The sordid history of least squares скачать в хорошем качестве

The sordid history of least squares

The universe rarely gives us perfect data. When astronomers in the early 1800s tried to calculate the orbit of newly discovered celestial objects, they ran into a problem: too many observations and too few unknowns. Every measurement gave a slightly different answer. The equations didn’t agree. Out of that chaos emerged one of the most important tools in statistics: least squares. In this video, I explore the dramatic history behind least squares, and how mathematicians like Gauss, Laplace, Lagrange, and Legendre wrestled with noisy data, scientific rivalry, and the challenge of extracting truth from imperfect measurements. Along the way, we’ll see how the simple idea of minimizing squared errors became the foundation of modern regression, machine learning, and statistical modeling. For the self-guided simplistics course: https://simplistics.net/course/univar... For the self-guided Mixed Models course: https://simplistics.net/course/mixed/ For the self-guided visualization course: https://simplistics.net/course/random... For the self-guided R course: https://simplistics.net/course/introd... For other classes, see: https://simplistics.net/all-courses/ For consulting, see: https://simplistics.net/product/stati...