The general goal in this discipline is for students to
learn the techniques of matrix manipulation so that they can solve
systems of linear equations in any number of variables. Linear
algebra is most often combined with another subject, such as trigonometry,
mathematical analysis, or precalculus.
1.0 Students solve linear equations in any number
of variables by using Gauss-Jordan elimination.
2.0 Students interpret linear systems as coefficient
matrices and the Gauss-Jordan method as row operations on the
coefficient matrix.
3.0 Students reduce rectangular matrices to
row echelon form.
4.0 Students perform addition on matrices and
vectors.
5.0 Students perform matrix multiplication and
multiply vectors by matrices and by scalars.
6.0 Students demonstrate an understanding that
linear systems are inconsistent (have no solutions), have exactly
one solution, or have infinitely many solutions.
7.0 Students demonstrate an understanding of
the geometric interpretation of vectors and vector addition (by
means of parallelograms) in the plane and in three-dimensional
space.
8.0 Students interpret geometrically the solution
sets of systems of equations. For example, the solution set of
a single linear equation in two variables is interpreted as a
line in the plane, and the solution set of a two-by-two system
is interpreted as the intersection of a pair of lines in the plane.
9.0 Students demonstrate an understanding of
the notion of the inverse to a square matrix and apply that concept
to solve systems of linear equations.
10.0 Students compute the determinants of 2
x 2 and 3 x 3 matrices and are familiar with their geometric interpretations
as the area and volume of the parallelepipeds spanned by the images
under the matrices of the standard basis vectors in two-dimensional
and three-dimensional spaces.
11.0 Students know that a square matrix is invertible
if, and only if, its determinant is nonzero. They can compute
the inverse to 2 x 2 and 3 x 3 matrices using row reduction methods
or Cramer's rule.
12.0 Students compute the scalar (dot) product
of two vectors in n- dimensional space and know that
perpendicular vectors have zero dot product.
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