Matrices: Definition
A rectangular array of numbers with m rows and n columns.
Key idea
A rectangular array of numbers with m rows and n columns.
In depth
A matrix is a rectangular array of numbers with m rows and n columns (m × n). It stores data, systems of equations, or a linear transformation. Entry aᵢⱼ is in row i, column j.
Worked example
[1 2 3; 4 5 6] is a 2 × 3 matrix; a₂₃ = 6.
Formula
Real-world uses
- Storing tables of data such as exam marks by student and subject in spreadsheets and code
Common mistake
Mixing up the row and column indices.
How to learn this
- Read the key idea and say it in your own words.
- Work through the worked example, then try a similar problem.
- Use the interactive lesson’s visual and mini-quiz to check the pattern.
Frequently asked questions
What is Matrices: Definition?
A rectangular array of numbers with m rows and n columns. It is a topic at the intermediate level in Linear Algebra.
What is the formula for Matrices: Definition?
The key formula is A = [aᵢⱼ].
Where is Matrices: Definition used in real life?
Real-world examples: Storing tables of data such as exam marks by student and subject in spreadsheets and code.
What should I learn before Matrices: Definition?
Make sure you are comfortable with Lines and Planes in Vector Form, the previous topic in Linear Algebra.
What is a common mistake with Matrices: Definition?
Mixing up the row and column indices.
How can I practise Matrices: Definition?
Open the interactive lesson, play with the visual, then answer the three-question mini-quiz. Getting two right marks the topic complete.
What comes after Matrices: Definition?
Move on to Matrix Addition and Scaling next.
Related intermediate topics in Linear Algebra
- Scalars and Vectors – A scalar is a number; a vector has magnitude and direction.
- Vector Notation and Components – Write vectors as ordered lists of coordinates.
- Vector Addition – Add component-wise; geometrically tip-to-tail.
- Scalar Multiplication – Scale a vector’s length.
- Vector Magnitude – Length of a vector.
- Unit Vectors – Vectors of length 1, found by normalising.