Skip to main content
Graph
Search
fr
|
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Extreme Values: Applications and Probability Framework
Graph Chatbot
Related lectures (32)
Previous
Page 1 of 4
Next
Optimality in Statistical Inference
Delves into the duality between confidence intervals and hypothesis tests, emphasizing the importance of precision and accuracy in estimation.
Statistical Inference: Confidence Intervals
Covers the construction of approximate confidence intervals using the central limit theorem for large sample sizes.
Statistical Inference: Approximate Critical Values and Confidence Intervals
Covers the construction of confidence intervals and approximate critical values in statistical inference.
Estimating GEV Parameters
Explores techniques for estimating GEV parameters using graphical and likelihood-based methods, illustrated with real-world examples.
L-Moment Estimation: Probability-Weighted Moments
Covers L-moment estimation, probability-weighted moments, and maximum likelihood inference basics.
Statistical Theory: Inference and Optimality
Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.
Probability Distributions in Environmental Studies
Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.
Interval Estimation: Method of Moments
Covers the method of moments for estimating parameters and constructing confidence intervals based on empirical moments matching distribution moments.
Quantiles, Sampling, Histogram Density
Explores quantiles, sampling, and histogram density for understanding distributions and constructing confidence intervals.
Interval Estimation
Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.
