Aircraft Structures for Engineering Students

Aircraft Structures for Engineering Students
Author: Thomas Henry Gordon Megson
Publisher: Hodder Education
Total Pages: 0
Release: 1990
Genre: Aeroelasticity
ISBN: 9780713136814

This book provides a self-contained course in aircraft structures which contains not only the fundamentals of elasticity and aircraft structural analysis but also the associated topics of airworthiness and aeroelasticity.

An Introduction to Categorical Data Analysis

An Introduction to Categorical Data Analysis
Author: Alan Agresti
Publisher: John Wiley & Sons
Total Pages: 393
Release: 2018-10-11
Genre: Mathematics
ISBN: 1119405270

A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.

Quantities, Units and Symbols in Physical Chemistry

Quantities, Units and Symbols in Physical Chemistry
Author: International Union of Pure and Applied Chemistry. Physical and Biophysical Chemistry Division
Publisher: Royal Society of Chemistry
Total Pages: 240
Release: 2007
Genre: Reference
ISBN: 0854044337

Prepared by the IUPAC Physical Chemistry Division this definitive manual, now in its third edition, is designed to improve the exchange of scientific information among the readers in different disciplines and across different nations. This book has been systematically brought up to date and new sections added to reflect the increasing volume of scientific literature and terminology and expressions being used. The Third Edition reflects the experience of the contributors with the previous editions and the comments and feedback have been integrated into this essential resource. This edition has been compiled in machine-readable form and will be available online.

Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R
Author: Kandethody M. Ramachandran
Publisher: Elsevier
Total Pages: 825
Release: 2014-09-14
Genre: Mathematics
ISBN: 012417132X

Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner.This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students.Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. - Step-by-step procedure to solve real problems, making the topic more accessible - Exercises blend theory and modern applications - Practical, real-world chapter projects - Provides an optional section in each chapter on using Minitab, SPSS and SAS commands - Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

Introduction to Probability Models

Introduction to Probability Models
Author: Sheldon M. Ross
Publisher: Academic Press
Total Pages: 801
Release: 2006-12-11
Genre: Mathematics
ISBN: 0123756871

Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes. There are two approaches to the study of probability theory. One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this text. The book begins by introducing basic concepts of probability theory, such as the random variable, conditional probability, and conditional expectation. This is followed by discussions of stochastic processes, including Markov chains and Poison processes. The remaining chapters cover queuing, reliability theory, Brownian motion, and simulation. Many examples are worked out throughout the text, along with exercises to be solved by students. This book will be particularly useful to those interested in learning how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. Ideally, this text would be used in a one-year course in probability models, or a one-semester course in introductory probability theory or a course in elementary stochastic processes. New to this Edition: - 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains - Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams - Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, and test bank - Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field Hallmark features: - Superior writing style - Excellent exercises and examples covering the wide breadth of coverage of probability topics - Real-world applications in engineering, science, business and economics

Statistical Parametric Mapping: The Analysis of Functional Brain Images

Statistical Parametric Mapping: The Analysis of Functional Brain Images
Author: William D. Penny
Publisher: Elsevier
Total Pages: 689
Release: 2011-04-28
Genre: Psychology
ISBN: 0080466508

In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible

Applied Multivariate Statistical Analysis (Classic Version)

Applied Multivariate Statistical Analysis (Classic Version)
Author: Richard A. Johnson
Publisher: Pearson
Total Pages: 808
Release: 2018-03-18
Genre: Multivariate analysis
ISBN: 9780134995397

This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.

Practical Research

Practical Research
Author: Paul D. Leedy
Publisher:
Total Pages: 384
Release: 2013-07-30
Genre: Research
ISBN: 9781292021171

For undergraduate or graduate courses that include planning, conducting, and evaluating research. A do-it-yourself, understand-it-yourself manual designed to help students understand the fundamental structure of research and the methodical process that leads to valid, reliable results. Written in uncommonly engaging and elegant prose, this text guides the reader, step-by-step, from the selection of a problem, through the process of conducting authentic research, to the preparation of a completed report, with practical suggestions based on a solid theoretical framework and sound pedagogy. Suitable as the core text in any introductory research course or even for self-instruction, this text will show students two things: 1) that quality research demands planning and design; and, 2) how their own research projects can be executed effectively and professionally.

Handbook of Sports Medicine and Science

Handbook of Sports Medicine and Science
Author: Dennis J. Caine
Publisher: John Wiley & Sons
Total Pages: 418
Release: 2013-07-18
Genre: Medical
ISBN: 1118357574

This new volume in the Handbook of Sports Medicine and Science series, published in conjunction with the Medical Commission of the International Olympic Committee, offers comprehensive and practical guidance on the training and medical care of competitive gymnasts. Written and edited by leading trainers, team doctors, coaches and other professionals with unparalleled experience in elite gymnastics, this book covers all the key aspects of caring for gymnasts, minimizing the unique risks these athletes face, and treating injuries when they happen. The book is organized into 4 sections covering: The evolution of gymnastics Growth and development Training and performance Sports medicine Individual chapters cover key topics such as energy needs and body weight management; biomechanics; psychology; the epidemiology of gymnastic injuries; treatment and rehabilitation of common injuries; injury prevention; and more. Endorsed by the International Gymnastics Federation (FIG), no other book offers such an in-depth look at the unique considerations and challenges that affect the growth, performance, training, and medical care of athletes in this demanding sport.