Concepts of Eigenvectors/values

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The discussion highlights frustrations with a Differential Equations/Linear Algebra class that fails to cover essential topics like linear transformations and diagonalization, impacting students' understanding of eigenvalues and eigenvectors. A participant seeks clarification on whether switching rows in a matrix affects the calculation of eigenvectors, confirming that row operations do not change the solution space. The conversation also addresses the common occurrence of eigenvectors having rows of zeros, suggesting that this may relate to the nature of eigenvectors being able to be "stretched" along their line. Overall, the thread emphasizes the challenges of learning these concepts in a combined course format. Understanding these foundational aspects is crucial for mastering eigenvalues and eigenvectors.
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Just a small rant to start. My DE/LA class is absolute nonsense. I am really wishing that I taken each class separate because this class is making me and many others lose the big picture. For instance, this class doesn't teach linear transformations and diagonalization both of which I keep seeing anytime I look up stuff about eigens. I've managed to learn some of these on my own but I can't spend too much time on that stuff for now.

Anyway, after I find the eigenvalues am I allowed to do any switch rows to find the eigenvectors? Or do I have to account for the switching of a row in the eigenvector? Most of the matrices that are produced from plugging in the eigenvalues have some strange configurations, usually they have a ton of zeros and not what I'm used to. Thanks for any help.
 
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i'm not sure what you mean by "switching the rows".

what i WILL say, is that if a matrix A models a set of linear equations, changing the order of the rows amounts to changing the order that the equations are written in, and does not change the solution space.
 
Once you have an eigenvalue, \lambda, for linear transformation, A, you find the eigenvectors by solving the equation Ax= \lambda x for x. IF you choose to use "row-reduction" to solve that equation, yes, you can use any row operations you wish to solve it.
 
Deveno said:
i'm not sure what you mean by "switching the rows".

what i WILL say, is that if a matrix A models a set of linear equations, changing the order of the rows amounts to changing the order that the equations are written in, and does not change the solution space.

Yeah that's I mean about switching the rows. That clears up that question.

Now, another question is why does every eigenvector I'm trying to find always seem to have an entire row of zeros? Is it because the eigenvector is capable of being "stretched" on it's line?
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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