Applied Linear Regression for Business Analytics with Python A Practical Guide Using Ravix with C...
Category: eBooks
- views: 182
- date: 11 June 2026
- posted by: BeMyLove
Applied Linear Regression for Business Analytics with Python A Practical Guide Using Ravix with Case Studies | 48.86 MB
Title: Applied Linear Regression for Business Analytics with Python
Author: Daniel P. McGibney
Category: Nonfiction, Computers, Database Management, Programming, Programming Languages, Reference & Language, Reference
Language: English | 340 Pages | ISBN: 9781398617278
Description:
Your essential textbook for mastering business analytics through Python.
Business Analytics with Python by Bowei Chen and Gerhard Kling is the definitive guide for upper-level undergraduate and postgraduate students studying business, management or finance. Designed to support analytics modules that prioritize practical application, this textbook introduces students to data-driven decision-making through Python, without assuming a background in computer science. It aligns with course outcomes by integrating statistical, mathematical and machine learning techniques into a unified business context.
This textbook takes a holistic approach to business analytics, exploring how Python can be used to interpret and solve real-world problems. From foundational coding skills to the implementation of supervised and unsupervised machine learning methods, students learn how to translate data into insight across key business functions. Through industry-relevant case studies, including customer churn analysis, fraud detection and sales forecasting, learners build confidence in applying analytics to real organizational challenges.
Pedagogical features include:
- A running case study that reinforces practical learning across chapters
- Clear learning objectives and chapter summaries to track progress
- Step-by-step exercises and coding activities to build analytical fluency
- Examples grounded in real business applications for immediate relevance
Whether preparing for exams or building analytical capability for a future career, this textbook equips students with the tools to turn business data into strategic advantage.
DOWNLOAD:
https://rapidgator.net/file/d453c41842055931e83ef02ab8d7926d/978-3-032-23806-1.rar
https://nitroflare.com/view/65B20682D69E344/978-3-032-23806-1.rar
Your essential textbook for mastering business analytics through Python.
Business Analytics with Python by Bowei Chen and Gerhard Kling is the definitive guide for upper-level undergraduate and postgraduate students studying business, management or finance. Designed to support analytics modules that prioritize practical application, this textbook introduces students to data-driven decision-making through Python, without assuming a background in computer science. It aligns with course outcomes by integrating statistical, mathematical and machine learning techniques into a unified business context.
This textbook takes a holistic approach to business analytics, exploring how Python can be used to interpret and solve real-world problems. From foundational coding skills to the implementation of supervised and unsupervised machine learning methods, students learn how to translate data into insight across key business functions. Through industry-relevant case studies, including customer churn analysis, fraud detection and sales forecasting, learners build confidence in applying analytics to real organizational challenges.
Pedagogical features include:
- A running case study that reinforces practical learning across chapters
- Clear learning objectives and chapter summaries to track progress
- Step-by-step exercises and coding activities to build analytical fluency
- Examples grounded in real business applications for immediate relevance
Whether preparing for exams or building analytical capability for a future career, this textbook equips students with the tools to turn business data into strategic advantage.
DOWNLOAD:
https://rapidgator.net/file/d453c41842055931e83ef02ab8d7926d/978-3-032-23806-1.rar
https://nitroflare.com/view/65B20682D69E344/978-3-032-23806-1.rar
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