You can write a vector in several ways, depending on the context and the level of detail needed. Here's a breakdown of common methods:
1. Using Component Form (Ordered Pairs/Triples)
This is a fundamental way to represent a vector. It expresses the vector in terms of its components along coordinate axes.
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2D Vector: A vector in two dimensions is represented as an ordered pair: (x, y), where x is the horizontal component and y is the vertical component. For instance, the vector (3, 4) represents a displacement of 3 units along the x-axis and 4 units along the y-axis.
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3D Vector: A vector in three dimensions is represented as an ordered triple: (x, y, z), where x, y, and z are the components along the x, y, and z axes, respectively. An example would be (1, -2, 5).
2. Using i, j, k Notation (Unit Vector Notation)
This method expresses a vector as a sum of scalar multiples of unit vectors.
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Unit Vectors: Unit vectors are vectors with a magnitude (length) of 1. In a Cartesian coordinate system, the unit vectors along the x, y, and z axes are denoted as i, j, and k, respectively.
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2D Vector: A 2D vector can be written as ai + bj, where a and b are scalar components along the x and y axes. For example, the vector (3, 4) can be written as 3i + 4j.
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3D Vector: A 3D vector is expressed as ai + bj + ck, where a, b, and c are scalar components along the x, y, and z axes. The vector (1, -2, 5) becomes 1i - 2j + 5k (or simply i - 2j + 5k).
3. Using Magnitude and Direction
You can define a vector by its magnitude (length) and direction (angle).
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2D Vector: You specify the magnitude r and the angle θ (theta) it makes with the positive x-axis. The components can then be found using trigonometry:
- x = r * cos(θ)
- y = r sin(θ)
Therefore, the vector is (r*cos(θ), r*sin(θ)) or (r*cos(θ))i + (r\sin(θ))j.
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3D Vector: Specifying a 3D vector using magnitude and direction is more complex, usually involving two angles (e.g., azimuth and elevation) or direction cosines.
4. As a Column or Row Matrix
Vectors can be written as column or row matrices, which is especially useful for linear algebra operations.
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Column Matrix:
[x] [y]
or
[x] [y] [z]
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Row Matrix:
[x y]
or
[x y z]
Summary Table
Representation | 2D Example | 3D Example | Description |
---|---|---|---|
Component Form | (3, 4) | (1, -2, 5) | Ordered pair/triple of components. |
i, j, k Notation | 3i + 4j | i - 2j + 5k | Sum of scalar multiples of unit vectors. |
Magnitude and Direction | r = 5, θ = 53.13° | (More Complex) | Magnitude (length) and angle(s) specifying the direction. |
Column Matrix | [3] [4] |
[1] [-2] [5] |
Matrix representation suitable for linear algebra. |
Row Matrix | [3 4] | [1 -2 5] | Matrix representation suitable for linear algebra. |
In essence, choosing how to write a vector depends on the specific application and the information you want to emphasize.