Transforming Vectors: Real-Life Examples Beyond Inclined Planes

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SUMMARY

Transforming vectors from a normal basis (xyz axes) to alternative bases is essential in various real-life applications beyond inclined planes. Key examples include changing reference frames for aircraft, adjusting measurements across different locations, and utilizing different units of measurement with scaling factors. Additionally, fields like acoustics, projectile motion, economics, and Galois theory demonstrate the necessity of basis transformations. Linear algebra serves as a powerful tool across diverse disciplines, including ballistics, statistics, and signal processing.

PREREQUISITES
  • Understanding of vector transformation and basis change
  • Familiarity with coordinate systems (rectangular and polar)
  • Basic knowledge of linear algebra concepts
  • Awareness of applications in fields like economics and acoustics
NEXT STEPS
  • Study vector transformations in different coordinate systems
  • Explore applications of linear algebra in economics and statistics
  • Learn about basis transformations in Galois theory
  • Investigate the role of linear algebra in signal processing and acoustics
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Students and professionals in mathematics, physics, engineering, economics, and data science who seek to understand the practical applications of vector transformations and linear algebra in various fields.

matqkks
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Why would we want to transform a vector in our normal basis (xyz axes) to another basis? The only situation I can recall is when we are looking at a force applied on an inclined plane. Are there any other real life examples where this may be necessary?
 
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matqkks said:
Why would we want to transform a vector in our normal basis (xyz axes) to another basis? The only situation I can recall is when we are looking at a force applied on an inclined plane. Are there any other real life examples where this may be necessary?

When you wish to charge reference frames. For instance you may want to change from the natural reference frame for an aircraft (x along the aircraft axis, y in the plane of the floor to the right, and z in the direction of the cabin roof) to an Earth base axis system.

CB
 
to expand on CaptainBlack's example, one may take physical measurements in 2 different locations. a different "origin" (reference point) may be used at each location (instead of a common reference point like the greenwich observatory).

or one may simply use different units of measurement, resulting in the need for "scaling factors" in the unit vectors.

in the world of acoustics, one may have different oscillators (or circuits) one uses for generating (or processing) sound. so different settings may be required to produce a (nearly identical) sound on differing pieces of equipment.

for studying some kinds of motion (like projectiles) a rectangular coordinate system may be the most convenient, for studying other kinds (like orbits), a polar system may work better. we need to know how to go "back and forth" between the two.

in economics we may note that different economic quantities may vary linearly (or can be approximated linearly), and be linearly independent. depending on what you want to DO with this information, you may want to consider each quantity as a "basis element" or you may want to consider "aggregates" (perhaps prices as a linear combination of various cost factors) instead as a basis (for determining a suitable price index in a certain industry, perhaps).

in field (galois) theory, it may be "natural" to consider two different bases for the same space. for example, it turns out that the field generated by a (primitive) 3rd root of unity over the rationals is the same field generated by a (primitive) 6th root of unity. if we call the 3rd root w, and the 6th root u, we have:

w = u2 or 1/u2

u = -1/w or -w

which means that either the basis {1,u} or {1,w} can be used when dealing with this field.

for more complicated vector spaces, such as the vector spaces of all continuous functions defined on a real interval [a,b], there may be no natural "standard" basis. so depending on which functions in this vector space you are studying (exponentials, polynomials, etc.) certain bases may be more convenient to work with. a fact proved in one basis may indeed "transfer" to another basis, but to do so, you might need "the change of basis" transformation (usually, for large vector spaces such as this one, describing such a transformation by a matrix is not feasible).

the point i want to get across is that linear algebra applies to "much more" than just "euclidean 3-space" (the normal xyz-system you are accustomed to). it's a very useful tool for many areas (ballistics, economics, statistics, manufacturing optimization, signal processing, cryptography, it's a long list...) that we wouldn't normally conceive of as "spaces" (in the geometric sense).
 

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