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Use Python without extensive programming knowledge + Get started with modern tools, including Jupyter notebooks and Visual Studio code + Use pandas to acquire, clean, and analyze data and replace typical Excel calculations + Automate tedious tasks like consolidation of Excel workbooks and production of Excel reports + Use xlwings to build interactive Excel tools that use Python as a calculation engine + Connect Excel to databases and CSV files and fetch data from the internet using Python code + Use Python as a single tool to replace VBA, Power Query, and Power Pivot.

Future microwave, wireless communication systems, computer chip designs, and sensor systems will require miniature fabrication processes in the order of nanometers or less as well as the fusion of various material technologies to produce composites consisting of many different materials. This requires distinctly multidisciplinary collaborations, implying that specialized approaches will not be able to address future world markets in communication, computer, and electronic miniaturized products.

Anticipating that many students lack specialized simultaneous training in magnetism and magnetics, as well as in other material technologies, Magnetics, Dielectrics, and Wave Propagation with MATLABR Codes avoids application-specific descriptions, opting for a general point of view of materials per se. Specifically, this book develops a general theory to show how a magnetic system of spins is coupled to acoustic motions, magnetoelectric systems, and superconductors. Phenomenological approaches are connected to atomic-scale formulations that reduce complex calculations to essential forms and address basic interactions at any scale of dimensionalities. With simple and clear coverage of everything from first principles to calculation tools, the book revisits fundamentals that govern magnetic, acoustic, superconducting, and magnetoelectric motions at the atomic and macroscopic scales, including superlattices. Constitutive equations in Maxwell’s equations are introduced via general free energy expressions which include magnetic parameters as well as acoustic, magnetoelectric, semiconductor, and superconducting parameters derived from first principles. More importantly, this book facilitates the derivation of these parameters, as the dimensionality of materials is reduced toward the microscopic scale, thus introducing new concepts. The deposition of ferrite films at the atomic scale complements the approach toward the understanding of the physics of miniaturized composites. Thus, a systematic formalism of deriving the permeability or the magnetoelectric coupling tensors from first principles, rather than from an ad hoc approach, bridges the gap between microscopic and macroscopic principles as applied to wave propagation and other applications.

Like its bestselling predecessor, Multilevel Modeling Using R, Third Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment.

After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single-level and multilevel data.

The third edition of the book includes several new topics that were not present in the second edition. Specifically, a new chapter has been included, focussing on fitting multilevel latent variable modeling in the R environment. With R, it is possible to fit a variety of latent variable models in the multilevel context, including factor analysis, structural models, item response theory, and latent class models. The third edition also includes new sections in Chapter 11 describing two useful alternatives to standard multilevel models, fixed effects models and generalized estimating equations. These approaches are particularly useful with small samples and when the researcher is interested in modeling the correlation structure within higher-level units (e.g., schools). The third edition also includes a new section on mediation modeling in the multilevel context, in Chapter 11.

This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research.