Resampling Methods

Sort options

Resampling, Selection and Splines (Coursera)

"Statistical Learning for Data Science" is an advanced course designed to equip working professionals with the knowledge and skills necessary to excel in the field of data science. Through comprehensive instruction on key topics such as shrink methods, parametric regression analysis, generalized linear models, and general additive models, students [...]

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 [...]

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 [...]

Statistics (edX)

This course provides an overview of bachelor-level statistics. You will review the concepts of descriptive and inferential statistics. You will use the statistical software package R on real data to gain insight in these topics. A strong foundation in mathematics is critical for success in all science and engineering [...]

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 [...]