Mathematical Methods for Physics (1版)

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本書所包的內容十分豐富，幾乎包含應用數學所有的重要課題，如Complex Variables, Partial Differential Equations, Special Functions, Fourier Transforms, Laplace Transforms etc。就如同作者在序中所言，本書適合研究生或優秀大學部學生研習，本書有些難度。作者寫書的方式是在每章每節開始時，先討論一個課題的基本概念及方法，而後舉出很多各式各樣不同的例子，其中有許多是來自古典力學、流体力學、量子力學、電磁學的重要例子，如果讀者能將本書全部念完並消化之，將受益不淺 目次 Chapter 1.COMPLEX VARIABLES. Chapter 2.CONFORMAL MAPPINGS. Chapter 3.ELLIPTICAL FUNCTIONS. Chapter 4.TENSOR CALCULUS. Chapter 5.Sturm-Liouville Theory. Chapter 6.GAMMA FUNCTION. Chapter 7.BESSEL FUNCTION. Chapter 8.LEGENDRE FUNCTIONS. Chapter 9.OTHER SPECIAL FUNCTIONS Chapter 10.Fourier SeriesLAPLACE TRANSFORM. Chapter 11.LAPLACE TRANSFORM. Chapter 12.MELLIN AND HANKEL TRANSFORM.I Chapter 14.NTEGRAL EQUATIONS.

Advanced Research Methods for the Social and Behavioral Sciences (1版)

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Description Written by an interdisciplinary team of global experts covering diverse research methods - including research design, research tools, and statistical techniques - this volume focuses on advanced research methods for anyone working in the social and behavioral sciences. The information needed to perform research in the laboratory, the field, or online is mapped out to provide specific applications and tools in applying each method. The issues surrounding reliability, validity, and obtaining consent are explained alongside detailed descriptions of the impact of pre-knowledge on participant behavior, the ways that researchers unintentionally influence participants, and tips on administering suspicion probes and debriefings. The book then lays out bio-physiological measures, eye-tracking methods and technologies, the construction of questionnaires, and reaction-time methodologies without assuming too much prior knowledge. The basics of Bayesian analysis, item response analysis, social network analysis, and meta-analysis are also summarised as the editors combine innovative methods and statistics to showcase how to perform quality research. A research methods volume written for advanced undergraduate students, graduate students, and those who already have a Ph.D. across the social and behavioral sciences Contains contributors that span the social and behavioral sciences to allow for a better understanding of performing research within and across multiple disciplines Supplies specific applications and tools to use in applying each method Table of Contents 1. A brief orientation to research methods and statistics for the social and behavioral sciences John E. Edlund and Austin Lee Nichols Part I. Performing Good Research: 2. Reliability and validity of measurement in the social and behavioral sciences Michael F. Wagner and John J. Skowronski 3. Performing research in the laboratory Austin Lee Nichols and John E. Edlund 4. Field research Sinikka Elliott 5. Using the internet for research Rosanna E. Guadagno Part II. Understanding Issues Present throughout the Research Process: 6. Issues in informed consent David S. Festinger, Karen L. Dugosh, Esther Choi and Chloe Sierka 7. Participant preknowledge and attitudes in research Elena C. Papanastasiou 8. Experimenter effects David B. Strohmetz 9. Suspicion probes and debriefing in the social and behavioral sciences Ginette C. Blackhart and Travis D. Clark Part III. The Social and Behavioral Scientist's Toolkit: 10. Physiological measures Eric J. Vanman and Michael C. Philipp 11. Eyetracking research Jeff B. Pelz 12. Questionnaire design Heather M. Stassen and Heather J. Carmack 13. Reaction time measures in the social and behavioral sciences: speed matters Jeremy D. Heider and Jason T. Reed Part IV. Emerging Issues in Social and Behavioral Science Research: 14. Replications and the social and behavioural sciences Courtney K. Soderberg and Timothy M. Errington 15. Research ethics for the social and behavioral sciences Ignacio Ferrero and Javier Pinto 16. Interdisciplinary research Rachel Adams Goertel, James P. Goertel and Mary G. Carey 17. Cross-cultural research Fons J. R. van de Vijver Part V. New Statistical Trends in the Social and Behavioral Sciences: 18. A gentle introduction to Bayesian statistics Milica Miočević and Rens van de Schoot 19. Development and applications of item response theory Clifford E. Hauenstein and Susan E. Embretson 20. Social network analysis Sebastian Leon Schorch and Eric Quintane 21. Meta analysis: an introduction Gregory D. Webster Appendix A: Metafor package R code for meta-analysis examples Index.