Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Causal Analysis of Observational Data
Graph Chatbot
Related lectures (31)
Probability and Statistics for SIC
Delves into probability, statistics, random experiments, and statistical inference, with practical examples and insights.
Probability Model Construction
Explores constructing a probability model, random sampling, variance calculation, and allocation optimization in experiments.
Probability Theory: Fundamentals and Calculations
Covers the basics of probability theory, including events, intersections, unions, and probabilities.
Design of Experiments Basics
Covers the fundamentals of Design of Experiments (DOE) and experimental strategies.
Experimental Design in Biostatistics
Introduces experimental design in biostatistics, covering research process, hypothesis testing, ANOVA modeling, and interpretation of results.
Causal Effects Bounds: Sensitivity Parameters on Risk Difference Scale
Explores deriving bounds for causal effects using sensitivity parameters on the risk difference scale, addressing limitations and proposing new approaches.
Ensemble Fondamental: Events Space
Discusses the fundamental set and the events space with illustrative examples.
Randomized Trials and Simpson's Paradox
Covers randomized clinical trials, confounding variables, ethical challenges, and Simpson's paradox in data analysis.
Designing Experiments and Measuring Learning
Explores experimental design challenges in social sciences, emphasizing hypothesis formulation, variable control, and bias mitigation.
Experimental Design: Strategies and Analysis
Discusses experimental design strategies, factors, responses, treatment combinations, and degrees of freedom.
Understanding Statistics & Experimental Design
Covers basic probability theory, ANOVA, experimental design, and statistical reporting errors.
Previous
Page 2 of 2
Next