Statistics and visualisation of morphometric data

Related lectures (32)

Page 3 of 4

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

Explores the storage capacity of associative memory in networks of neurons and the impact of multiple prototypes on error rates.

Covers wave functions, electron density, probability distributions, and quantum operators.

Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.

Investigates how birth month influences athlete success, analyzing Japanese athletes' dataset to explore trends in birthdates and occupations.

Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.

Explores random variables, their variability, realization of random processes, and the scientific method in material science.

Explores the neuron as a unique electrical device, focusing on synaptic potentials and spiking activity.

Covers the propagation of uncertainty in model measurements and the importance of understanding errors.

Covers statistical thematic mapping, types of maps, discretization methods, and proportional symbols in maps.