Master's in Mechanical Engineering Structure

Related lectures (28)

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Covers the coordination of physics assistantship for electromagnetism course.

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

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Explores scale-free networks, power laws, preferential attachment, and network assortativity.

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Explores copulas for measuring dependence strength in distributions and transforming variables to unit Fréchet margins.

Explores epidemics in network data, covering SIR model, basic reproductive ratio, percolation, directed networks, and maximum likelihood estimation.

Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.