Professional C# 4.0 and .NET 4
This book starts by reviewing the overall architecture of .NET in order to give you the background you need to be able to write managed code. After that, the book is divided into a number of sections that cover both the C# language and its application in a variety of areas.
Part I: The C# Language gives a good grounding in the C# language for experienced programmers. You start by looking at basic syntax and data types. Objects, types, inheritance, generics, arrays, tuples, operators, casts, delegates, lambdas, events, strings, regular expressions, collections, Language Integrated, Query (LINQ), Dynamic Language Extensions, memory management, pointers, reflection, errors, and exceptions are all covered.
Part II: Visual Studio looks at Visual Studio 2010 (the best way to use the tool to build applications based on the .NET Framework 4) and deploying your projects.
Part III: Foundation looks at .NET assemblies, instrumentation, security, threading, tasks, synchronization, localization, System.Transactions, networking, interop, XAML, Managed Extensibility Framework, Manipulating Files and the Registry, transactions, building Windows services, and generating your own libraries as assemblies.
Part IV: Data covers accessing databases with ADO.NET, ADO.NET Entity Framework, data services, support in .NET for XML, and the .NET features of SQL Server 2008.
Part V: Presentation shows how to build applications based on the Windows Presentation Foundation and Silverlight, and covers writing components that will run on web sites. It also has coverage on building Windows Forms applications in as well as ASP.NET and ASP.NET MVC. Part VI: Communication covers services for platform-independent communication using the Windows Communication Foundation (WCF). With Message Queuing, asynchronous disconnected communication is shown. This section looks at utilizing the Windows Workflow Foundation 4, peer to peer networking, and creating syndication feeds.
Introduction to Linear Regression Analysis
Praise for the Fourth Edition
"As with previous editions, the authors have produced a leading textbook on regression."
Journal of the American Statistical Association
A comprehensive and up-to-date introduction to the fundamentals of regression analysis
Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.
Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including:
- A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models
- Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model
- Tests on individual regression coefficients and subsets of coefficients
- Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data.
In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material.
Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.