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Business Analytics

Walter R. Paczkowski
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      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.
      Format: Paperback / softback CONTRIBUTORS: Walter R. Paczkowski EAN: 9783030870256 COUNTRY: Switzerland PAGES: WEIGHT: 652 g HEIGHT: 235 cm
      PUBLISHED BY: Springer Nature Switzerland AG DATE PUBLISHED: 2023-01-05 CITY: GENRE: BUSINESS & ECONOMICS / Consumer Behavior, BUSINESS & ECONOMICS / Statistics, BUSINESS & ECONOMICS / Industries / Computers & Information Technology, BUSINESS & ECONOMICS / E-Commerce / Online Trading, COMPUTERS / Mathematical & Statistical Software WIDTH: 155 cm SPINE:

      Book Themes:

      Business mathematics and systems, Market research, Probability and statistics, Mathematical and statistical software, Maths for computer scientists

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      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).
      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.
      Format: Paperback / softback CONTRIBUTORS: Walter R. Paczkowski EAN: 9783030870256 COUNTRY: Switzerland PAGES: WEIGHT: 652 g HEIGHT: 235 cm
      PUBLISHED BY: Springer Nature Switzerland AG DATE PUBLISHED: 2023-01-05 CITY: GENRE: BUSINESS & ECONOMICS / Consumer Behavior, BUSINESS & ECONOMICS / Statistics, BUSINESS & ECONOMICS / Industries / Computers & Information Technology, BUSINESS & ECONOMICS / E-Commerce / Online Trading, COMPUTERS / Mathematical & Statistical Software WIDTH: 155 cm SPINE:

      Book Themes:

      Business mathematics and systems, Market research, Probability and statistics, Mathematical and statistical software, Maths for computer scientists

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      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).

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