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Unbiased estimation of standard deviation
Formal sciences
Statistics
Statistical inference
Mathematical statistics
Related lectures (32)
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Random Variables: Deterministic vs. Random
Explores random variables, their variability, realization of random processes, and the scientific method in material science.
Linear Algebra in Data Science
Explores the application of linear algebra in data science, covering variance reduction, model distribution theory, and maximum likelihood estimates.
Numpy: Broadcasting, Operations, Comparisons, and Constants
Covers broadcasting, operations, comparisons, and numpy constants like pi, e, and infinity.
Probability Theory: Random Variables and Distributions
Introduces probability theory, random variables, and distributions, with a focus on their applications in atomic diffusion.
Statistics and visualisation of morphometric data
Covers statistical analysis and visualization of morphometric data, including discrimination between tree types and numpy calculations.
Stochastic Simulation: LHS Estimator and Variances Analysis
Covers the analysis of the LHS estimator and variances in stochastic simulation.
Elements of Statistics: Probability and Random Variables
Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.
Measures of dispersion: Mean Square Error
Explains data dispersion, central tendency, variance, standard deviation, and Mean Square Error.
Propagation of Uncertainty: Model Measurements
Covers the propagation of uncertainty in model measurements and the importance of understanding errors.
Thematic Attributes and Classification
Covers statistical thematic mapping, types of maps, discretization methods, and proportional symbols in maps.