Overview
- Uses case studies to illustrate concepts
- Presents examples using Python in the context of Jupyter notebooks with Programming Literacy examples
- Features appendices with technical details
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Table of contents (12 chapters)
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Front Matter
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Intermediate Analytics
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Front Matter
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Back Matter
Keywords
About this book
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of:
1. statistical, econometric, and machine learning techniques;
2. data handling capabilities;
3. at least one programming language.
Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.
Authors and Affiliations
About the author
Walter R. Paczkowski, PhD, has worked at AT&T, AT&T Bell Labs, and AT&T Labs. He founded Data Analytics Corp., a statistical consulting company, in 2001. Dr. Paczkowski is also a part-time lecturer of economics at Rutgers University. He is the author of Deep Data Analytics for New Product Development (2020), Pricing Analytics: Models and Advanced Quantitative Techniques for Product Pricing (2018), and Market Data Analysis Using JMP (2016).
Bibliographic Information
Book Title: Business Analytics
Book Subtitle: Data Science for Business Problems
Authors: Walter R. Paczkowski
DOI: https://doi.org/10.1007/978-3-030-87023-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-87022-5Published: 04 January 2022
Softcover ISBN: 978-3-030-87025-6Published: 05 January 2023
eBook ISBN: 978-3-030-87023-2Published: 03 January 2022
Edition Number: 1
Number of Pages: XXXVIII, 387
Number of Illustrations: 23 b/w illustrations, 215 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Big Data/Analytics, Probability and Statistics in Computer Science, Online Marketing/Social Media, Consumer Behavior, Market Research/Competitive Intelligence