Probability and Statistics

Related lectures (30)

Page 3 of 3

Explores the convergence of random variables, the law of large numbers, and the distribution of failure time.

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Explores different modes of convergence for random variables.

Explores variance, covariance, and practical applications in statistics and probability.

Covers probability, statistics, independence, covariance, correlation, and random variables.

Explores PDF forms, statistics, boxplots, density curves, and data analysis methods.

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.