Using a Standard Normal Table
Learn to interpret standard normal tables, calculate areas and percentiles for normal distributions, and standardize variables in this comprehensive statistical guide.
Fast and Optimal Low-Rank Tensor Regression via Importance - Garvesh Raskutti, UW-Madison
Explore low-rank tensor regression using importance sketching for efficient high-dimensional data analysis, with theoretical guarantees and practical applications in neuroimaging.
Statistical Rethinking 2023 - Markov Chain Monte Carlo
Explore Markov Chain Monte Carlo methods, from basic concepts to advanced techniques like Hamiltonian Monte Carlo, with practical applications and diagnostics for statistical modeling.
Statistical Rethinking - Markov Chain Monte Carlo
Explore Markov chain Monte Carlo and Hamiltonian Monte Carlo methods, including practical implementation in Stan and diagnostic techniques for statistical modeling.
Sampling Crash Course
Explore geometric methods in optimization and sampling, covering direct methods, Markov chain Monte Carlo, and probabilistic approaches for efficient algorithm design and analysis.
Statistics Tutorial with Python - Fundamentals and Data Analysis
Learn Python-based statistics: data types, visualization, measures of central tendency, dispersion, and relationships between variables. Gain practical skills for data analysis.
The Power of Sampling by Peter W. Glynn
Explore sampling methods in statistics, computation, and engineering. Learn about their history, applications, and advantages in overcoming dimensional challenges and creating scalable algorithms.
Enhancing Markov Chain Monte Carlo Sampling Methods with Deep Learning
Explore advanced techniques combining Markov Chain Monte Carlo sampling with deep learning, focusing on importance sampling, normalizing flows, and non-equilibrium methods for enhanced efficiency in high-dimensional problems.
MCMC Training of Bayesian Neural Networks
Explore Bayesian Neural Networks, MCMC methods, and their applications in machine learning with Prof. Radford Neal. Gain insights into flexible modeling and practical implementations.
Second and Higher Order Statistical Methods in Some Once Differentiable Problems
Explores advanced statistical methods for high-dimensional data analysis, including bias correction in linear regression, bootstrap techniques for distribution approximation, and functional estimation of mean vectors.
Elchanan Mossel: Combinatorial Statistics and the Sciences
Explore the intersection of combinatorial statistics and scientific applications with insights from renowned mathematician Elchanan Mossel in this thought-provoking lecture.
Using Statistical Methods and Reproducible Tools to Gain New Insights from Biomed and Public Health Data
Learn statistical methods and reproducible tools for analyzing biomedical and public health data, gaining valuable insights for research and decision-making in healthcare.
Statistical Methods for Scientists and Engineers
Comprehensive exploration of statistical techniques including parametric and non-parametric methods, multivariate analysis, and probability distributions for scientific and engineering applications.
T-Test: Fundamentals and Applications - Lecture 9
Explore the fundamentals and practical applications of t-tests in statistical analysis, enhancing your ability to interpret and conduct hypothesis testing effectively.
Efficient Truncated Statistics with Unknown Truncation
Explore efficient methods for analyzing truncated data with unknown truncation points, enhancing statistical inference in various fields of study.
Stratification for Markov Chain Monte Carlo
Explore advanced Markov Chain Monte Carlo techniques, focusing on stratification methods for complex systems modeling and statistical inference in various scientific domains.
Point Estimation Combining Measurements and Fitting - Lecture 2
Explore advanced statistical techniques for point estimation, measurement combination, and data fitting in high-energy physics, enhancing analysis skills for complex experimental data.
Bayesian Inference - Lecture 2
Explore Bayesian inference principles, methods, and applications in data assimilation for weather and climate modeling. Gain insights into uncertainty estimation and practical implementation.
Tools of High Dimensional Data - Lecture 3
Explore high-dimensional data analysis techniques with Bruce Walsh, focusing on advanced tools and methods for complex datasets in biological evolution and genetics.
Statistical Rethinking 2023
Comprehensive exploration of advanced statistical concepts, from basic models to complex techniques like Gaussian Processes and Generalized Linear Models, enhancing analytical skills for data interpretation.
Distribution Testing - Hypothesis Testing from Very Little or Very Private Data
Explore hypothesis testing techniques for distribution analysis using limited or private datasets, focusing on sublinear algorithms and their applications in data science.