Statistical Analysis: Data Exploration and Inference

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Related lectures (29)

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Statistical Models and Parameter Estimation

Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.

Statistical Theory: Fundamentals

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

Confidence Intervals: Definition and Estimation

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

Estimation Methods in Probability and Statistics

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Density of States and Bayesian Inference in Computational Mathematics

Explores computing density of states and Bayesian inference using importance sampling, showcasing lower variance and parallelizability of the proposed method.

Sampling Theory: Statistics and Inference

Covers sampling theory, statistics, and inference, focusing on the sampling distribution of statistics.

Sampling Distributions: Estimators and Variance

Covers estimation of parameters, MSE, Fisher information, and the Rao-Blackwell Theorem.

Sampling: Inference and Statistics

Explores sampling in inferential statistics, emphasizing the impact of sample size and randomness on inference accuracy.

Sampling Distributions: Understanding Ancillary Statistics

Explores ancillary statistics, sufficiency, and minimally sufficient statistics in sampling distributions.