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Linear Algebra

  1. Vectors
    1. Scalars
    2. Vectors vs Sets
    3. Addition and Subtraction
    4. Scalar Multiplication
    5. Zero Vectors
    6. Linear Combinations
    7. Real Dot Product
    8. Length of a Vector
    9. Orthogonal Vectors
    10. Parallel Vectors
    11. Angle Between Vectors
    12. Unit Vectors
  2. Matrices
    1. Notation
    2. Indexing
    3. Submatrices
    4. Matrix-by-Vector Product
    5. Addition and Subtraction
    6. Scalar Multiplication
    7. Transpose
    8. Symmetries
    9. Matrix Multiplication
    10. Identity Matrix
    11. Non-Negative Integer Powers
    12. Reverse Order Law of Transposition
  3. Linear Systems
    1. Inverse Matrices
    2. Singular Matrices
    3. Linear Dependence
    4. Solutions
  4. Planes
    1. Vector Cross Product
  5. Gaussian Elimination
Linear Algebra ›Vectors ›Zero Vectors

Zero Vectors

There is a special kind of vector which I would like to mention - the so-called zero vector.

The zero vector is a vector whose components all equal 000. It is often denoted as 0⃗\vec{0}0 (the number zero with the little arrow on top).

A two-dimensional zero vector looks like this:

0⃗=[00].\vec{0} = \begin{bmatrix} 0 \\ 0 \end{bmatrix}.0=[00​].

The zero vector can be obtained by multiplying any vector by 000 (scalar multiplication), or by subtracting a vector from itself:

0v⃗=[0⋅v10⋅v2]=[00]=0⃗,0\vec{v} = \begin{bmatrix} 0 \cdot v_1 \\ 0 \cdot v_2 \end{bmatrix} = \begin{bmatrix} 0 \\ 0 \end{bmatrix} = \vec{0},0v=[0⋅v1​0⋅v2​​]=[00​]=0,

or

v⃗−v⃗=[v1−v1v2−v2]=[00]=0⃗.\vec{v} - \vec{v} = \begin{bmatrix} v_1 - v_1 \\ v_2 - v_2 \end{bmatrix} = \begin{bmatrix} 0 \\ 0 \end{bmatrix} = \vec{0}.v−v=[v1​−v1​v2​−v2​​]=[00​]=0.
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Multiplying a Vector by a Scalar
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Linear Combinations
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