Data Modeling for the Sciences: Applications, Basics, Computations

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Steve Pressé (Arizona State University) Ioannis Sgouralis (University of Tennessee, Knoxville)

Data Modeling for the Sciences

Applications, Basics, Computations

Steve Pressé (Arizona State University), Ioannis Sgouralis (University of Tennessee, Knoxville)

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English

Cambridge University Press
31 August 2023

Data analysis: general; Scientific equipment, experiments & techniques; Astronomical observation: observatories, equipment & methods; Applied physics; Data capture & analysis

With the increasing prevalence of big data and sparse data, and rapidly growing data-centric approaches to scientific research, students must develop effective data analysis skills at an early stage of their academic careers. This detailed guide to data modeling in the sciences is ideal for students and researchers keen to develop their understanding of probabilistic data modeling beyond the basics of p-values and fitting residuals. The textbook begins with basic probabilistic concepts, models of dynamical systems and likelihoods are then presented to build the foundation for Bayesian inference, Monte Carlo samplers and filtering. Modeling paradigms are then seamlessly developed, including mixture models, regression models, hidden Markov models, state-space models and Kalman filtering, continuous time processes and uniformization. The text is self-contained and includes practical examples and numerous exercises. This would be an excellent resource for courses on data analysis within the natural sciences, or as a reference text for self-study.

By: Steve Pressé (Arizona State University), Ioannis Sgouralis (University of Tennessee, Knoxville)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Weight: 1.044kg
ISBN: 9781009098502
ISBN 10: 1009098500
Pages: 346
Publication Date: 31 August 2023
Audience: College/higher education , Further / Higher Education
Format: Hardback
Publisher's Status: Active

Steve Pressé is Professor of Physics and Chemistry at Arizona State University, Tempe. His research lies at the interface of Biophysics and Chemical Physics with an emphasis on inverse methods. He is a recipient of a National Science Foundation CAREER award and a Research Corporation 'Molecules come to Life' Fellow. He has extensive experience in teaching data analysis and modeling at both undergraduate and graduate level with funding from the NIH and NSF in data modelling applied to the interpretation of single molecule dynamics and image analysis. Ioannis Sgouralis is Assistant Professor of Mathematics at the University of Tennessee, Knoxville. His research is focused on computational modeling and applied mathematics, particularly the integration of data acquisition with data analysis across biology, chemistry, and physics.