Lectures in course MATH-234(a): Probability and statistics

Estimation Methods: Point Estimate and Maximum Likelihood

Discusses different estimators and how to choose between them, emphasizing calculation and properties.

Explores estimators, bias, and efficiency in statistics, emphasizing the trade-off between bias and variability.

Estimating Parameters: Confidence Intervals

Explores estimating parameters through confidence intervals in linear regression and statistics.

Explores parameter estimation, standard errors, and confidence intervals using the central limit theorem and practical examples.

Regression and Kinetics Modeling

Explores regression analysis, kinetics modeling, parameter estimation, and atmospheric ozone concentration modeling using linear relationships and scatterplots.

Linear Regression: Model Adjustment and Parameter Estimation

Explains the decomposition of total sum of squares, model adjustment, and parameter estimation in linear regression.