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Related lectures (32)

Confidence Intervals and MLE Limit Theorems

Explores constructing confidence intervals and MLE limit theorems for large samples.

Introduction to Financial Markets and Time Series

Introduces financial markets, time series, machine learning applications in finance, and natural language processing.

Stochastic Simulation: Low-Discrepancy Point Sets

Explores low-discrepancy point sets in stochastic simulation and their construction algorithms.

VaR Model Evaluation

Discusses Monte Carlo VaR accuracy, confidence intervals, backtesting, and multivariate distributions.

Describing Data: Statistics & Uncertainty

Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.

Describing Data: Statistics and Hypothesis Testing

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Battery System Operation

Explores a framework for scheduling a battery system to provide multiple ancillary services to the grid efficiently.

Uncertainty and Significant Figures

Explains confidence intervals, margin of error, pivots, and significant figures in statistical estimation.

Estimation Methods in Probability and Statistics

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Estimators and Confidence Intervals

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Error Estimation in LHS

Covers error estimation in Latin Hypercube Sampling, emphasizing the importance of accurate variance estimation.

Applied Biostatistics: Bivariate Data and Regression Analysis

Covers bivariate data analysis, correlation, and regression techniques, including interpretation of coefficients and least squares geometry.

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