Lectures related to Battery System Operation

Statistical Inference: Approximate Critical Values and Confidence Intervals

Covers the construction of confidence intervals and approximate critical values in statistical inference.

Delves into the duality between confidence intervals and hypothesis tests, emphasizing the importance of precision and accuracy in estimation.

Interval Estimation

Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Power Management in Embedded Systems

Delves into power management in embedded systems, covering batteries, costs, and alternative solutions with practical examples.

Confidence Intervals: Student, Asymptotic Wald

Covers confidence intervals for Gaussian means, Student distribution, and Wald confidence intervals for maximum likelihood estimators.

Bivariate Data Analysis: Correlation and Regression

Explores bivariate data analysis, correlation, and regression techniques for model assessment.

Applied Biostatistics: Bivariate Data Analysis

Explores bivariate data analysis in applied biostatistics, covering correlation, regression, model selection, and diagnostics.

Assessing Significance and Fit

Covers confidence intervals, R2, and examples on cement heat evolution and car horsepower-MPG relationships.

Distribution Theory of Least Squares

Explores the distribution theory of least squares estimators in a Gaussian linear model, focusing on precision and confidence intervals construction.

Stochastic Simulation: Computation and Estimation

Covers computation and estimation in stochastic simulation, focusing on generating iid replicas and optimal importance sampling.

Interval Estimation: Method of Moments

Covers the method of moments for estimating parameters and constructing confidence intervals based on empirical moments matching distribution moments.

Ancillary Services from Active Distribution Networks

Covers the provision of multiple ancillary services from active distribution networks using a flexible asset.

Statistical Theory: Inference and Optimality

Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.

Soot Formation in Gas Fuels

Explores soot formation in gas fuels, emissions from gasoline and diesel, energy density of battery systems, and global carbon emissions.

Confidence Intervals: Margins, Coverage, Pivots

Explains margins of error, coverage, and pivots in constructing confidence intervals for scalar parameters.

Confidence Interval for Bernoulli Model Score

Explains how to calculate the confidence interval for the score parameter in the Bernoulli model.

Basic Concepts of Statistics: Weighing Three Objects

Covers basic statistics concepts, confidence intervals, t distribution, and experimental study strategies.

Numerical Simulation of SDEs: Monte Carlo & Optimal Control

Covers Monte Carlo methods, variance reduction, and stochastic optimal control, exploring simulation techniques, efficiency, and investment dynamics.

Variance Reduction Techniques

Covers variance reduction techniques in stochastic simulation to improve output quantity estimation accuracy.

Confidence Intervals: Gaussian Estimation

Explores confidence intervals, Gaussian estimation, Cramér-Rao inequality, and Maximum Likelihood Estimators.