Electric Cable Potential Analysis

Related lectures (29)

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Covers the basics of linear regression and how to solve estimation problems using least squares and matrix notation.

Covers linear regression for estimating train speed using least squares and regularization.

Explains the concept of least squares solutions and their application in finding the closest solution to a system of equations.

Explores linear regression using the method of least squares to fit data points with the equation y = ax + b.

Explores linear regression estimation, hypothesis testing, and practical applications in statistics.

Covers parametric estimation in time series analysis, including integrated processes and seasonal modeling.

Covers the Recursive Least-Squares algorithm with weighted formulation for real-time data updating.

Covers the fundamentals of statistics, exploring probabilistic models, variability, uncertainty, and data collection.

Explains least squares approximation for finding best fit lines or curves to data points.

Explores linear least squares, normal equations, and the importance of linear regression in minimizing errors.