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Related lectures (32)
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Distribution Estimation
Covers the estimation of distributions using various methods such as minimum loss and expectation.
Convergence Criteria: Richardson Method
Covers the Richardson method for solving linear systems and convergence criteria.
Geometry and Least Squares
Discusses the geometry of least squares, exploring row and column perspectives, hyperplanes, projections, residuals, and unique vectors.
Stability: Poles, Zeros, and Control
Covers stability, poles, zeros, and control in dynamic systems, emphasizing the importance of observability.
Experimental Design: Strategies and Analysis
Discusses experimental design strategies, factors, responses, treatment combinations, and degrees of freedom.
Linear Regression
Covers linear regression for estimating train speed using least squares and regularization.
Model Diagnostics: Outliers, Leverage, and Influential Observations
Explores outliers, leverage, and influential observations in statistical models, including methods for detection and assessment.
Linear Regression: Understanding Quantitative Relationships
Covers linear regression, from developing research questions to interpreting R-squared and adding predictors to improve the model.
Polynomial Optimization: SOS and Nonnegative Polynomials
Explores polynomial optimization, emphasizing SOS and nonnegative polynomials, including the representation of polynomials as quadratic functions of monomials.
Linear Regression: Model Adjustment and Parameter Estimation
Explains the decomposition of total sum of squares, model adjustment, and parameter estimation in linear regression.
Generalized Additive Models: Penalized Iterative Weighted Least Squares
Covers the introduction to generalized additive models and iterative weighted least squares for model checking and smooth fits.
DOE Qualitative factors III
Explores qualitative factors in Design of Experiments, including Latin squares, factorial designs, and ANOVA tables.
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