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A Primer on Statistical Distributions

Autor: Narayanaswamy Balakrishnan , V. B. Nevzorov

Número de Páginas: 322

Designed as an introduction to statistical distribution theory. * Includes a first chapter on basic notations and definitions that are essential to working with distributions. * Remaining chapters are divided into three parts: Discrete Distributions, Continuous Distributions, and Multivariate Distributions. * Exercises are incorporated throughout the text in order to enhance understanding of materials just taught.

Lagrangian Probability Distributions

Autor: Prem C. Consul , Felix Famoye

Número de Páginas: 363

Fills a gap in book literature Examines many new Lagrangian probability distributions and their applications to a variety of different fields Presents background mathematical and statistical formulas for easy reference Detailed bibliography and index Exercises in many chapters May be used as a reference text or in graduate courses and seminars on Distribution Theory and Lagrangian Distributions

A Primer for Benefit-cost Analysis

Autor: Richard O. Zerbe , Allen S. Bellas

Número de Páginas: 323

Benefit cost analysis (BCA) is the best technique for analyzing proposed or previously enacted projects to determine whether undertaking them is in the public interest, or for choosing between two or more mutually exclusive projects. An introduction to BCA for students as well as practitioners, this accessible volume describes the underlying economic theory and legal and philosophical foundations of BCA. BCA provides an objective framework around which discussion, correction and amendment can take place. Stated simply, it is the calculation of values for all the inputs and outputs from a project and then the subtraction of the first from the second. The authors goal here is to take the mystery out of the process. They discuss practical issues of market-based valuation and aggregation, non-market valuation, practical applications of general equilibrium models, issues in discounting, and the impacts of risk and uncertainty in BCA. They also provide a list of resources and case studies looking at ethanol and the use of cellular phones by drivers. Straightforward in style and cutting-edge in coverage, this volume will be highly usable both as a text and a reference. Advanced...

Primer for Data Analytics and Graduate Study in Statistics

Autor: Douglas Wolfe , Grant Schneider

Número de Páginas: 236

This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.

A Primer in Probability

Autor: Kathleen Subrahmaniam

Número de Páginas: 337

Somewhat revised/expanded new edition of a problem-oriented introductory undergraduate text, the first edition of which appeared about a decade ago. The author writes with courteous clarity, and imposes only modest demands upon the mathematical skills of her readers. Problems at the end of each of t

Transcriptome Analysis

Autor: Alessandro Cellerino , Michele Sanguanini

Número de Páginas: 196

The goal of this book is to be an accessible guide for undergraduate and graduate students to the new field of data-driven biology. Next-generation sequencing technologies have put genome-scale analysis of gene expression into the standard toolbox of experimental biologists. Yet, biological interpretation of high-dimensional data is made difficult by the lack of a common language between experimental and data scientists. By combining theory with practical examples of how specific tools were used to obtain novel insights in biology, particularly in the neurosciences, the book intends to teach students how to design, analyse, and extract biological knowledge from transcriptome sequencing experiments. Undergraduate and graduate students in biomedical and quantitative sciences will benefit from this text as well as academics untrained in the subject.

Distributions for Modeling Location, Scale, and Shape

Autor: Robert A. Rigby , Mikis D. Stasinopoulos , Gillian Z. Heller , Fernanda De Bastiani

Número de Páginas: 544

This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application. Key features: Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions. Comprehensive summary tables of the properties of the distributions. Discusses properties of...

Handbook of Statistical Distributions with Applications

Autor: K. Krishnamoorthy

Número de Páginas: 371

In the area of applied statistics, scientists use statistical distributions to model a wide range of practical problems, from modeling the size grade distribution of onions to modeling global positioning data. To apply these probability models successfully, practitioners and researchers must have a thorough understanding of the theory as well as a

Scientific Data Analysis with R

Autor: Azizur Rahman , Faruq Abdulla , Md. Moyazzem Hossain

Número de Páginas: 419

In an era marked by exponential growth in data generation and an unprecedented convergence of technology and healthcare, the intersection of biostatistics and data science has become a pivotal domain. This book is the ideal companion in navigating the convergence of statistical methodologies and data science techniques with diverse applications implemented in the open-source environment of R. It is designed to be a comprehensive guide, marrying the principles of biostatistics with the practical implementation of statistics and data science in R, thereby empowering learners, researchers, and practitioners with the tools necessary to extract meaningful knowledge from biological, health, and medical datasets. This book is intended for students, researchers, and professionals eager to harness the combined power of biostatistics, data science, and the R programming language while gathering vital statistical knowledge needed for cutting-edge scientists in all fields. It is useful for those seeking to understand the basics of data science and statistical analysis, or looking to enhance their skills in handling any simple or complex data including biological, health, medical, and industry ...

Continuous Bivariate Distributions

Autor: N. Balakrishnan , Chin Diew Lai

Número de Páginas: 714

Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions.

A Mathematical Primer for Social Statistics

Autor: John Fox

Número de Páginas: 185

The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

Autor: Joseph F. Hair, Jr. , G. Tomas M. Hult , Christian M. Ringle , Marko Sarstedt

Número de Páginas: 257

The third edition of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering the techniques of this approach in clear language. Authors Joseph H. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt use their years of conducting and teaching research to communicate the fundamentals of PLS-SEM in straightforward language to explain the details of this method, with limited emphasis on equations and symbols. A running case study on corporate reputation follows the different steps in this technique so readers can better understand the research applications. Learning objectives, review and critical thinking questions, and key terms help readers cement their knowledge. This edition has been thoroughly updated, featuring the latest version of the popular software package SmartPLS 3. New topics have been added throughout the text, including a thoroughly revised and extended chapter on mediation, recent research on the foundations of PLS-SEM, detailed descriptions of research summarizing the advantages as well as limitations of PLS-SEM, and extended coverage of advanced concepts and methods, such as out-of-sample...

Dealing With Data Pocket Primer

Autor: Oswald Campesato

Número de Páginas: 218

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of managing data using a variety of computer languages and applications. It is intended to be a fast-paced introduction to some basic features of data management and covers statistical concepts, data-related techniques, features of Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. Companion files with source code and color figures are available. FEATURES: Covers Pandas, RDBMS, NLP, data cleaning, SQL, and data visualization Introduces probability and statistical concepts Features numerous code samples throughout Includes companion files with source code and figures

Data Architecture: A Primer for the Data Scientist

Autor: W.h. Inmon , Daniel Linstedt

Número de Páginas: 378

Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: - Turn textual information into a form that can be analyzed by...

Cluster Analysis: A Primer Using R

Autor: Lior Rokach

Número de Páginas: 303

Cluster analysis is a fundamental data analysis task that aims to group similar data points together, revealing the inherent structure and patterns within complex datasets. This book serves as a comprehensive and accessible guide, taking readers on a captivating journey through the foundational principles of cluster analysis.At its core, the book delves deeply into various clustering algorithms, covering partitioning methods, hierarchical methods, and advanced techniques such as mixture density-based clustering, graph clustering, and grid-based clustering. Each method is presented with clear, concise explanations, supported by illustrative examples and hands-on implementations in the R programming language — a popular and powerful tool for data analysis and visualization.Recognizing the importance of cluster validation and evaluation, the book devotes a dedicated chapter to exploring a wide range of internal and external quality criteria, equipping readers with the necessary tools to assess the performance of clustering algorithms. For those eager to stay at the forefront of the field, the book also presents deep learning-based clustering methods, showcasing the remarkable...

A Primer in Financial Data Management

Autor: Martijn Groot

Número de Páginas: 302

A Primer in Financial Data Management describes concepts and methods, considering financial data management, not as a technological challenge, but as a key asset that underpins effective business management. This broad survey of data management in financial services discusses the data and process needs from the business user, client and regulatory perspectives. Its non-technical descriptions and insights can be used by readers with diverse interests across the financial services industry. The need has never been greater for skills, systems, and methodologies to manage information in financial markets. The volume of data, the diversity of sources, and the power of the tools to process it massively increased. Demands from business, customers, and regulators on transparency, safety, and above all, timely availability of high quality information for decision-making and reporting have grown in tandem, making this book a must read for those working in, or interested in, financial management. - Focuses on ways information management can fuel financial institutions' processes, including regulatory reporting, trade lifecycle management, and customer interaction - Covers recent regulatory...

Probability and Statistics by Example: Volume 2, Markov Chains: A Primer in Random Processes and Their Applications

Autor: Yu. M. Suhov , Mark Kelbert

Número de Páginas: 499

The subject is critical in many modern applications such as mathematical finance, quantitative management, insurance and actuarial studies.

A Primer to the 42 Most commonly used Machine Learning Algorithms (With Code Samples)

Autor: Murat Durmus

Número de Páginas: 220

Would you like a quick, profound overview of the most popular machine-learning algorithms? Then this is the book for you.! (This book is also suitable for Beginners) This book introduces you to the 42 most commonly used machine learning algorithms in an understandable way. Each algorithm is also demonstrated with a simple code example in Python. About the Author Murat Durmus is CEO and founder of AISOMA (a Frankfurt am Main (Germany) based company specializing in AI-based technology development and consulting) and Author of the book "Mindful AI - Reflections on Artificial Intelligence" and "INSIDE ALAN TURING." The following algorithms are covered in this book: • ADABOOST • ADAM OPTIMIZATION • AGGLOMERATIVE CLUSTERING • ARMA/ARIMA MODEL • BERT • CONVOLUTIONAL NEURAL NETWORK • DBSCAN • DECISION TREE • DEEP Q-LEARNING • EFFICIENTNET • FACTOR ANALYSIS OF CORRESPONDENCES • GAN • GMM • GPT-3 • GRADIENT BOOSTING MACHINE • GRADIENT DESCENT • GRAPH NEURAL NETWORKS • HIERARCHICAL CLUSTERING • HIDDEN MARKOV MODEL (HMM) • INDEPENDENT COMPONENT ANALYSIS • ISOLATION FOREST • K-MEANS • K-NEAREST NEIGHBOUR • LINEAR REGRESSION • LOGISTIC...

Computational Modeling Of Gene Regulatory Networks - A Primer

Autor: Hamid Bolouri

Número de Páginas: 341

This book serves as an introduction to the myriad computational approaches to gene regulatory modeling and analysis, and is written specifically with experimental biologists in mind. Mathematical jargon is avoided and explanations are given in intuitive terms. In cases where equations are unavoidable, they are derived from first principles or, at the very least, an intuitive description is provided. Extensive examples and a large number of model descriptions are provided for use in both classroom exercises as well as self-guided exploration and learning. As such, the book is ideal for self-learning and also as the basis of a semester-long course for undergraduate and graduate students in molecular biology, bioengineering, genome sciences, or systems biology./a

A Primer on Machine Learning in Subsurface Geosciences

Autor: Shuvajit Bhattacharya

Número de Páginas: 182

This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences.

Statistics in MATLAB

Autor: Moonjung Cho , Wendy L. Martinez

Número de Páginas: 280

This primer provides an accessible introduction to MATLAB version 8 and its extensive functionality for statistics. Fulfilling the need for a practical user's guide, the book covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB, presenting examples of how MATLAB can be used to analyze data. It explains how to determine what method should be used for analysis, and includes figures, visual aids, and access to a companion website with data sets and additional examples.

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

Autor: Joseph F. Hair

Número de Páginas: 329

"A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), by Hair, Hult, Ringle, and Sarstedt, provides a concise yet very practical guide to understanding and using PLS structural equation modeling (PLS-SEM). PLS-SEM is evolving as a statistical modeling technique and its use has increased exponentially in recent years within a variety of disciplines, due to the recognition that PLS-SEM's distinctive methodological features make it a viable alternative to the more popular covariance-based SEM approach. This text includes extensive examples on SmartPLS software, and is accompanied by multiple data sets that are available for download from the accompanying website (www.pls-sem.com). "--Publisher's website.

Multi-Asset Risk Modeling

Autor: Morton Glantz , Robert Kissell

Número de Páginas: 545

Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management. - Covers all asset classes - Provides mathematical theoretical explanations of risk as well as practical examples with empirical data - Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities

A Primer of Life Histories

Autor: Jeffrey A. Hutchings

Número de Páginas: 241

Life histories can be defined as the means by which individuals (or more precisely genotypes) vary their age- or stage-specific expenditures of reproductive effort in response to genetic, phenotypic, and environmental correlates of survival and fecundity. Life histories reflect the expression of traits most closely related to individual fitness, such as age and size at maturity, number and size of offspring, and the timing of the expression of those traits throughout an individual's life. In addition to addressing questions of fundamental importance to ecology and evolution, life-history research plays an integral role in species conservation and management. This accessible primer encompasses the basic concepts, theories, and applied elements of life history evolution, including patterns of trait variability, underlying mechanisms of plastic/evolutionary change, and the practical utility of life-history traits as metrics of species/population recovery, sustainable exploitation, and risk of extinction. Empirical examples are drawn from the entire spectrum of life. A Primer of Life Histories is designed for readers from a broad range of academic backgrounds and experience including...

A Primer in Econometric Theory

Autor: John Stachurski

Número de Páginas: 449

A concise treatment of modern econometrics and statistics, including underlying ideas from linear algebra, probability theory, and computer programming. This book offers a cogent and concise treatment of econometric theory and methods along with the underlying ideas from statistics, probability theory, and linear algebra. It emphasizes foundations and general principles, but also features many solved exercises, worked examples, and code listings. After mastering the material presented, readers will be ready to take on more advanced work in different areas of quantitative economics and to understand papers from the econometrics literature. The book can be used in graduate-level courses on foundational aspects of econometrics or on fundamental statistical principles. It will also be a valuable reference for independent study. One distinctive aspect of the text is its integration of traditional topics from statistics and econometrics with modern ideas from data science and machine learning; readers will encounter ideas that are driving the current development of statistics and increasingly filtering into econometric methodology. The text treats programming not only as a way to work...

A Primer on Experiments with Mixtures

Autor: John A. Cornell

Número de Páginas: 376

The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting with mixtures. Outlining useful techniques through an applied approach with examples from real research situations, the book supplies a comprehensive discussion of how to design and set up basic mixture experiments, then analyze the data and draw inferences from results. Drawing from his extensive experience teaching the topic at various levels, the author presents the mixture experiments in an easy-to-follow manner that is void of unnecessary formulas and theory. Succinct presentations explore key methods and techniques for carrying out basic mixture experiments, including: Designs and models for exploring the entire simplex factor space, with coverage of simplex-lattice and simplex-centroid designs, canonical polynomials, the plotting of individual residuals, and axial designs Multiple constraints on the component proportions in the form of lower and/or upper bounds, introducing L-Pseudocomponents,...

Dimensional Modeling: In a Business Intelligence Environment

Autor: Chuck Ballard , Daniel M. Farrell , Amit Gupta , Carlos Mazuela , Stanislav Vohnik , Ibm Redbooks

Número de Páginas: 670

In this IBM Redbooks publication we describe and demonstrate dimensional data modeling techniques and technology, specifically focused on business intelligence and data warehousing. It is to help the reader understand how to design, maintain, and use a dimensional model for data warehousing that can provide the data access and performance required for business intelligence. Business intelligence is comprised of a data warehousing infrastructure, and a query, analysis, and reporting environment. Here we focus on the data warehousing infrastructure. But only a specific element of it, the data model - which we consider the base building block of the data warehouse. Or, more precisely, the topic of data modeling and its impact on the business and business applications. The objective is not to provide a treatise on dimensional modeling techniques, but to focus at a more practical level. There is technical content for designing and maintaining such an environment, but also business content. For example, we use case studies to demonstrate how dimensional modeling can impact the business intelligence requirements for your business initiatives. In addition, we provide a detailed discussion ...

A Primer on Pseudorandom Generators

Autor: Oded Goldreich

Número de Páginas: 130

The primer assumes basic familiarity with the notion of efficient algorithms and with elementary probability theory, but provides a basic introduction to all notions that are actually used. as a result, the primer is essentially self-contained, although the interested reader is at times referred to other sources for more detail. --Book Jacket.

Mathematics Of Planet Earth: A Primer

Autor: Jochen Broecker , Ben Calderhead , Davoud Cheraghi , Colin Cotter , Darryl D Holm , Tobias Kuna , Beatrice Pelloni , Ted Shepherd , Hilary Weller

Número de Páginas: 371

Mathematics of Planet Earth (MPE) was started and continues to be consolidated as a collaboration of mathematical science organisations around the world. These organisations work together to tackle global environmental, social and economic problems using mathematics.This textbook introduces the fundamental topics of MPE to advanced undergraduate and graduate students in mathematics, physics and engineering while explaining their modern usages and operational connections. In particular, it discusses the links between partial differential equations, data assimilation, dynamical systems, mathematical modelling and numerical simulations and applies them to insightful examples.The text also complements advanced courses in geophysical fluid dynamics (GFD) for meteorology, atmospheric science and oceanography. It links the fundamental scientific topics of GFD with their potential usage in applications of climate change and weather variability. The immediacy of examples provides an excellent introduction for experienced researchers interested in learning the scope and primary concepts of MPE.

Normal and Student ́s t Distributions and Their Applications

Autor: Mohammad Ahsanullah , B.m. Golam Kibria , Mohammad Shakil

Número de Páginas: 163

The most important properties of normal and Student t-distributions are presented. A number of applications of these properties are demonstrated. New related results dealing with the distributions of the sum, product and ratio of the independent normal and Student distributions are presented. The materials will be useful to the advanced undergraduate and graduate students and practitioners in the various fields of science and engineering.

A Primer of Ecology with R

Autor: M. Henry Stevens

Número de Páginas: 404

Provides simple explanations of the important concepts in population and community ecology. Provides R code throughout, to illustrate model development and analysis, as well as appendix introducing the R language. Interweaves ecological content and code so that either stands alone. Supplemental web site for additional code.

Biostatistics for Population Health: A Primer

Autor: Lisa M. Sullivan

Número de Páginas: 184

Written for undergraduate and graduate students with little or no mathematical background, Biostatistics for Population Health: A Primer offers current and future health professionals a clear, and accessible approach to learning the basic tools and techniques necessary to conduct biostatistical analyses and the professional confidence to critically evaluate and interpret biostatistical findings. Each unit begins with a contemporary population health issue (e.g., the opioid crisis, physical inactivity among children, diabetes) and raises questions that require the use of techniques discussed in that unit. Each technique, in turn, is illustrated with realistic, contemporary examples (e.g. vaping) to pique student interest. By the end of the unit, students are encouraged to apply the techniques to address the questions that were raised.

A Primer on Complex Systems

Autor: Raúl Sánchez , David Newman

Número de Páginas: 416

The purpose of this book is to illustrate the fundamental concepts of complexity and complex behavior and the best methods to characterize this behavior by means of their applications to some current research topics from within the fields of fusion, earth and solar plasmas. In this sense, it is a departure from the many books already available that discuss general features of complexity. The book is divided in two parts. In the first part the most important properties and features of complex systems are introduced, discussed and illustrated. The second part discusses several instances of possible complex phenomena in magnetized plasmas and some of the analysis tools that were introduced in the first part are used to characterize the dynamics in these systems. A list of problems is proposed at the end of each chapter. This book is intended for graduate and post-graduate students with a solid college background in mathematics and classical physics, who intend to work in the field of plasma physics and, in particular, plasma turbulence. It will also be of interest to senior scientists who have so far approached these systems and problems from a different perspective and want a new...

A Primer on Risk Assessment Modelling

Autor: Aamir M. Fazil , Food And Agriculture Organization Of The United Nations

Número de Páginas: 68

This paper is written as an introduction to the concepts of microbial risk assessment in general, but with a seafood focus and greater emphasis on the quantitative approach. The risk of food-borne disease is a combination of the likelihood of exposure to the pathogen, the likelihood of infection or intoxication resulting in illness and the severity of the illness. In a system as complex as the production and consumption of food, many factors affect both the likelihood and severity. To manage food safety effectively, a systematic means of examining these factors is necessary.

A Primer on Machine Learning Applications in Civil Engineering

Autor: Paresh Chandra Deka

Número de Páginas: 281

Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book is to provide a broad overview of the available machine-learning techniques that can be utilized for solving civil engineering problems. The fundamentals of both theoretical and practical aspects are discussed in the domains of water resources/hydrological modeling, geotechnical engineering, construction engineering and management, and coastal/marine engineering. Complex civil engineering problems such as drought forecasting, river flow forecasting, modeling evaporation, estimation of dew point temperature, modeling compressive strength of concrete, ground water level forecasting, and significant wave height forecasting are also included. Features Exclusive information on machine learning and data analytics applications with respect to civil engineering Includes many machine learning techniques in numerous civil engineering disciplines Provides ideas on how and where to apply machine learning techniques for problem solving Covers water resources and hydrological modeling, geotechnical engineering, construction engineering...

A Primer on Scientific Programming with Python

Autor: Hans Petter Langtangen

Número de Páginas: 942

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the...

A Primer on Statistics for Business and Economics

Autor: Irwin Miller

Número de Páginas: 200

SAS® Coding Primer and Reference Guide

Autor: Connie Tang

Número de Páginas: 297

Although the web and online SAS® communities can provide volumes of information for programmers, these resources are often overwhelming and lack a simple path to guide coding SAS. This reference, however, does provide such a path from a data user’s standpoint vs. seeing things as a code writer. Written by an experienced SAS programmer, this book lets SAS coders easily find explanations and clarification to typical programming problems. This book presents practical real-world data analysis steps encountered by analysts in the field. These steps include the following: Getting to know raw data Understanding variables Getting data into SAS Creating new data variables Performing data manipulations, including sorting, ranking, grouping, subtotal, total, and percentage Statistical testing under a broad range of logical and conditional settings Data visualization Throughout this book, statements and codes are accompanied by thorough annotation. Line-by-line explanations ensure that all terms are clearly explained. Code examples and sample codes have broad usages. All the examples are related to highway transportation where the use of big data is exploding and presenting new challenges...

Statistical Distributions

Autor: Catherine Forbes , Merran Evans , Nicholas Hastings , Brian Peacock

Número de Páginas: 206

A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to serve as an authoritative guide on the application of statistical methods to research across various disciplines. The book provides a concise presentation of popular statistical distributions along with the necessary knowledge for their successful use in data modeling and analysis. Following a basic introduction, forty popular distributions are outlined in individual chapters that are complete with related facts and formulas. Reflecting the latest changes and trends in statistical distribution theory, the Fourth Edition features: A new chapter on queuing formulas that discusses standard formulas that often arise from simple queuing systems Methods for extending independent modeling schemes to the dependent case, covering techniques for generating complex distributions from simple distributions New coverage of conditional probability, including conditional expectations and joint and marginal distributions Commonly used tables associated with the normal (Gaussian), student-t, F and...

Spintronics

Autor: Jean-philippe Ansermet

Número de Páginas: 455

A sound understanding of magnetism, transport theory, spin relaxation mechanisms, and magnetization dynamics is necessary to engage in spintronics research. In this primer, special effort has been made to give straightforward explanations for these advanced concepts. This book will be a valuable resource for graduate students in spintronics and related fields. Concepts of magnetism such as exchange interaction, spin-orbit coupling, spin canting, and magnetic anisotropy are introduced. Spin-dependent transport is described using both thermodynamics and Boltzmann’s equation, including Berry curvature corrections. Spin relaxation phenomenology is accounted for with master equations for quantum spin systems coupled to a bath. Magnetic resonance principles are applied to describe spin waves in ferromagnets, cavity-mode coupling in antiferromagnets, and coherence phenomena relevant to spin qubits applications. Key Features: • A pedagogical approach to foundational concepts in spintronics with simple models that can be calculated to enhance understanding. • Nineteen chapters, each beginning with a historical perspective and ending with an outlook on current research. • 1200...