What is an eigenvalue in the context of matrices?

Eigenvalues and Characteristic Equations

Interactive Video
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Mathematics
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10th - 12th Grade
•
Hard

Amelia Wright
FREE Resource
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A polynomial of degree n
A matrix that is invertible
A scalar that satisfies a specific determinant equation
A vector that is multiplied by a matrix
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which equation must be satisfied for a number to be considered an eigenvalue of a matrix?
The matrix must be symmetric
The determinant of the matrix must be zero
The matrix must be diagonalizable
The determinant of the matrix minus lambda times the identity matrix must be zero
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the relationship between a matrix, a vector, and an eigenvalue?
The matrix is a scalar multiple of the vector
The vector is a scalar multiple of the eigenvalue
The matrix times the vector equals the eigenvalue times the vector
The eigenvalue is a scalar multiple of the matrix
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the characteristic polynomial of a matrix?
A polynomial that is always quadratic
A polynomial that represents the trace of the matrix
A polynomial in lambda that results from the determinant equation
A polynomial that represents the inverse of the matrix
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the characteristic equation in finding eigenvalues?
To find the eigenvalues of a matrix
To find the eigenvectors of a matrix
To calculate the determinant of a matrix
To determine if a matrix is invertible
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the example, what is the first step in calculating the eigenvalues of a 2x2 matrix?
Finding the inverse of the matrix
Setting up the determinant equation
Solving a linear equation
Calculating the trace of the matrix
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the determinant of a 2x2 matrix used for in this context?
To determine if the matrix is symmetric
To solve for eigenvalues
To calculate the eigenvectors
To find the inverse of the matrix
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