Free Download Python for Beginners (Easy Statistics)
English | 2025 | ASIN: B0DXQGG428 | Pages not found | PDF | 2.95 MB
This book, authored by Anusha Illukkumbura, is a practical guide for beginners to learn regression analysis using Python. It focuses on implementing linear and non-linear regression models with step-by-step examples, leveraging essential Python libraries like NumPy, Pandas, MatDescriptionlib, and Statsmodels. The book is structured to progressively introduce concepts, starting from basic linear regression to more advanced models like logarithmic and quadratic regression.
Chapter 1: Introduces simple linear regression, explaining how to calculate correlation, fit a regression model, and interpret results using Python.
Chapter 2: Explains the use of Jupyter Notebook for coding and visualization.
Chapter 3: Covers advanced regression techniques, including log-linear and log-log models, with detailed coding examples.
Chapter 4: Focuses on quadratic regression, demonstrating how to model non-linear relationships and validate results.
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