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Lecture
Design of Experiments Basics
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Related lectures (31)
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Online Matching in Evolving Environments
Explores online matching in evolving environments, addressing challenges and solutions for adapting algorithms to changing data.
Randomization tests: Understanding Experimental Results
Explores randomization tests as an alternative to t-tests for experimental analysis, using fake data to assess treatment effectiveness.
Statistical Modeling: Fundamentals and Process Factors
Covers the fundamental concept of statistical modeling and process factors for prediction and optimization.
Exploration Bias
Explores the concept of exploration bias and its impact on data.
Understanding Statistics & Experimental Design
Covers basic probability theory, ANOVA, experimental design, and correlations, emphasizing the importance of planning multiple tests and power analysis.
Introduction to Probability Theory
Covers the basics of probability theory, including definitions, calculations, and important concepts for statistical inference and machine learning.
Causal Inference: Estimands and Ontologies
Explores causal inference, emphasizing the importance of committing to an ontology for drawing causal inferences and selecting appropriate estimands.
Design and Analysis of Experiments
Covers the design and analysis of experiments, focusing on statistics for experimenters.
ANOVA & Moderation
Explores ANOVA, moderation, and statistical analysis methods in digital education, emphasizing their significance in educational research.
Introduction to ANOVA
Covers the basics of ANOVA using a case study on sleeping pill effectiveness.
