) and can be applied to such a system. That is exactly why the rule is of theoretical importance.