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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.
The author uses his extensive classroom experience to guide students toward deeper understanding of key concepts, while they gain facility with software they will need to master for later studies and practical use in their engineering careers.
Readers begin with simple data operations and the underlying theory of choice analysis and conclude by working with sophisticated models including latent class logit models, mixed logit models, and ordinal logit models with taste heterogeneity.
This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with data science.
This book explains the best practices of the UNCTAD & WTO for trade analysis to the R users community. It shows how to replicate the UNCTAD & WTO's Stata codes in the Practical Guide to Trade Policy Analysis by using R.
Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research.
This book discusses modelling and analysis of Magnetic Resonance Imaging (MRI) data of the human brain.
This volume presents a selection of articles on statistical modeling and... Læs mere