Data Analytics

Handbook of Formulas and Techniques
1. Auflage 2024
ISBN: 978-0-367-53742-5
Verlag: CRC Press

Buch, Englisch, 272 Seiten, Format (B × H): 153 mm x 230 mm, Gewicht: 396 g

Reihe: Systems Innovation Book Series

Good data analytics is the basis for effective decisions. Whoever has the data, has the ability to extract information promptly and effectively to make pertinent decisions. The premise of this handbook is to empower users and tool developers with the appropriate collection of formulas and techniques for data analytics and to serve as a quick reference to keep pertinent formulas within fingertip reach of readers.

This handbook includes formulas that will appeal to mathematically inclined readers. It discusses how to use data analytics to improve decision-making and is ideal for those new to using data analytics to show how to expand their usage horizon. It provides quantitative techniques for modeling pandemics, such as COVID-19. It also adds to the suite of mathematical tools for emerging technical areas.

This handbook is a handy reference for researchers, practitioners, educators, and students in areas such as industrial engineering, production engineering, project management, civil engineering, mechanical engineering, technology management, and business management worldwide.

Zielgruppe

Academic, Postgraduate, Professional, and Undergraduate Advanced

Autoren/Hrsg.

Badiru, Adedeji B

Fachgebiete

• Mathematik | Informatik Mathematik Operations Research
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Industrielle Qualitätskontrolle
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
• Mathematik | Informatik Mathematik Mathematische Analysis Funktionalanalysis
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Technische Wissenschaften Technik Allgemein Industrial Engineering
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik

Inhaltsverzeichnis

Chapter 1. Essential Data Analytics. Chapter 2. Empirical Model Building. Chapter 3. Data Visualization Methods. Chapter 4. Basic Mathematical Calculations for Data Analytics. Chapter 5. Statistical Methods for Data Analytics. Chapter 6. Descriptive Statistics for Data Presentation. Chapter 7. Data Analytics Tools for Understanding Random Field Regression Models. Chapter 8. Application of DEJI Systems Model to Data Integration.

Über Autor(innen)

Adedeji B. Badiru is a professor of systems engineering at the Graduate School of Engineering and Management at the Air Force Institute of Technology. He was previously Professor and Department Head of Industrial Engineering at the University of Tennessee, and Professor of Industrial Engineering at the University of Oklahoma. He is a registered professional engineer (PE), a certified Project Management Professional (PMP), and a Fellow of the Institute of Industrial & Systems Engineers. He is the author of over 30 books, 34 book chapters, and 80 technical journal articles. He is a member of several professional associations and scholastic honor societies.