Fundamentals of Statistics

Massachusetts Institute of Technology (MIT) is a private research university located in Cambridge, Massachusetts, United States. Established in 1861, MIT is devoted to the advancement of knowledge and education in science, technology, and other areas of scholarship that will best serve the nation and the world in the 21st century. MIT is known for its strong emphasis on research and innovation, as well as its commitment to solving real-world problems through interdisciplinary collaboration. Its main campus spans over 160 acres and is home to five schools and one college, including the School of Architecture and Planning, the School of Engineering, the School of Humanities, Arts, and Social Sciences, the Sloan School of Management, the School of Science, and the MIT Schwarzman College of Computing.

Statistics is the science of turning data into insights and ultimately decisions. Behind recent advances in machine learning, data science and artificial intelligence are fundamental statistical principles. The purpose of this class is to develop and understand these core ideas on firm mathematical grounds starting from the construction of estimators and tests, as well as an analysis of their asymptotic performance.After developing basic tools to handle parametric models, we will explore how to answer more advanced questions, such as the following:How suitable is a given model for a particular dataset?How to select variables in linear regression?How to model nonlinear phenomena?How to visualize high-dimensional data?Taking this class will allow you to expand your statistical knowledge to not only include a list of methods, but also the mathematical principles that link them together, equipping you with the tools you need to develop new ones.