12.012 MatLab, Statistics, Regression, Signal Processing

Class Info

Introduces the basic tools needed for data analysis and interpretation in the Geosciences, as well as other sciences. Composed of four modules, targeted at introducing students to the basic concepts and applications in each module. MatLab: Principles and practice in its uses, script and function modules, basic approaches to solving problems. Statistics: Correlation, means, dispersion, precision, accuracy, distributions, central limit theorem, skewness, probability, Chi-Square, Gaussian and other common distributions used in hypothesis testing. Regression: Random and grid search methods, basic least squares and algorithms applicable to regression, inversion and parameter estimation. Signal Processing: Analog and digital signals, Z-transform, Fourier series, fast Fourier transforms, spectral analysis leakage and bias, digital filtering. Students taking the graduate version complete different assignments.

This class has 18.06 as a corequisite.

12.012 will be offered this semester (Fall 2017). It is instructed by F. D. Morgan, T. A. Herring and S. Ravela.

Lecture occurs 11:00 AM to 12:30 PM on Tuesdays and Thursdays in 54-824.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+12.012&btnG=Google+Search&inurl=https site or on the 12.012 Stellar site.

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