Simple Linear Regression in Python with statsmodels | Ch. 13

How much does blood pressure change for each BMI point? Learn the simple linear regression model, its intercept and slope, and how to fit and read sm.OLS() on NHANES data. You will learn: How regression extends correlation The computational toolkit: pandas, NumPy, statsmodels The model: intercept, slope and error Fit and read sm.OLS() on NHANES Interpreting coefficients, t-statistics and R-squared Every example comes from the book, so you can read the section and run the code yourself. Get the book: https://www.idasm.com Chapter 13 playlist:    • Applied Data Science with Python Vol I, Ch...   Applied Data Science with Python, Volume I: Data Science and Statistical Foundations By Dr. Aymen Bennihi and Dr. Brahim Zirari Chapter 13: Linear Regression (Sections 13.1 to 13.4) Chapters: 0:00 Intro 0:07 From association to a line 0:26 Roadmap 0:49 From correlation to regression 1:48 The computational toolkit 2:19 Intercept and slope 3:04 sm.OLS() on NHANES 3:46 Interpreting the output 4:46 Cautions 5:15 Recap If this helped, like the video and subscribe for the next chapters. #Python #LearnPython #PythonForBeginners #DataScience #AppliedDataScience #PythonTutorial #Programming #LinearRegression