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Related lectures (30)

Page 2 of 3

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Statistical Inference: Approximate Critical Values and Confidence Intervals

Covers the construction of confidence intervals and approximate critical values in statistical inference.

Statistical Theory: Fundamentals

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Introduction to Probability Theory

Covers the basics of probability theory, including definitions, calculations, and important concepts for statistical inference and machine learning.

Confidence Intervals: Definition and Estimation

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.

Probabilistic Models for Linear Regression

Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.

Estimating R: Example 100

Explores correlation limitations, probability, random variables, and statistical inference using a ball-drawing example.

Fracture Mechanics: Crack Growth and Weakest Link

Explores fracture mechanics, crack growth, and the weakest link theory, emphasizing the statistical distribution of crack sizes and the significance of the largest crack in material failure.

Data Analysis: Correlation Measures

Covers the basics of data analysis, focusing on statistical concepts and correlation measures.

Maximum Likelihood Inference

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.