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4.4
52 reviewsThe tutorial style of writing, accompanied by over 30 diagrams, offers a visually intuitive account of linear regression, including a brief overview of nonlinear and Bayesian regression. Hands-on experience is provided in the form of numerical examples, included as Python code at the end of each chapter, and implemented online as Python and Matlab code. Supported by a comprehensive glossary and tutorial appendices, this book provides an ideal introduction to regression analysis.