Vector Magnitude Calculator
Calculation Result:
Understanding Vector Magnitude
In mathematics and physics, a vector is a quantity that has both magnitude and direction. The magnitude (also known as the length or norm) of a vector represents its size or the distance from its starting point to its endpoint. Calculating the magnitude is a fundamental operation in linear algebra, geometry, and engineering.
The Magnitude Formula
The calculation of a vector's magnitude is based on the Pythagorean theorem. For a vector v with components (x, y, z), the formula for magnitude is:
|v| = √(x² + y² + z²)
Step-by-Step Calculation Guide
- Identify the Components: Determine the individual coordinates of the vector along the X, Y, and (if applicable) Z axes.
- Square the Components: Multiply each component by itself (e.g., x * x, y * y).
- Sum the Squares: Add all the squared values together.
- Square Root: Take the square root of the final sum to find the magnitude.
Practical Examples
Example 1: 2D Vector
Vector A has components (3, 4).
|A| = √(3² + 4²) = √(9 + 16) = √25 = 5.
Vector A has components (3, 4).
|A| = √(3² + 4²) = √(9 + 16) = √25 = 5.
Example 2: 3D Vector
Vector B has components (2, 6, 9).
|B| = √(2² + 6² + 9²) = √(4 + 36 + 81) = √121 = 11.
Vector B has components (2, 6, 9).
|B| = √(2² + 6² + 9²) = √(4 + 36 + 81) = √121 = 11.
Why Is This Important?
Magnitude calculations are essential in various fields:
- Physics: Calculating the speed of an object (the magnitude of the velocity vector) or the total force acting on a body.
- Navigation: Determining the absolute distance between two points in space.
- Computer Graphics: Normalizing vectors to determine lighting, shading, and 3D positioning.
- Data Science: Measuring the similarity between vectors in machine learning algorithms (Cosine similarity).