Linear algebra multiple choice

In summary, the conversation discusses properties of symmetric matrices, rotations of the Euclidean plane, and similar matrices. It also covers the concepts of eigenvalues and eigenvectors and their relationship to linear operators. The summary concludes with a true or false statement for each of the ten statements discussed.
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underacheiver
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Homework Statement


1. If A is a real symmetric matrix, then there is a diagonal matrix D and an orthogonal matrix P so that D = P T AP.
a. True
b. False

2. Given that λi and λj are distinct eigenvalues of the real symmetric matrix A and that v1 and v2 are the respective eigenvectors associates with these values, then v1 and v2 are orthogonal.
a. True
b. False

3.If T(θ) is a rotation of the Euclidean plane 2 counterclockwise through an angle θ, then T can be represented by an orthogonal matrix P whose eigenvalues are λ1 = 1 and λ2 = -1.
a. True
b. False

4. If A and B represent the same linear operator T: U → U, then they have the same eigenvalues.
a. True
b. False

5. If A and B represent the same linear operator T: U → U, then they have the same eigenvectors.
a. True
b. False

6. If A and B have the same eigenvalues, then they are similar matrices.
a. True
b. False

7. Which of the following statements is not true?
a. Similar matrices A and B have exactly the same determinant.
b. Similar matrices A and B have exactly the same eigenvalues.
c. Similar matrices A and B have the same characteristic polynomial.
d. Similar matrices A and B have exactly the same eigenvectors.
e. none of the above

8. Let the n × n matrix A have eigenvalues λ1, λ2 ... λn (not necessarily distinct). Then det(A) = λ1λ2 ... λn.
a. True
b. False

9. Every real matrix A with eigenvalues as in problem 8 is similar to the diagonal matrix D = diag [λ1, λ2, ... λn].
a. True
b. False

10. Eigenvectors corresponding to distinct eigenvalues for any n × n matrix A are always linearly independent.
a. True
b. False

Homework Equations


The Attempt at a Solution


1. b
2. a
3. a
4. a
5. b
6. b
7. d
8. a
9. b
10. a
 

Related to Linear algebra multiple choice

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with linear equations and their representations in vector spaces. It involves studying the properties and operations of vectors and matrices.

2. What are the applications of linear algebra?

Linear algebra has numerous applications in fields such as physics, engineering, computer science, and economics. It is used to solve systems of equations, analyze data, and model real-world problems.

3. What is a vector in linear algebra?

A vector in linear algebra is a mathematical object that has both magnitude and direction. It is represented by an array of numbers and can be used to represent physical quantities such as velocity and force.

4. What is a matrix in linear algebra?

A matrix in linear algebra is a rectangular array of numbers arranged in rows and columns. It is used to represent systems of linear equations and perform operations such as addition, subtraction, and multiplication.

5. What are eigenvalues and eigenvectors in linear algebra?

Eigenvalues and eigenvectors are important concepts in linear algebra. Eigenvalues are scalars that represent the amount by which an eigenvector is stretched or compressed by a linear transformation. Eigenvectors are non-zero vectors that remain parallel to their original direction after a linear transformation.

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