Scientific & Statistical Reasoning
Learn to apply critical thinking principles to scientific claims and statistical data. Understand concepts like correlation vs. causation, sample size, and statistical significance to avoid being misled by data.
118 courses
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Causal Inference and DAGs in R
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Calculating and Interpreting Effect Sizes: d and r Families
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How to Read Medical Research: Evaluate Health Claims and Spot Bad Science
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Evidence-Based Healthcare: Evaluating Medical Research and Claims
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Understanding Statistical Inference and Experimental Design
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Practical Causal Inference for Data Analysis
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Demystifying Forensic Science: Evidence, Limits, and the Courtroom
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Evaluating Evidence: A Guide to Science Literacy
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Statistical Hypothesis Testing: A Simplified, Example-Based Guide
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Causal Diagrams for Data Analysis and Study Design
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Data to Knowledge: Scientific Methods for Critical Thinking
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Causal Inference Fundamentals: Understanding Cause and Effect in Data
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Statistical Inference and Modeling for High-Throughput Data
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Introduction to Causal Inference: Understanding Cause and Effect in Data
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Causal Inference Project Ideation and Design
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Causal Data Science: Making Decisions Over Time
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Infrared Spectroscopy: Systematic Spectra Interpretation
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Null Hypothesis Significance Testing and z-Tests for Beginners
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Introduction to t-Tests: Hypothesis Testing for Analyzing Means
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Practical Causal Inference: From Correlation to Causation
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Real-time Data Science Decisions
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Minitab: Applied Statistics and Hypothesis Testing
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Foundations of Research Methodology
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Medical Research and Biostatistics Fundamentals
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Showing 1–24 of 118 courses