Linear Algebra Terms

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Can you name the Linear Algebra Ultimate Review?

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

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