the Nest of Students

Conrad Carlberg ... 272 pages - Publisher: Que Publishing; 1st edition (November, 2016) ... Language: English - ISBN-10: 0789757850 - ISBN-13: 978-0789757852 ...

Microsoft Excel can perform many statistical analyses, but thousands of business users and analysts are now reaching its limits. R, in contrast, can perform virtually any imaginable analysis—if you can get over its learning curve. In R for Microsoft® Excel Users, Conrad Carlberg shows exactly how to get the most from both programs. Drawing on his immense experience helping organizations apply statistical methods, Carlberg reviews how to perform key tasks in Excel, and then guides you through reaching the same outcome in R—including which packages to install and how to access them. Carlberg offers expert advice on when and how to use Excel, when and how to use R instead, and the strengths and weaknesses of each tool. Writing in clear, understandable English, Carlberg combines essential statistical theory with hands-on examples reflecting real-world challenges. By the time you’ve finished, you’ll be comfortable using R to solve a wide spectrum of problems—including many you just couldn’t handle with Excel. Contents: • Smoothly transition to R and its radically different user interface • Leverage the R community’s immense library of packages • Efficiently move data between Excel and R • Use R’s DescTools for descriptive statistics, including bivariate analyses • Perform regression analysis and statistical inference in R and Excel • Analyze variance and covariance, including single-factor and factorial ANOVA • Use R’s mlogit package and glm function for Solver-style logistic regression • Analyze time series and principal components with R and Excel.

Conrad Carlberg ... 368 pages - Publisher: Que Publishing; 1st edition (May, 2016) ... Language: English - ISBN-10: 0789756552 - ISBN-13: 978-0789756558 ...

Braja M. Das ... 944 pages - Publisher: Cengage Learning; 8th edition (January, 2015) ... Language: English - ISBN-10: 1305081552 - ISBN-13: 978-1305081550 ...

Master the fundamental concepts and applications of foundation analysis design with Principles of Foundation Engineering. This market leading text maintains a careful balance of current research and practical field applications, offers a wealth of worked out examples and figures that show you how to do the work you will be doing as a civil engineer, and helps you develop the judgment you'll need to properly apply theories and analysis to the evaluation of soils and foundation design.

Xin Yan, Xiao Gang Su ... 328 pages - Publisher: World Scientific; 1st edition (June, 2009) ... Language: English - ISBN-10: 9812834109 - ISBN-13: 978-9812834102 ...

This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields.

Giuseppe Ciaburro, Balaji Venkateswaran ... 270 pages - Publisher: Packt Publishing; (September, 2017) ... Language: English - ISBN-10: 1788397878 - ISBN-13: 978-1788397872 ...

Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book.

S. Chakraverty, Susmita Mall ... 157 pages - Publisher: CRC Press; (July, 2017) ... Language: English - ASIN: B0744Q3RW2 by Amazon.

Differential equations play a vital role in the fields of engineering and science. Problems in engineering and science can be modeled using ordinary or partial differential equations. Analytical solutions of differential equations may not be obtained easily, so numerical methods have been developed to handle them. Machine intelligence methods, such as Artificial Neural Networks (ANN), are being used to solve differential equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This book shows how computation of differential equation becomes faster once the ANN model is properly developed and applied.