Requirements
- Statistics
- Matrices
- Series
Useful, Self-Contained Class
" One of the most useful courses I have ever taken." Students with basic knowledge of statistics, linear algebra and Fourier Series will have the background necessary for the course, but an effort is made to introduce these concepts so that the course is self-contained for a sufficiently motivated student.
Linear Algebra.
" Matrix maniptulations and systems of linear equations form the foundation for many of the methods uses."Regression, Empirical Orthogonal Functions, Maximum Covariance Analysis and many more techniques depend on linear algebra and concepts like the eigenvalue problem, singular value decomposition, and other operations on matrices.
Orthogonal Functions
" Fourier series and other orthogonal basis sets form the foundation of spectral analysis and filtering of time and space series.Fourier series, a series in sines and cosines, is optimal in a root-mean-square sense and hits the midpoint at discontinuities. Complex variables are an efficient way to deal with these subjects.
accessible & Applicable
Learning by doing.
