Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.
Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.
Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.
Explains estimation, correlation, and Pearson correlation in statistics, focusing on measuring and describing relationships between variables.
Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.
Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
