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Databases & Big Data - Data Modeling for the Sciences: Applications, Basics, Computations

Description

Book Synopsis: 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.

Details

Are you a student or researcher looking to develop your data analysis skills? Look no further! Introducing Data Modeling for the Sciences: Applications, Basics, Computations. In today's data-driven world, it is essential to have a solid understanding of probabilistic data modeling beyond the basics. This comprehensive guide is tailored specifically for students and researchers in the sciences, ready to take their data analysis to the next level.

From basic probabilistic concepts to modeling paradigms, this textbook covers it all. Learn about dynamical systems, likelihoods, and Bayesian inference, all crucial skills in scientific research. With practical examples and numerous exercises, you'll get hands-on experience that will solidify your understanding. Whether you're taking a course or studying on your own, this self-contained text is your go-to resource.

Why settle for just learning about p-values and fitting residuals when you can explore the fascinating world of data modeling? Don't miss out on this opportunity to enhance your academic career. Get your copy of Data Modeling for the Sciences now and unlock the secrets of effective data analysis!

Click here to get your copy of Data Modeling for the Sciences: Applications, Basics, Computations today and start your journey towards becoming a data analysis expert.

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