Linear Algebra Terms

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Can you name the Linear Algebra Ultimate Review?

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vector u times vector v = u1v1+...+unvn
when vector u times vector v = 0, U and v vectors are:
the set of all linear combinations of a set of vectors
vector starting at the origin and ending at a point
system where all constraints are 0 (when every equation in the system equals 0)
the distance between vector u and the projection of vector u onto vector v
If det(A) does not equal 0 then A is
0-parameter solution =
above and below leading ones are zeroes
a basic solution to a linear program in which all variables are nonnegative
A basis that is also an orthonormal set
If given any demand there is a production schedule that meets that demand
choosing a point in a matrix, turning it into a one, then annihilating entries above and below it
If every vector is a unit vector and the vectors are mutually orthogonal then the vectors are
first nonzero entry in every row is one and below each one are zeroes
linear system that does not have any solutions
If AB = I and BA = I then B is the _______ of A.
method used to find the determinant and/or inverse of a 3x3 matrix or larger
the number of vectors in a basis for a vector space
a matrix that represents the cost per dollar to run several companies/industries in an economy
the number of non-zero rows the matrix has after it has been put in ref
A^t (switching a matrix's rows and columns)
1-parameter solution =
vector of length one
the square root of (u1)^2+...+ (uk)^k
when it costs less then $1 in raw materials to make $1 worth of product
a matrix where all entries are non-negative and every column sums to one
when a linear system has an infinite number of solutions it has:
x vector =(x1,x2,...,xn) = Po vector + t times the v vector
2-parameter solution =
system of linear equations with one or more solutions
3-or more-parameter solution =
vector x = vector Po + t times vector v1 + s times vector v2
When vectors can be written as linear combinations of each other they are
If a set of vectors spans the vector space V and the set is linearly independent it is a
when one non-zero vector is a scalar multiple of another, these vectors are:
an extra variable that's added to an inequality to make the constraint an equality
A vector space W that is part of a larger vector space V
when you multiply this with a matrix it is like multiplying by one
A system is consistent if and only if the row rank of the coefficient matrix equals the row rank of the augmented matrix
Problem of maximizing or minimizing a linear function over a set of constraints
Vector Sn = T^n times vector So
using row operations to put a matrix into ref
vector v = c1v1+c2v2+...+ckvk for some scalars c1,
When no vector in S is a linear combination of the other vectors

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Created Dec 14, 2011ReportNominate
Tags:algebra, linear, review, ultimate