The.Hottest

Syouji Nakamura, Toshio Nakagawa ... 316 pages - Publisher: World Scientific Publishing Company (November, 2009) ... Language: English - ISBN-10: 9814277436 - ISBN-13: 978-9814277433 ...

Reliability theory and applications become major concerns of engineers and managers engaged in making high quality products and designing highly reliable systems. This book aims to survey new research topics in reliability theory and useful applied techniques in reliability engineering. Our research group in Nagoya, Japan has continued to study reliability theory and applications for more than twenty years, and has presented and published many good papers at international conferences and in journals. This book focuses mainly on how to apply the results of reliability theory to practical models. Theoretical results of coherent, inspection, and damage systems are summarized methodically, using the techniques of stochastic processes. There exist optimization problems in computer and management sciences and engineering. It is shown that such problems as computer, information and network systems are solved by using the techniques of reliability. Furthermore, some useful techniques applied to the analysis of stochastic models in management science and plants are shown. The reader will learn new topics and techniques, and how to apply reliability models to actual ones. The book will serve as an essential guide to a subject of study for graduate students and researchers and as a useful guide for reliability engineers engaged not only in maintenance work but also in management and computer works.

Wes McKinney ... 544 pages - Publisher: O'Reilly Media; 2nd edition (October, 2017) ... Language: English - ISBN-10: 1491957662 - ISBN-13: 978-1491957660 ... 

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing * Learn basic and advanced features in NumPy (Numerical Python) * Get started with data analysis tools in the pandas library * Use flexible tools to load, clean, transform, merge, and reshape data * Create informative visualizations with matplotlib * Apply the pandas groupby facility to slice, dice, and summarize datasets * Analyze and manipulate regular and irregular time series data * Learn how to solve real-world data analysis problems with thorough, detailed examples.

A. J. M. Ferreira ... 235 pages - Publisher: Springer; (December, 2008) ... Language: English - ISBN-10: 1402091990 - ISBN-13: 978-1402091995 ...

This book illustrates how MATLAB compact and powerful programming framework can be very useful in the finite element analysis of solids and structures. The book shortly introduces finite element concepts and an extensive list of MATLAB codes for readers to use and modify. The book areas range from very simple springs and bars to more complex beams and plates in static bending, free vibrations and buckling problems. This book intend to supply readers with some MATLAB codes for finite element analysis of solids and structures. After a short introduction to MATLAB, the book illustrates the finite element implementation of some problems by simple scripts and functions. The following problems are discussed: • Discrete systems, such as springs and bars • Beams and frames in bending in 2D and 3D • Plane stress problems • Plates in bending • Free vibration of Timoshenko beams and Mindlin plates, including laminated composites • Buckling of Timoshenko beams and Mindlin plates The book does not intends to give a deep insight into the finite element details, just the basic equations so that the user can modify the codes. The book was prepared for undergraduate science and engineering students, although it may be useful for graduate students.

Alan Agresti ... 400 pages - Publisher: Wiley-Interscience; 2nd edition (March, 2007) ... Language: English - ISBN-10: 0471226181 - ISBN-13: 978-0471226185 ...

The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses. This Second Edition features: Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models * A unified perspective based on generalized linear models * An emphasis on logistic regression modeling * An appendix that demonstrates the use of SAS(r) for all methods * An entertaining historical perspective on the development of the methods * Specialized methods for ordinal data, small samples, multicategory data, and matched pairs * More than 100 analyses of real data sets and nearly 300 exercises. Written in an applied, nontechnical style, the book illustrates methods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Second Edition is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control.

Hector Guerrero ... 338 pages - Publisher: Springer; (March, 2010) ... Language: English - ISBN-10: 3642108342 - ISBN-13: 978-3642108341 ...

Why does the World Need―Excel Data Analysis, Modeling, and Simulation? When spreadsheets ?rst became widely available in the early 1980s, it spawned a revolution in teaching. What previously could only be done with arcane software and large scale computing was now available to the common-man, on a desktop. Also, before spreadsheets, most substantial analytical work was done outside the classroom where the tools were; spreadsheets and personal computers moved the work into the classroom. Not only did it change how the analysis curriculum was taught, but it also empowered students to venture out on their own to explore new ways to use the tools. I can’t tell you how many phone calls, of?ce visits, and/or emails I have received in my teaching career from ecstatic students crowing about what they have just done with a spreadsheet model. I have been teaching courses related to spreadsheet based analysis and modeling for about 25 years and I have watched and participated in the spreadsheet revolution.

R. Lyman Ott, Micheal T. Longnecker ... 1297 pages - Publisher: Brooks Cole; 6th edition (December, 2008) ... Language: English - ISBN-10: 0495017582 - ISBN-13: 978-0495017585 ...

Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Sixth Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and in news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments.

Contact Form

Name

Email *

Message *

Powered by Blogger.