Deep Data Analytics for New Product Development
Deep Data Analytics for New Product Development

Author: Walter R. Paczkowski

Publisher: Routledge

Published: 2020-02-19

Total Pages: 304

ISBN-13: 0429663315

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This book presents and develops the deep data analytics for providing the information needed for successful new product development. Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole. This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs.

Predictive and Simulation Analytics
Predictive and Simulation Analytics

Author: Walter R. Paczkowski

Publisher: Springer Nature

Published: 2023-07-18

Total Pages: 381

ISBN-13: 3031318870

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This book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems to direct data-driven decisions. Readers will explore methods for extracting information from data, work with simple and complex systems, and meld multiple forms of analytics for a more nuanced understanding of data science. The methods can be readily applied to business problems such as demand measurement and forecasting, predictive modeling, pricing analytics including elasticity estimation, customer satisfaction assessment, market research, new product development, and more. The book includes Python examples in Jupyter notebooks, available at the book's affiliated Github. This volume is intended for current and aspiring business data analysts, data scientists, and market research professionals, in both the private and public sectors.

Business Analytics
Business Analytics

Author: Walter R. Paczkowski

Publisher: Springer Nature

Published: 2022-01-03

Total Pages: 416

ISBN-13: 3030870235

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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.

Modern Survey Analysis
Modern Survey Analysis

Author: Walter R. Paczkowski

Publisher: Springer Nature

Published: 2022-09-11

Total Pages: 365

ISBN-13: 303076267X

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This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the basics of Bayesian data analysis and its Python implementation are presented. Since surveys are widely used as the primary method to collect data, and ultimately information, on attitudes, interests, and opinions of customers and constituents, these tools are vital for private or public sector policy decisions. As a compact volume, this book uses case studies to illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives: Demonstrate how to extract actionable, insightful, and useful information from survey data; and Introduce Python and Pandas for analyzing survey data.

Hands-On Prescriptive Analytics
Hands-On Prescriptive Analytics

Author: Walter R. Paczkowski

Publisher: "O'Reilly Media, Inc."

Published: 2024-10-17

Total Pages: 412

ISBN-13: 1098153146

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Business decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty. With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive analytics explores the results from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future. While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. Author Walter R. Paczkowski, Ph.D. shows you: The distinction among descriptive, predictive, and prescriptive analytics How predictive analytics produces a menu of action options How prescriptive analytics narrows the menu of action options The forms of prescriptive analytics: eight prescriptive methods Two broad classes of these methods: non-stochastic and stochastic How to develop prescriptive analyses for action recommendations Ways to use an appropriate tool-set in Python

Intelligent Systems and IoT Applications in Clinical Health
Intelligent Systems and IoT Applications in Clinical Health

Author: Joshi, Herat

Publisher: IGI Global

Published: 2024-11-01

Total Pages: 522

ISBN-13:

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Integrating intelligent systems and internet of things (IoT) into clinical health is crucial for enhancing patient care and operational efficiency. These technologies enable real-time data collection and analysis, facilitating personalized treatment plans and improving diagnostic accuracy. Together innovations can streamline workflows, reduce costs, and ultimately lead to better health outcomes for patients. It is essential to explore how these technologies can be implemented into healthcare. Intelligent Systems and IoT Applications in Clinical Health explores and elucidates the integration of AI, IoT, and blockchain technologies in healthcare. It advances current research by providing comprehensive insights into how these technologies can be leveraged to enhance patient care, improve operational efficiency, and ensure data security. Covering topics such as clinical healthcare, digital health experience, and monitoring systems, this book is an excellent resource for researchers, academicians, medical professionals, medical administrators, educators, graduate and postgraduate students, and more.

Product Analytics
Product Analytics

Author: Joanne Rodrigues

Publisher: Addison-Wesley Professional

Published: 2020-08-27

Total Pages: 735

ISBN-13: 0135258634

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Use Product Analytics to Understand Consumer Behavior and Change It at Scale Product Analytics is a complete, hands-on guide to generating actionable business insights from customer data. Experienced data scientist and enterprise manager Joanne Rodrigues introduces practical statistical techniques for determining why things happen and how to change what people do at scale. She complements these with powerful social science techniques for creating better theories, designing better metrics, and driving more rapid and sustained behavior change. Writing for entrepreneurs, product managers/marketers, and other business practitioners, Rodrigues teaches through intuitive examples from both web and offline environments. Avoiding math-heavy explanations, she guides you step by step through choosing the right techniques and algorithms for each application, running analyses in R, and getting answers you can trust. Develop core metrics and effective KPIs for user analytics in any web product Truly understand statistical inference, and the differences between correlation and causation Conduct more effective A/B tests Build intuitive predictive models to capture user behavior in products Use modern, quasi-experimental designs and statistical matching to tease out causal effects from observational data Improve response through uplift modeling and other sophisticated targeting methods Project business costs/subgroup population changes via advanced demographic projection Whatever your product or service, this guide can help you create precision-targeted marketing campaigns, improve consumer satisfaction and engagement, and grow revenue and profits. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Research Anthology on Telemedicine Efficacy, Adoption, and Impact on Healthcare Delivery
Research Anthology on Telemedicine Efficacy, Adoption, and Impact on Healthcare Delivery

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2021-01-15

Total Pages: 689

ISBN-13: 1799881075

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Telemedicine, which involves electronic communications and software, provides the same clinical services to patients without the requirement of an in-person visit. Essentially, this is considered remote healthcare. Though telemedicine is not a new practice, it has become an increasingly popular form of healthcare delivery due to current events, including the COVID-19 pandemic. Not only are visits being moved onto virtual platforms, but additional materials and correspondence can remain in the digital sphere. Virtual lab results, digital imaging, medical diagnosis, and video consultations are just a few examples that encompass how telemedicine can be used for increased accessibility in healthcare delivery. With telemedicine being used in both the diagnosis and treatment of patients, technology in healthcare can be implemented at almost any phase of the patient experience. As healthcare delivery follows the digital shift, it is important to understand the technologies, benefits and challenges, and overall impacts of the remote healthcare experience. The Research Anthology on Telemedicine Efficacy, Adoption, and Impact on Healthcare Delivery presents the latest research on best practices for adopting telehealth into medical practices and its efficacy and solutions for the improvement of telemedicine, as well as addresses emerging challenges and opportunities, including issues such as securing patient data and providing healthcare accessibility to rural populations. Covering important themes that include doctor-patient relationships, tele-wound monitoring, and telemedicine regulations, this book is essential for healthcare professionals, doctors, medical students, academic and medical libraries, medical technologists, practitioners, stakeholders, researchers, academicians, and students interested in the emerging technological developments and solutions within the field of telemedicine.

Pricing Analytics
Pricing Analytics

Author: Walter R. Paczkowski

Publisher: Routledge

Published: 2018-06-27

Total Pages: 339

ISBN-13: 1351713094

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The theme of this book is simple. The price – the number someone puts on a product to help consumers decide to buy that product – comes from data. Specifically, itcomes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly provide the background and framework for the models. Therefore, this book emphasizes two interlocking components of modeling: economic theory and statistical principles. The economic theory component is sufficient to provide understanding of the basic principles for pricing, especially about elasticities, which measure the effects of pricing on key business metrics. Elasticity estimation is the goal of statistical modeling, so attention is paid to the concept and implications of elasticities. The statistical modeling component is advanced and detailed covering choice (conjoint, discrete choice, MaxDiff) and sales data modeling. Experimental design principles, model estimation approaches, and analysis methods are discussed and developed for choice models. Regression fundamentals have been developed for sales model specification and estimation and expanded for latent class analysis.