Mathematical statistics

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Related lectures (30)

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Probability and Statistics

Covers probability distributions, moments, and continuous random variables.

Descriptive Statistics: Hypothesis Testing

Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.

Poisson Statistics: Examples and Applications

Explores Poisson statistics, examples of earthquakes and lightning strikes, dark current, and readout noise in photosensitive devices.

Normal Distribution: Characteristics and Z-scores

Explores normal distribution characteristics, Z-scores, probability in inferential statistics, sample effects, and binomial distribution approximation.

Statistics: Hypothesis Testing & Confidence Intervals

Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Extreme Value Analysis: Applications and Consequences

Explores extremal limit theorems and statistical analysis for analyzing extreme events like Venezuela rainfall and Venice data.

Genomic Data Analysis: Microarray Technology

Explores microarray technology for genomic data analysis, covering Affymetrix GeneChip Probe Arrays, data preprocessing, normalization, differential expression analysis, and method comparisons.

Describing Data: Statistics and Hypothesis Testing

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Estimation Methods in Probability and Statistics

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

Statistical Theory: Overview of Stochastic Convergence

Explores parametric inference, convergence, functions of random variables, and asymptotic approximations in statistical theory.