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4 cards from this section. Quick, good the night before a test.
What happens to an eigenvector if it is multiplied by a scalar?
Think about if it stretches or shrinks.
If a matrix has 3 distinct eigenvalues, how many linearly independent eigenvectors will it have?
Remember the definition of distinct eigenvalues.
What does it mean if eigenvectors are linearly independent?
Recall the definition of linear independence.
True or False: All eigenvectors of symmetric matrices are complex.
Think about the properties of symmetric matrices.
Given a 3x3 real symmetric matrix, prove that its eigenvectors corresponding to distinct eigenvalues are orthogonal.
Apply the eigenvalue equation and manipulate using the symmetry property.
Consider a 4x4 matrix that has 4 distinct eigenvalues. How would you go about finding its eigenvectors? Discuss the method and implications for usage in scenarios such as structural analysis.
Remember to check for linear independence.
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