Resampling Methods

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Practical Predictive Analytics: Models and Methods (Coursera)

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help [...]
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Introduction to Statistics (Coursera)

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You [...]
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Successfully Evaluating Predictive Modelling (edX)

Gain an in-depth understanding of evaluation and sampling approaches for effective predictive modelling using Python. A predictive exercise is not finished when a model is built. This course will equip you with essential skills for understanding performance evaluation metrics, using Python, to determine whether a model is performing [...]
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Data Science: Inferential Thinking through Simulations (edX)

Learn how to test hypotheses, draw inferences, and make robust conclusions based on data. Using real-world examples from a wide range of domains including law, medicine, and football, you’ll learn how data scientists make conclusions about unknowns based on the data available. In this course, you will learn the [...]
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