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  • Statistical Mechanics
    Statistical Mechanics

    Statistical Mechanics, Fourth Edition, explores the physical properties of matter based on the dynamic behavior of its microscopic constituents.This valuable textbook introduces the reader to the historical context of the subject before delving deeper into chapters about thermodynamics, ensemble theory, simple gases theory, Ideal Bose and Fermi systems, statistical mechanics of interacting systems, phase transitions, and computer simulations.In the latest revision, the book's authors have updated the content throughout, including new coverage on biophysical applications, updated exercises, and computer simulations.This updated edition will be an indispensable to students and researchers of statistical mechanics, thermodynamics, and physics.

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  • Statistical Thermodynamics
    Statistical Thermodynamics

    The renowned Oxford Chemistry Primers series, which provides focused introductions to a range of important topics in chemistry, has been refreshed and updated to suit the needs of today's students, lecturers, and postgraduate researchers.The rigorous, yet accessible, treatment of each subject area is ideal for those wanting a primer in a given topic to prepare them for more advanced study or research. The learning features provided, including end of book problems and online multiple-choice questions, encourage active learning and promote understanding.Furthermore, frequent diagrams and margin notes help to enhance a student's understanding of these essential areas of chemistry. Statistical Thermodynamics gives a concise and accessible account of this fundamental topic by emphasizing the underlying physical chemistry, and using this to introduce the mathematics in an approachable way.The material is presented in short, self-contained sections making it flexible to teach and learn from, and concludes with the application of the theory to real systems. Online Resource Centre: The Online Resource Centre to accompany Statistical Thermodynamics features: For registered adopters of the text: · Figures from the book available to download For students: · Worked solutions to the questions and problems at the end of the book. · Multiple-choice questions for self-directed learning

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  • Statistical Epidemiology
    Statistical Epidemiology

    Statistics are a vital skill for epidemiologists and form an essential part of clinical medicine and public health.This textbook introduces students to statistical epidemiology methods in a carefully structured and accessible format.With clearly defined learning outcomes, the suggested chapter orders can be tailored to the needs of students at both undergraduate and graduate level from a range of academic backgrounds.The book covers study design, measuring disease, bias, error, analysis and modelling and is illustrated with figures, focus boxes, study questions and examples applicable to everyday clinical problems.Drawing on the authors' extensive teaching experience, the text provides an introduction to core statistical epidemiology that will be a valuable resource for students and lecturers in health and medical sciences and applied statistics, health staff, clinical researchers and data managers.

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  • Statistical Inference
    Statistical Inference

    This book builds theoretical statistics from the first principles of probability theory.Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts.Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background.It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

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  • Is Lilith a statistical goddess?

    Lilith is not a statistical goddess. In various mythologies and belief systems, Lilith is often portrayed as a figure associated with themes of independence, rebellion, and sexuality. She is not typically associated with statistical concepts or principles. Instead, she is more commonly linked to themes of feminism, empowerment, and the supernatural.

  • What are statistical accounts?

    Statistical accounts are detailed records or summaries of numerical data related to a specific topic or area. They provide information on various aspects such as demographics, economics, social trends, and other relevant statistics. Statistical accounts are used by researchers, policymakers, and businesses to analyze trends, make informed decisions, and understand the characteristics of a particular population or phenomenon. These accounts are often compiled by government agencies, research institutions, or organizations to provide a comprehensive overview of a subject based on quantitative data.

  • What are statistical measures?

    Statistical measures are numerical values that summarize and describe a dataset. They provide insights into the characteristics of the data, such as central tendency, dispersion, and shape of the distribution. Common statistical measures include mean, median, mode, standard deviation, and range. These measures help in understanding the data, making comparisons, and drawing conclusions based on the information provided.

  • Is the goddess Selene Artemis?

    No, the goddess Selene is not Artemis. In Greek mythology, Selene is the goddess of the moon, while Artemis is the goddess of the hunt, wilderness, and childbirth. Although they are both associated with the night and the moon, they are distinct deities with their own unique attributes and roles in mythology. Selene is often depicted as driving a chariot across the night sky, while Artemis is known for her skill in hunting and her association with wild animals.

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  • Statistical Physics
    Statistical Physics

    The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B.H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition E. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A. C. Phillips Computing for Scientists R. J. Barlow and A. R. Barnett Statistical Physics, Second Edition develops a unified treatment of statistical mechanics and thermodynamics, which emphasises the statistical nature of the laws of thermodynamics and the atomic nature of matter.Prominence is given to the Gibbs distribution, leading to a simple treatment of quantum statistics and of chemical reactions.Undergraduate students of physics and related sciences will find this a stimulating account of the basic physics and its applications.Only an elementary knowledge of kinetic theory and atomic physics, as well as the rudiments of quantum theory, are presupposed for an understanding of this book.Statistical Physics, Second Edition features: A fully integrated treatment of thermodynamics and statistical mechanics. A flow diagram allowing topics to be studied in different orders or omitted altogether. Optional "starred" and highlighted sections containing more advanced and specialised material for the more ambitious reader. Sets of problems at the end of each chapter to help student understanding.Hints for solving the problems are given in an Appendix.

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  • Statistical Consulting
    Statistical Consulting

    The motivation for this book arose from the statistical consulting course that we have taught regularly for several years.In that course, we focus on the themes: • Understanding the statistical consulting "process" • Developing effective communication skills • Obtaining experience through case studies.In reality, there is no substitute for consulting directly with a client and for this interaction to be effective, good communication skills are essential.Unfortunately, this aspect of a statistician's training is often neglected and statistics graduates have little choice but to learn these skills on the job.One of the purposes of this book is to address this need.Statistical consulting occurs in a diverse range of environments and for tackling real-life statistical problems, the statistician needs to have a strong interest in the scientific method.History itself provides the best examples for developing this interest and so we begin with a brief historical voyage in Chapter 1.There's no time like the present, of course, and in the remainder of this chapter we describe some of the environments in which statistical consulting plays a major role.A detailed discussion on verbal and written communication skills that will be required in a consulting environment is presented in Chapter 2.

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  • Introductory Statistical Mechanics
    Introductory Statistical Mechanics

    This book explains the ideas and techniques of statistical mechanics-the theory of condensed matter-in a simple and progressive way.The text starts with the laws of thermodynamics and simple ideas of quantum mechanics.The conceptual ideas underlying the subject are explained carefully; the mathematical ideas are developed in parallel to give a coherent overall view.The text is illustrated with examples not just from solid state physics, but also from recent theories of radiation from black holes and recent data on the background radiation from the Cosmic background explorer.In this second edition, slightly more advanced material on statistical mechanics is introduced, material which students should meet in an undergraduate course.As a result the new edition contains three more chapters on phase transitions at an appropriate level for an undergraduate student.There are plenty of problems at the end of each chapter, and brief model answers are provided for odd-numbered problems.From reviews of the first edition: '...Introductory Statistical Mechanics is clear and crisp and takes advantage of the best parts of the many approaches to the subject' Physics Today

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  • Theoretical Statistical Optics
    Theoretical Statistical Optics

    This monograph overviews classic and recent developments in theoretical statistical optics in connection with stationary and non-stationary (pulsed) optical source characterization and modeling, discusses various phenomena occurring with random light propagating in free space, on its interaction with optical systems, extended media and particulate collections.The text includes scalar, beam-like and general electromagnetic treatment of light.A brief statistical description of four fundamental experiments relating to random light: spatial and temporal field interference, intensity interferometry and phase conjugation, is also included in order to relate the analytical descriptions with practical observations.Rigorous mathematical methods for statistical manipulation of light sources useful for remote shaping of its various average properties, enhanced image resolution, optimized transmission in random media and for other applications are introduced.For illustration of efficient ways for manipulation of light polarization the generalized Stokes-Mueller calculus is applied for description of interaction of beam-like fields with classic and currently popular devices of polarization optics, including a spatial light modulator.Random light plays a special role in the image formation process.Three imaging modalities including the classic intensity-based system with structured source correlations, the polarization-based imaging system and the ghost interference approach are discussed in detail.Theoretical aspects of potential scattering of light from weakly scattering media are considered under a very broad range of assumptions: scalar/electromagnetic incident light, deterministic/random light/media, single/particulate media.Then, problems and methods in light characterization on interaction with extended, turbulent-like natural media, such as the Earth's atmosphere, oceans and soft bio-tissues that are currently widely used for communication, remote sensing and imaging purposes in these media, are provided.

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  • What is statistical conservative testing?

    Statistical conservative testing refers to a method of hypothesis testing that is designed to minimize the risk of making a Type I error (incorrectly rejecting a true null hypothesis). This approach involves setting a more stringent significance level or using more conservative statistical methods to ensure that only strong evidence can lead to rejecting the null hypothesis. By being more cautious in accepting alternative hypotheses, statistical conservative testing helps to reduce the chances of drawing incorrect conclusions from the data.

  • What is the statistical charge?

    The statistical charge refers to the concept in statistical mechanics that describes the distribution of particles in a system according to their energy levels. It is used to calculate the probability of finding a particle in a particular energy state, and is essential for understanding the behavior of systems at the microscopic level. The statistical charge is a fundamental concept in statistical mechanics and is used to derive important thermodynamic properties of a system, such as entropy and free energy.

  • What statistical distribution is present here?

    The statistical distribution present here is a normal distribution. This can be inferred from the bell-shaped curve of the data, where the majority of the values cluster around the mean with symmetrical tails on either side. The normal distribution is commonly seen in natural phenomena and is characterized by its mean and standard deviation, which can be used to make predictions about the data.

  • Which statistical method is best suited?

    The best statistical method depends on the specific research question and the type of data being analyzed. For example, if the research question involves comparing the means of two or more groups, then analysis of variance (ANOVA) may be the best method. On the other hand, if the research question involves examining the relationship between two continuous variables, then linear regression may be more appropriate. It is important to carefully consider the research question and the characteristics of the data before selecting the most suitable statistical method.

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