Logistic Regression
Learn to predict discrete outcomes using logistic regression, covering coefficients, maximum likelihood, R-squared, p-values, deviance, and practical implementation in R.
Parameter Estimation in Mathematical Oncology - Lecture
Dive into advanced techniques for parameter estimation in mathematical oncology, exploring key concepts and practical applications.
Using Classical Algorithms for Modern Applications: MCMC for Tail Calculations, EM - Lecture
Explore classical algorithms applied to modern challenges: MCMC for tail probability estimation and EM for PET reconstruction. Gain insights into innovative adaptations of established methods for cutting-edge problems.
Maximum Likelihood Estimation
Comprehensive exploration of Maximum Likelihood Estimation across various probability distributions, including practical applications using R for data generation and parameter estimation.
Parameter Estimation
Explore various parameter estimation methods, their optimality properties, and key statistical concepts like sufficient statistics, Bayesian estimation, and Fisher's information.
Maximum Likelihood Estimator Topics
Explore maximum likelihood estimation for various probability distributions, including gamma, Bernoulli, exponential, and geometric.
Regression
Explore point estimation, maximum likelihood, and distribution for regression coefficients, focusing on ordinary least squares and slope estimator analysis.
Maximum Likelihood Estimation
Explore maximum likelihood estimation through examples of binomial, Poisson, and uniform distributions, enhancing statistical analysis skills.
Actuarial Statistics 1
Comprehensive coverage of actuarial statistics, including probability distributions, data analysis, and statistical concepts. Includes calculator tutorials and R programming for practical application in actuarial work.
Qualitative Response Models: Logit and Types - Part II
Explore types of qualitative response models, focusing on logit models and their applications in statistical analysis.
Qualitative Response Models: Logit and Probit - Part IV
Explore logit and probit models as examples of qualitative response models, gaining insights into their applications and interpretations.
Qualitative Response Models: Logit and Probit - Part III
Explore logit, probit, and qualitative response models for analyzing categorical data and predicting discrete outcomes.
Detecting Power Laws in Real-world Data with Python Code
Learn to detect power laws in real-world data using Python, covering log-log and maximum likelihood approaches with practical examples using artificial and social media datasets.
Towards Generalized Schubert Varieties and Anabelian Matroids
Delve into advanced geometric theories connecting Huh's matroid discoveries with Schubert varieties, exploring applications in statistics and combinatorics through mixed Eulerian numbers.
Statistical Inference
Comprehensive exploration of statistical inference, covering likelihood, hypothesis testing, Bayesian statistics, and non-parametric methods for robust data analysis and decision-making.
Recent Progress in High-Dimensional Learning
Explore recent advancements in high-dimensional learning, covering robust estimation, maximum likelihood, and algorithmic approaches for handling noise and adversarial scenarios.
Your Dreams May Come True with MTP2 by Caroline Uhler
Explore multivariate totally positive distributions, their properties, and applications in various fields. Learn about density estimation, ML estimation, and practical uses in portfolio selection and gene networks.
Invariant Theory for Maximum Likelihood Estimation
Explore connections between maximum likelihood estimation and invariant theory stability in log-linear and Gaussian group models, with applications to statistical modeling.
Linear Regression Analysis and Forecasting
Learn regression analysis techniques for modeling, hypothesis testing, and forecasting using MINITAB software. Covers simple and multiple linear regression, parameter estimation, diagnostics, and practical applications.
Statistics for Data Analysis with Exercises - Lecture 3
Explore advanced statistical methods for data analysis in high-energy physics, focusing on practical applications and exercises to enhance understanding and skills in this specialized field.
How to Be More Productive Using Mathematics
Discover how mathematical concepts like Poisson distribution and vector calculus can boost your productivity, explained by an Oxford mathematician using real-world applications and advanced modeling techniques.