Back to Symmetric matrices and variance

Exercise 7

Avg difficulty 2.5

Suppose that CC is the covariance matrix of a demeaned dataset.

  1. Suppose that u\uvec is an eigenvector of CC with associated eigenvalue λ\lambda and that u\uvec has unit length. Explain why Vu=λV_{\uvec} = \lambda.

  2. Suppose that the covariance matrix of a demeaned dataset can be written as C=QDQTC=QDQ^T where Q=[u1u2],D=[10000].Q = \begin{bmatrix} \uvec_1 & \uvec_2 \end{bmatrix}, \hspace{24pt} D = \begin{bmatrix} 10 & 0 \\ 0 & 0 \\ \end{bmatrix}. What is Vu2V_{\uvec_2}? What does this tell you about the demeaned data?

  3. Explain why the total variance of a dataset equals the sum of the eigenvalues of the covariance matrix.

Austin, Understanding Linear Algebra, §7.1 Symmetric matrices and variance, Exercise 7

AI Tutor

Adapted from Understanding Linear Algebra © 2023 David Austin. Licensed under CC BY 4.0. Source: Understanding Linear Algebra. Imported at revision 3e6dced.