Related lectures (32)
Heavy-Tailed Distributions
Explores heavy-tailed distributions, the Hill estimator, convergence to Gaussian, and distribution comparison.
Descriptive Statistics: Hypothesis Testing
Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.
Big Data Challenges: Scaling to Massive Data
Explores challenges of handling massive data in the era of big data, discussing solutions like MapReduce and Spark.
Renormalization & Scaling
Explores renormalization, scaling, critical points, exponents, and phase transitions in conformal field theory and quantum gravity.
Describing Data: Statistics & Uncertainty
Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.
Rheological Measurements: Newtonian Fluid and Non-Newtonian Fluids
Covers rheological measurements of Newtonian and non-Newtonian fluids.
Scaling Laws in Micro & Nanosystems
Explores scaling laws in micro and nanosystems, covering density, motion, electrostatic force, frequency control, and thermal vs mechanical energy.
Critical Exponents: Theory and Applications
Explores the derivation of critical exponents and the scaling laws in phase diagrams.
Pointed Mapping Spaces: Exponential Law and Adjunction
Explores pointed mapping spaces, the exponential law, adjunction properties, and homotopic classes.
Optimal Transport: Gradient Flows in Rd
Explores optimal transport and gradient flows in Rd, emphasizing convergence and the role of Lipschitz and Picard-Lindelöf theorems.

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