Observational Studies: Pitfalls and Solutions

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Page 3 of 4

Explores the assessment of market regulation, focusing on high-frequency trading and the impact of regulatory changes on liquidity and market quality.

Simpson's Paradox: Understanding and Randomized Trials

Explores Simpson's Paradox with a real-world example and emphasizes the significance of randomized trials.

Experimental Design in Biostatistics

Introduces experimental design in biostatistics, covering research process, hypothesis testing, ANOVA modeling, and interpretation of results.

Designing Experiments and Measuring Learning

Explores experimental design challenges in social sciences, emphasizing hypothesis formulation, variable control, and bias mitigation.

Advanced Probability: Bayes' Theorem and Random Variables

Covers advanced probability concepts, including Bayes' Theorem and Random Variables.

Experimental Design: Replication, Randomization, Blocking

Delves into experimental design in genomics, emphasizing replication, randomization, and blocking for reducing bias and controlling variation.

Causal Inference: Understanding Treatment Effects

Explores treatment effects, confounding variables, and challenges in interpreting observational study results.

Experimental Design: Strategies and Analysis

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

Causal Inference in Epidemiology: Pregnancy and Prostate Cancer

Explores causal inference in epidemiology, focusing on COVID-19's impact on preterm birth and refining treatment strategies for prostate cancer.

Design and Analysis of Experiments

Covers the design and analysis of experiments, focusing on statistics for experimenters.