What exactly is a vector in and 5-D and more dimensions?

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SUMMARY

A vector in ℝ^n, where n exceeds three, can be understood as a mathematical object that represents both position and orientation in high-dimensional space. For example, to accurately describe an airplane's position and orientation, six dimensions are necessary: three for spatial coordinates and three for rotational parameters (roll, pitch, yaw). While vectors can be represented as rows of numbers (n-tuples), they possess a more complex structure that conveys significant information beyond mere numerical representation. Understanding high-dimensional vectors is essential in fields such as neuroscience and data analysis.

PREREQUISITES
  • Understanding of basic vector concepts in ℝ^2 and ℝ^3
  • Familiarity with n-dimensional spaces and their properties
  • Knowledge of vector operations and structures
  • Basic principles of data representation in high-dimensional contexts
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  • Explore the concept of high-dimensional spheres and cubes for visual representation
  • Study the mathematical properties of n-tuples and their applications
  • Learn about vector operations in higher dimensions, such as dot product and cross product
  • Investigate the role of high-dimensional vectors in machine learning and data analysis
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Mathematicians, data scientists, engineers, and anyone interested in understanding high-dimensional data representation and its applications in various fields.

mahrap
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I'm having a hard time grasping the concept of a vector geometrically. A vector in $$ℝ^2$$ is a line going in the direction specified from the terms. A vector in $$ℝ^3$$ is similary just a line going in the direction specified by the terms. But what exactly is a vector in $$ℝ^n$$ where n is greater than 3? Is there even a way to geometrically represent these vectors? Or should I just view them as rows of numbers and leave it at that?
 
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At first, it may seem that going beyond three dimensions is pointless, because many might think that if we want to describe something in our concrete physical world, certainly three dimensions (or possibly four dimensions if we consider time) will be enough. But in reality, it isn't. I often run into high dimensional vectors in neuroscience, and there are many other examples where records of data sets can be represented by high-dimensional vectors in high-dimensional space, for example the position of an airplane in space (it's a well-known example): one would think that it would take three dimensions to do that, one each to specify the x-coordinate, y-coordinate, and the z-coordinate of the airplane. Although it is correct that one needs only three dimensions to specify, for example, the center (or any given point) of the airplane, it is however important to note that the airplane could "rotate". In fact, it can rotate in three different directions, such as the roll, the pitch, and the yaw. Consequently, we would need six dimensions to specify the precise position of the airplane: three to specify the location of the center (or any given point) of the airplane and three other to specify the direction in which the airplane is pointing. Your vector representing the position of the airplane would then be in six dimensions.

In fact, you can view them as "rows of numbers", but they could mean something. They could physically represent something, even if it's hard to visualize. For visual representation of n-dimensional spaces, you could search about high-dimensional spheres and cubes and consider the representation of their vertices.
 
mahrap said:
Or should I just view them as rows of numbers and leave it at that?

Rows of numbers with specific operations. A "row of numbers" is an n-tuple. Vectors have more structure than that.
 

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