SCIENTIFIC PROGRAMMING LAB: PROBABILITY AND STATISTICS

Catalog description

This is a follow-up laboratory course in scientific computing, building upon foundational programming and statistical methods. The course focuses on statistical modeling, data analysis, and probabilistic simulations, providing students with the computational tools to manipulate structured data, conduct hypothesis testing, and assess statistical models. Students will develop problem-solving skills through hands-on programming, working with statistical computing tools to explore real-world applications in data science and scientific research. Laboratory activities will include implementing statistical models, analyzing probability distributions, conducting hypothesis tests, and performing Monte Carlo simulations. Students will work with structured datasets, apply numerical techniques for statistical inference, and generate visualizations to communicate results effectively. The course emphasizes computational efficiency, reproducibility, and ethical data management in statistical computing.