Air Pollution Analysis

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Related lectures (30)

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Statistical Theory: Fundamentals

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

Fundamental Limits of Gradient-Based Learning

Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.

Linear Combinations: Moment-Generating Functions

Explores moment-generating functions, linear combinations, and normality of random variables.

Continuous Random Variables: Basic Ideas

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Air Pollution and Wind Analysis

Focuses on analyzing wind directions to understand air pollutant origins, covering loading libraries, reading wind data, and visualizing wind roses.

Probabilities and Statistics

Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.

Random Variables and Expected Value

Introduces random variables, probability distributions, and expected values through practical examples.

Probability and Statistics

Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.

Describing Data: Statistics and Hypothesis Testing

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