Opening book details…
Can I read Industrial Statistics: A Computer-Based Approach with Python (Statistics for Industry, Technology, and Engineering) on EtoBox?
Industrial Statistics: A Computer-Based Approach with Python (Statistics for Industry, Technology, and Engineering) by Ron S. Kenett, Shelemyahu Zacks, Peter Gedeck is a computer science book available to read on EtoBox.
What is Industrial Statistics: A Computer-Based Approach with Python (Statistics for Industry, Technology, and Engineering) about?
This innovative textbook presents material for a course on industrial statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications. Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail. A custom Py
Who reads Industrial Statistics: A Computer-Based Approach with Python (Statistics for Industry, Technology, and Engineering)?
It is typically read by working professionals who need an authoritative practice reference.
Common subject areas: medicine, law, business, engineering.
- Author
- Ron S. Kenett, Shelemyahu Zacks, Peter Gedeck
- Publisher
- Birkhäuser
- Published
- 2023
- Language
- EN
- ISBN
- 9783031284823
- Category
- computer science
- Subjects
- Mathematics, Computer Science, Computers
- Updated
- 2026-03-25
Other editions & translations
More by Ron S. Kenett, Shelemyahu Zacks, Peter Gedeck
Browse all works by Ron S. Kenett, Shelemyahu Zacks, Peter Gedeck
Similar books
- Modern Statistics : A Computer-Based Approach with Python — Ron S. Kenett; Shelemyahu Zacks; Peter Gedeck (2022)
- Scan Statistics: Methods and Applications (Statistics for Industry and Technology) — Joseph Glaz, Vladimir Pozdnyakov, Sylvan Wallenstein, Joseph Naus (2009)
- Guide to Teaching Computer Science : An Activity-Based Approach — Orit Hazzan; Noa Ragonis; Tami Lapidot (2020)
- Python for R Users : A Data Science Approach — Ajay Ohri (2017)
- Statistics and Data Visualisation with Python — Jesús Rogel-Salazar (2023)
- Quantile-based Reliability Analysis (statistics For Industry And Technology) — N. Unnikrishnan Nair, P.G. Sankaran, N. Balakrishnan (auth.) (2013)