Now that we’ve learned about vector quantities, we can expand upon those lessons and focus on matrices. A matrix is a quantity with m rows and n columns of data. For example, we can combine multiple vectors into a matrix where each column of that matrix is one of the vectors.
To the right, you can see a comparison between scalars, vectors, and matrices for context.
We can also think of vectors as single-column matrices in their own right. Matrices are helpful because they allow us to perform operations on large amounts of data, such as representing entire systems of equations in a single matrix quantity.
Matrices can be represented by using square brackets that enclose the rows and columns of data (elements). The shape of a matrix is said to be mxn, where there are m rows and n columns. When representing matrices as a variable, we denote the matrix with a capital letter and a particular matrix element as the matrix variable with an “m,n” determined by the element’s location. Let’s look at an example of this. Consider the matrix below.
The value corresponding to the first row and second column is b.
What is the value corresponding to the second row and third column?