Module 4 Flashcards
Covariance matrices are always…
Square (where m=n) and symmetric
Principal Component Analysis (PCA)
Way of organizing complex data into simplistic structures that order variance
Scatter plots reveal…
Correlation and covariance
Covariance
Measure in how variance and mean values between two or more locations are related to each other
Row vector
A matrix of a single row where m = 1
Column vector
A matrix of a single column where n = 1
What is a useful working definition of climate?
The average of weather over time
Climate is what you expect while weather…
Is what you get
Eigenvectors (e)
Special column vectors which remain unchanged when multiplied by a matrix, except that they are multiplied by a scalar, the eigenvalue
How to arrange eigenvectors
In order of decreasing eigenvalue
Total variance is the sum of the…
Eigenvalues
Eigenvectors of a covariance matrix are called…
Principal components
Principal components are useful…
For identifying climate signals
What kind of information do principal components provide?
How data co-varies at different locations
Empirical Orthogonal Fuctions (EOFs)
Analysis to study patterns of variability and how they change with time