Eigenvalues: Definition, Properties & Examples


Choose an answer and hit 'next'. You will receive your score and answers at the end.

question 1 of 3

When a matrix multiplies one of its eigenvectors, the eigenvector gets scaled by the associated _____.

Start Your Free Trial To Take This Quiz

As a member, you'll also get unlimited access to over 75,000 lessons in math, English, science, history, and more. Plus, get practice tests, quizzes, and personalized coaching to help you succeed.

Free 5-day trial
It only takes a few minutes to set up and you can cancel at any time.
Already registered? Login here for access

1. Setting the determinant of A - λI to zero gives us what equation?

2. The sum of the diagonal elements of a matrix is called the _____.

Start your free trial to access this entire page
A premium account gives you access to all lesson, practice exams, quizzes & worksheets
Access to all video lessons
Quizzes, practice exams & worksheets
Certificate of Completion
Access to instructors
Create an account to get started Create Account

About This Quiz & Worksheet

See what you know about eigenvalues by completing this quiz and worksheet. The quiz focuses on eigenvectors and related terminology from the lesson.

Quiz & Worksheet Goals

The assessment will test your knowledge of:

  • The name of the sum of a matrix's diagonal elements
  • What a matrix doesn't have if the determinant is zero
  • The resulting equation when setting a given determinant to zero

Skills Practiced

  • Information recall - access the knowledge you've gained regarding what the product of the eigenvalues of a matrix is equivalent to
  • Reading comprehension - ensure that you draw the most important information from the lesson on eigenvalues
  • Knowledge application - use your knowledge to answer a question regarding what an eigenvector gets scaled by when a matrix multiplies one of its engenvectors

Additional Learning

Eigenvalues: Definition, Properties & Examples is a lesson that teachers you about eigenvalues. The objectives covered include:

  • Review the parts of matrices
  • Know what a column vector is
  • Understand how to find eigenvalues