
Eigenvalues and Determinants Concepts
Interactive Video
•
Mathematics
•
10th - 12th Grade
•
Hard
Standards-aligned
Aiden Montgomery
FREE Resource
Standards-aligned
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10 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main challenge when finding eigenvalues for a 3x3 matrix compared to a 2x2 matrix?
The determinant is always zero.
The eigenvalues are always complex numbers.
The matrix is larger, making calculations more complex.
The eigenvectors are not unique.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is true about an eigenvalue λ of a matrix A?
A times a non-zero vector equals λ times the same non-zero vector.
A times a zero vector equals λ times the zero vector.
A times a non-zero vector equals zero.
A times any vector equals λ times the identity matrix.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the condition for λ to be an eigenvalue of matrix A?
The determinant of λ times the identity matrix plus A is zero.
The determinant of λ times the identity matrix minus A is zero.
The determinant of A is non-zero.
The determinant of A is equal to λ.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What method is used to find the determinant of the matrix in the video?
Gaussian Elimination
Laplace Expansion
Rule of Sarrus
Cramer's Rule
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the characteristic polynomial of a matrix?
A polynomial whose roots are the eigenvectors of the matrix.
A polynomial whose roots are the eigenvalues of the matrix.
A polynomial that represents the trace of the matrix.
A polynomial that represents the inverse of the matrix.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the first step in simplifying the determinant expression?
Setting the determinant equal to zero.
Using the rule of Sarrus to find the determinant.
Factoring out common terms.
Expanding the determinant using cofactor expansion.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the significance of finding a zero for the characteristic polynomial?
It indicates a solution for the eigenvectors.
It identifies a potential eigenvalue.
It confirms the matrix is invertible.
It shows the matrix is singular.
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