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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 โ€บVectors

Vectors - Introduction

In mathematics, you can think of vectors as an ordered list. Formally, this is not really correct, but for now, this definition will do.

You will not yet be able to understand the meaning of the following sentence, but at the end of the whole course, you hopefully will

A vector is an element of a vector space.

The notation for vectors is

vโƒ—=[v1v2]. \vec{v} = \begin{bmatrix} v_1 \\ v_2 \end{bmatrix}.v=[v1โ€‹v2โ€‹โ€‹].

As shown in the example, to denote vectors, conventionally a lowercase letter with a small arrow on top of it is used. Often, instead of brackets, parentheses may be used. This is especially common in pure mathematics and is totally valid notation:

vโƒ—=(v1v2). \vec{v} = \begin{pmatrix} v_1 \\ v_2 \end{pmatrix}.v=(v1โ€‹v2โ€‹โ€‹).

In engineering and related fields, square brackets are usually preferred. I will be using square brackets in this course, but keep in mind that parentheses are just as valid.

In the example above, we have a so-called โ€œtwo-dimensionalโ€ vector vโƒ—\vec{v}v, where v1v_1v1โ€‹ is the first component of vโƒ—\vec{v}v and v2v_2v2โ€‹ is the second component of vโƒ—\vec{v}v.

Now consider a vector vโƒ—\vec{v}v defined as

vโƒ—=[23]. \vec{v} = \begin{bmatrix} 2 \\ 3 \end{bmatrix}.v=[23โ€‹].

Such a vector can also be represented graphically as an arrow in a coordinate system. Typically with the arrow starting at the origin (0,0)(0,0)(0,0), and ending at the point corresponding to the vector components - in this case (2,3)(2,3)(2,3).

The vector vโƒ—\vec{v}v above can be drawn as follows:

Similarly, a three-dimensional vector can be represented in a three-dimensional coordinate system. Four dimensional vectors can also graphically be thought of as these โ€œarrows in some four-dimensional spaceโ€, but since we canโ€™t draw such a space, let alone imagine it, we have to stick to 2D and 3D for the graphical representation.

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