Probability and Statistical Data Analysis: Hypothesis Testing and Machine Learning Model Validation

## About Test scientific hypotheses with regression, validate assumptions with diagnostics, and control false discoveries across multiple comparisons. Then practice the modeling workflow with validation, interpretability, calibration, and deferral strategies. By the end of this course, you will have the knowledge and experience with an end-to-end workflow for building, evaluating, and deploying models you can defend with confidence. This course is part five of five in the Probability and Statistical Data Analysis Program, which includes the following: * Foundations and Exploratory Data Analysis * Discrete Distributions and Categorical Data * Multivariate Statistics and Bayesian Inference * Uncertainty Quantification and Data-Driven Decisions * Hypothesis Testing and Machine Learning Model Validation ## What you'll learn * Speak the language of sample spaces and events * Reason conditionally about how outcomes relate * Turn a scientific question into a probability question * Summarize data with histograms, boxplots, and proportions

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