Confidence interval

Related lectures (32)

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

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

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

Covers the construction of approximate confidence intervals using the central limit theorem for large sample sizes.

Covers the properties and error estimates of the Monte Carlo method in stochastic simulation.

Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Covers the Upper Confidence Bound algorithm for multi-arm bandits.

Explores the linear regression model, OLS properties, hypothesis testing, interpretation, transformations, and practical considerations.

Explores interspike intervals, renewal processes, and escape noise experiments in neuronal dynamics.

Covers hypothesis testing, power, confidence intervals, and small sample considerations.

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

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

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