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Structural Engineer's Pocket Book 3rd Edition
The hugely useful Structural Engineer’s Pocket Book is now overhauled and revised in line with the Eurocodes. It forms a comprehensive pocket reference guide for professional and student structural engineers, especially those taking the IStructE Part 3 exam. With stripped-down basic material—tables, data, facts, formulae, and rules of thumb—it is directly usable for scheme design by structural engineers in the office, in transit, or on site. It brings together data from many different sources, and delivers a compact source of job-simplifying and time-saving information at an affordable price. It acts as a reliable first point of reference for information that is needed on a daily basis. This third edition is referenced throughout to the structural Eurocodes. After giving general information and details on actions on structures, it runs through reinforced concrete, steel, timber, and masonry. * Provides essential data on steel, concrete, masonry, timber, and other main materials. * Pulls together material from a variety of sources for everyday work. * Serves as a first point of reference for structural and civil engineers. A core structural engineering book, Structural Engineer's Pocket Book: Eurocodes, Third Edition benefits both students and industry professionals.
Soil Behavior And Critical State Soil Mechanics
Soils can rarely be described as ideally elastic or perfectly plastic and yet simple elastic and plastic models form the basis for the most traditional geotechnical engineering calculations. With the advent of cheap powerful computers the possibility of performing analyses based on more realistic models has become widely available. One of the aims of this book is to describe the basic ingredients of a family of simple elastic-plastic models of soil behavior and to demonstrate how such models can be used in numerical analyses. Such numerical analyses are often regarded as mysterious black boxes but a proper appreciation of their worth requires an understanding of the numerical models on which they are based. Though the models on which this book concentrates are simple, understanding of these will indicate the ways in which more sophisticated models will perform.
Design Handbook for Reinforced Concrete Elements
This book is the essential and easy-to-use guide for all students and practicing engineers who need to understand and design concrete structures. This second edition of the book is updated to include the revised Concrete Structures and Loading Codes. It develops: simple theory to help the student understand fundamental principles ; design formulas from first principles ; and design charts for all aspects of reinforced concrete design. It incorporates: many design samples to help the user understand the design processes ; the current 2001 AS3600 Concrete Structures Code requirements for deflection and crack control in beams and slabs ; high strength concrete column design charts with concrete strengths of 65, 80, 100 and 120MPa used in modern design and expected to be included in the next main revision of the code.
Data Analysis Using Regression and Multilevel/Hierarchical Models
Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.
Stata: Software for Statistics and Data Science
Features: Linear models: regression • censored outcomes • endogenous regressors • bootstrap, jackknife, and robust and cluster–robust variance • instrumental variables • three-stage least squares • constraints • quantile regression • GLS • more. Panel/longitudinal data: random and fixed effects with robust standard errors • linear mixed models • random-effects probit • GEE • random- and fixed-effects Poisson • dynamic panel-data models • instrumental variables • panel unit-root tests • more. Multilevel mixed-effects models: continuous, binary, count, and survival outcomes • two-, three-, and higher-level models • generalized linear models • nonlinear models • random intercepts • random slopes • crossed random effects • BLUPs of effects and fitted values • hierarchical models • residual error structures • DDF adjustments • support for survey data • more. Binary, count, and limited outcomes: logistic, probit, tobit • Poisson and negative binomial • conditional, multinomial, nested, ordered, rank-ordered, and stereotype logistic • multinomial probit • zero-inflated and left-truncated count models • selection models • marginal effects • more. Extended regression models (ERMs): combine endogenous covariates, sample selection, and nonrandom treatment in models for continuous, interval-censored, binary, and ordinal outcomes • more.
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