Observational Studies: Pitfalls and Solutions

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Related lectures (31)

Page 3 of 4

Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.

Probability Theory: Fundamentals and Calculations

Covers the basics of probability theory, including events, intersections, unions, and probabilities.

Probability and Statistics for SIC

Delves into probability, statistics, random experiments, and statistical inference, with practical examples and insights.

Experimental Design in Biostatistics

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

Experimental Design: Replication, Randomization, Blocking

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

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.

Experimental Design: Strategies and Analysis

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

Simpson's Paradox: Understanding and Randomized Trials

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

Block Pulled by a Spring

Explores the dynamics of a block pulled by a spring under various conditions.

Design and Analysis of Experiments

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