Matrix and Linear Algebra Quiz

Linear equation = An equation of the form $ax + by = c$ Matrix = A rectangular array of numbers, symbols, or expressions arranged in rows and columns Vector = A quantity having direction and magnitude, especially as determining the position of one point in space relative to another Polynomial = An expression consisting of variables and coefficients, that involves only the operations of addition, subtraction, multiplication, and non-negative integer exponents of variables

System of linear equations = A collection of one or more linear equations involving the same set of variables Determinant = A scalar value that can be computed from the elements of a square matrix and encodes certain properties of the linear transformation described by the matrix Eigenvalue = A scalar that represents how a particular linear transformation behaves as a multiple of the identity transformation Transpose = An operation that flips a matrix over its diagonal

Matrix addition = The operation of adding two matrices by adding the corresponding entries together Matrix multiplication = The operation of multiplying two matrices to obtain a new matrix Matrix inversion = The process of finding a matrix that, when multiplied by the original matrix, gives the identity matrix Matrix transpose = The operation of switching the rows and columns of a matrix

Degree of a polynomial = The highest power of the variable in the polynomial Linear combination = A combination of vectors obtained by multiplying each vector by a scalar and adding the results Span of a set of vectors = The set of all possible linear combinations of the vectors in the set Eigenvector = A non-zero vector that only changes by a scalar factor when a given linear transformation is applied to it

Orthogonal vectors = Vectors that are perpendicular to each other Null space of a matrix = The set of all vectors that map to the zero vector under the given transformation described by the matrix Row space of a matrix = The set of all possible linear combinations of the rows of the matrix Column space of a matrix = The set of all possible linear combinations of the columns of the matrix

A linear equation in two variables is one that can be written in the form $ax + by = c$. An example of a linear equation in two variables is $2x + 3y = 6$.

An equation in n variables is said to be a linear equation if it can be written in the form $a_1x_1 + a_2x_2 + ... + a_nx_n = b$, where $a_i$ and $b$ are constants.

To solve for n variables, we typically require n equations.

The degree of a polynomial in the context of linear equations refers to the highest power of the variable in the equation. For a linear equation, the degree of the polynomial is 1.

A linear equation in one variable is an equation of the form $p(x) = 0$ where p is a degree one polynomial, in other words, a linear equation is one that can be written as $ax = b$.