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  • Linear systems of equations

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  • Basic terminology
  • Parametric form of the solution set of a system of linear equations
  • Parametric vector form of the solution set of a system of linear equations
  • Gaussian elimination as a method to solve a linear system
  • Definition of echelon form of a linear system
  • All echelon forms of a linear system have the same free variables
  • Definition of equation operations on a linear system
  • Equation operations on a linear system give an equivalent system.
  • Definition of equivalent systems of linear equations
  • The geometry of linear systems
  • Definition of consistent linear system
  • Definition of inconsistent linear system
  • Definition of homogeneous linear system of equations
  • Homogeneous linear systems are consistent.
  • Definition of nontrivial solution to a homogeneous linear system of equations
  • Definition of trivial solution to a homogeneous linear system of equations
  • A homogeneous system has a nontrivial solution if and only if it has a free variable.
  • The number of solutions to a linear system
  • Definition of basic/dependent/leading variable in a linear system
  • Definition of free/independent variable in a linear system
  • Theorem describing the vector form of sulutions to a linear system.
  • The solutions to a nonhomogeneous system are given by a particular solution plus the solutions to the homogeneous system.
  • Definition of ill-conditioned linear system
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  1. The solutions to a nonhomogeneous system are given by a particular solution plus the solutions to the homogeneous system.

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  • Equivalence theorem for injective linear transformations: The image of a basis for V is a basis for the range of T.#24085
  • Equivalence theorem for injective linear transformations: The inverse of T is a linear transformation on its range.#24078
  • Equivalence theorem for injective linear transformations: The kernel of T is 0.#24081
  • Equivalence theorem for injective linear transformations: The nullity of T is 0.#24080
  • Equivalence theorem for injective linear transformations: The null space of T is 0.#24079
  • Equivalence theorem for injective linear transformations: The rank of T is equals the number of columns in any matrix representation..#24084
  • Equivalence theorem for injective linear transformations: The rank of T is n.#24083
  • Equivalence theorem for injective linear transformations: T(x)=0 only for x=0.#24082
  • Equivalence theorem for nonsingular matrices: the columns of A are a basis for R^n (or C^n).#23653
  • Equivalence theorem for nonsingular matrices: the columns of A are linearly independent.#23651
  • Equivalence theorem for nonsingular matrices: the columns of A span R^n (or C^n).#23649
  • Equivalence theorem for nonsingular matrices: the determinant of A is nonzero.#23665
  • Equivalence theorem for nonsingular matrices: the dimension of the column space of A is n.#23654
  • Equivalence theorem for nonsingular matrices: the equation Ax=0 has only the trivial solution.#23647
  • Equivalence theorem for nonsingular matrices: the equation Ax=b has a solution for all b.#23646
  • Equivalence theorem for nonsingular matrices: the equation Ax=b has a unique solution for all b.#23645
  • Equivalence theorem for nonsingular matrices: the linear transformation given by T(x)=Ax has an inverse.#23663
  • Equivalence theorem for nonsingular matrices: the linear transformation given by T(x)=Ax is an isomorphism.#23664
  • Equivalence theorem for nonsingular matrices: the linear transformation given by T(x)=Ax is one-to-one/injective.#23661
  • Equivalence theorem for nonsingular matrices: the linear transformation given by T(x)=Ax is onto/surjective.#23662
  • Equivalence theorem for nonsingular matrices: the matrix A does not have 0 as an eigenvalue.#23669
  • Equivalence theorem for nonsingular matrices: the matrix A has a left inverse.#23658
  • Equivalence theorem for nonsingular matrices: the matrix A has an inverse.#23657
  • Equivalence theorem for nonsingular matrices: the matrix A has a right inverse.#23659
  • Equivalence theorem for nonsingular matrices: the matrix A has rank n.#23666
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