Types of Matrices
This lesson describes a few of the more important types of matrices:
transpose matrices, vectors, and different kinds of square matrices.
Transpose Matrix
The transpose of one matrix is another matrix that is obtained by using
by using rows from the first matrix as columns in the second matrix.
For example, it is easy to see that the transpose of matrix A is
A'. Row 1 of matrix A becomes column 1 of
A'; row 2 of A becomes column 2 of
A'; and row 3 of A becomes column 3 of
A'.
Note that the
order
of a matrix is reversed after it has been transposed. Matrix
A is a 3 x 2 matrix, but matrix A'
is a 2 x 3 matrix.
With respect to notation, this website uses a prime to indicate a
transpose. Thus, the transpose of matrix B would be
written as B'.
Vectors
Vectors are a type of matrix having only one column or one
row.
Vectors come in two flavors: column vectors and
row vectors. For example, matrix a
is a column vector, and matrix a' is a row vector.
We use lowercase, boldface letters to represent column vectors. And since the
transpose of a column vector is a row vector, we use lowercase,
boldface letters plus a prime to represent row vectors.
Thus, vector b
would be a column vector, and vector b' would be a
row vector.
Square Matrices
A square matrix is an n x n matrix; that is,
a matrix with the same number of rows as columns. In this section, we describe
several special kinds of square matrix.

Symmetric matrix. If the transpose of a matrix is equal
to itself, that matrix is said to be symmetric. Two examples of
symmetric matrices appear below.
Note that each of these matrices satisfy the defining requirement of a
symmetric matrix: A = A' and
B = B'.

Diagonal matrix. A diagonal matrix is a special kind
of symmetric matrix. It is a symmetric matrix with zeros in the
offdiagonal elements. Two diagonal matrices are shown below.
Note that the diagonal of a matrix refers to the elements
that run from the upper left corner to the lower right corner.

Scalar matrix. A scalar matrix is a special kind of
diagonal matrix. It is a diagonal matrix with equalvalued elements
along the diagonal. Two examples of a scalar matrix appear below.
These square matrices play a prominent role in the application of matrix
algebra to realworld problems.
For example, a scalar matrix called the
identity matrix
is critical to the solution of simultaneous linear equations. (We cover
the identity matrix later in the tutorial.)
Test Your Understanding
Problem 1
Consider the matrices shown below  a, A,
B, and C
Which of the following statements are true?
I. a is a row matrix
II. A = B'
III. C is a symmetric matrix
(A) I and II
(B) I and III
(C) II and III
(D) None of the above
(E) All of the above
Solution
The correct answer is (C), as explained below.
 Matrix a is a column vector, not a row matrix
 The transpose of a matrix is created by interchanging corresponding
rows and columns. When this is done to matrix B,
we see that A = B'.
 The transpose of C is equal to C;
that is C = C'. Therefore,
C is a symmetric matrix.
Note that the offdiagonal elements of matrix C are equal
to zero; so matrix C is a diagonal matrix, which is a special kind of
symmetric matrix.