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It covers topics such as statistical process control, including multivariate methods, the design of experiments, including computerexperiments and reliability methods, including Bayesian reliability.
Embedded in the IBM ILOG CPLEX Optimization Studio with its solver engine CPLEX, OPL has been popular for years not only for academic and scientific purposes, but also among practitioners who need to model and solve large-scale real-world business optimization problems.
In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to design and analyze control systems using MATLAB’s specialized Control Systems Toolbox.
This textbook is designed for students in statistics, data science, biostatistics, engineering, and physical science programs who need... Læs mere
Mathematical Foundations of Computer Science introduces students to the discrete mathematics needed later in their Computer Science coursework with theory of... Læs mere
This practical guide shows programmers who understand analysis concepts how to build the skills necessary to achieve business value. Author Deanne Larson helps you bridge the technical and business worlds to meet these requirements.
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.
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking.
This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems.
This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data, with the applications of Excel VBA, Python and R.
This book presents a selection of peer-reviewed contributions to the fifth Bayesian Young Statisticians Meeting, BaYSM 2021, held virtually due to the COVID-19 pandemic on 1-3 September 2021.