Basis Calculator

Find bases of a vector space step by step

The calculator will find a basis of the space spanned by the set of given vectors, with steps shown.

Related calculators: Linear Independence Calculator, Matrix Rank Calculator

$$$\mathbf{\vec{v_{1}}}$$$ $$$\mathbf{\vec{v_{2}}}$$$ $$$\mathbf{\vec{v_{3}}}$$$

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The Basis Calculator is an advanced online resource specifically designed to find the basis of a vector space. The calculator aims to ease your mathematical journey by providing quick, precise, and correct results. Thus, it allows you to concentrate on the comprehension of concepts instead of diving into complicated calculations.

How to Use the Basis Calculator?

  • Input

    Input the vectors of the vector space in the fields provided.

  • Calculation

    Once you've input your data, simply click on the "Calculate" button.

  • Result

    The calculator will immediately compute and display the result, i.e., the basis of the vector space.

Understanding the Concept of Basis

In the realm of linear algebra, the notion of the basis of a vector space is an essential building block. The basis for a vector space is defined as a set of vectors that satisfy two key conditions:

  • They are linearly independent.
  • They span the entire vector space.

Being linearly independent implies that no vector in the set can be expressed as a linear combination of the others. In other words, there's no way to add or scale some vectors in the set to obtain another vector from the same set.

On the other hand, the property of spanning the vector space means that every vector in the space can be expressed as a linear combination of the basis vectors. In essence, the basis vectors form a "framework" that fills the entire vector space.

These two properties together mean that every vector in the space has a unique representation as a linear combination of the basis vectors.

Mathematically, if $$$\mathbf{\vec{v_1}},\mathbf{\vec{v_1}},\ldots,\mathbf{\vec{v_n}}$$$ form a basis for a vector space, any vector $$$\mathbf{\vec{v}}$$$ in the space can be written as


Here, $$$a_1,a_2,\ldots,a_n$$$ are scalars, and their values are uniquely determined for each vector $$$\mathbf{\vec{v}}$$$ in the space.

Let's consider a simple example in $$$\mathbb{R^2}$$$ (the 2D space of real numbers). The vectors $$$\mathbf{\vec{v_1}}=\langle1,0\rangle$$$ and $$$\mathbf{\vec{v_2}}=\langle0,1\rangle$$$ form a basis for this space. Any vector $$$\mathbf{\vec{v}}=\langle x,y\rangle$$$ in $$$\mathbb{R^2}$$$ can be written as the combination of $$$\mathbf{\vec{v_1}}$$$ and $$$\mathbf{\vec{v_2}}$$$, namely $$$\mathbf{\vec{v}}=x\mathbf{\vec{v_1}}+y\mathbf{\vec{v_2}}$$$.

The concept of a basis is fundamental to understanding many properties of vector spaces, and it plays a critical role in various mathematical disciplines, physics, engineering, computer science, and more.

Why Choose Our Basis Calculator?

  • User-Friendly Design

    With an intuitive interface, the calculator is easily accessible to both beginners and experienced users.

  • Fast Calculations

    Our calculator provides instant results, saving valuable time that manual computations would otherwise consume.

  • Accuracy

    The Basis Calculator guarantees precise results, removing the risk of errors that manual calculations may carry.

  • Versatility

    The basis calculator can handle different vectors.


Can I use the Basis Calculator for any vector?

The Basis Calculator is versatile and can handle different vectors. Whether you're dealing with a 2D, 3D, or higher dimensional space, this calculator is here to assist.

Why should I choose the Basis Calculator?

Our Basis Calculator is user-friendly, fast, and accurate, making it an ideal tool for anyone dealing with vector algebra. Whether you're a student, teacher, or professional, this calculator can be a great aid in your work or studies.

What is a basis in linear algebra?

In linear algebra, the basis of a vector space is a set of vectors that are linearly independent and span the entire vector space. This means every vector in the space can be expressed uniquely as a linear combination of the basis vectors.