Lectures related to Scientific control

Covers causal analysis of observational data, pitfalls, tools for valid conclusions, and addressing confounding variables.

Discusses experimental design strategies, factors, responses, treatment combinations, and degrees of freedom.

Covers randomized clinical trials, confounding variables, ethical challenges, and Simpson's paradox in data analysis.

Covers advanced principles of Chaos Engineering, emphasizing risk management and minimizing user impact.

Covers research questions, hypotheses, variables, and experimental designs in learning experiments.

Covers the principles of feedback control systems and their applications in various fields.