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Applied Linear Regression for Business Analytics with Python

A Practical Guide Using Ravix with Case Studies

Medium: Buch
ISBN: 978-3-032-23805-4
Verlag: Springer
Erscheinungstermin: 18.07.2026
Lieferfrist: bis zu 10 Tage

This textbook provides a practical, business-focused introduction to regression analysis using Python. It equips readers with the intuition, coding skills, and statistical tools needed to transform raw data into actionable insights. In today’s data-driven economy, where organizations rely on analytics for pricing, marketing, employee retention, and financial forecasting, regression remains a cornerstone method.

The text bridges theory and application by combining clear explanations, step-by-step coding, and real-world business case studies. A distinguishing feature is the introduction of the Ravix package, a regression modeling and visualization framework developed to streamline regression workflows in Python. Ravix simplifies model building, produces clear and interpretable output, and integrates seamlessly with core scientific Python libraries such as NumPy, Pandas, Statsmodels, and Scikit-learn. By reducing coding complexity and emphasizing interpretation, Ravix makes modern regression techniques accessible to students, analysts, and professionals.


Produkteigenschaften


  • Artikelnummer: 9783032238054
  • Medium: Buch
  • ISBN: 978-3-032-23805-4
  • Verlag: Springer
  • Erscheinungstermin: 18.07.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: International Series in Operations Research & Management Science
  • Produktform: Gebunden
  • Seiten: 327
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Introduction.- Basic Statistics and Functions Using Python.- Regression Fundamentals.- Simple Linear Regression.- Multiple Regression.- Estimation Intervals and Analysis of Variance.- Predictor Variable Transformations.- Model Diagnostics.- Variable Selection.- Appendix.- References.- Index.