The.Hottest

Friday, September 07, 2018 , ,
Russell C. Hibbeler ... 704 pages - Publisher: Prentice Hall; 14th edition (February, 2015) ... Language: English - ISBN-10: 0133918920 - ISBN-13: 978-0133918922.

Engineering Mechanics: Statics excels in providing a clear and thorough presentation of the theory and application of engineering mechanics. Engineering Mechanics empowers students to succeed by drawing upon Professor Hibbeler’s everyday classroom experience and his knowledge of how students learn. This text is shaped by the comments and suggestions of hundreds of reviewers in the teaching profession, as well as many of the author’s students. The Fourteenth Edition includes new Preliminary Problems, which are intended to help students develop conceptual understanding and build problem-solving skills. The text features a large variety of problems from a broad range of engineering disciplines, stressing practical, realistic situations encountered in professional practice, and having varying levels of difficulty.
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Thursday, September 06, 2018 , , ,
R. C. Hibbeler ... 912 pages - Publisher: Pearson; 4th edition (August, 2013) ... Language: English - ISBN-10: 0133451607 - ISBN-13: 978-0133451603 ...

Statics and Mechanics of Materials provides a comprehensive and well-illustrated introduction to the theory and application of statics and mechanics of materials. The text presents a commitment to the development of student problem-solving skills and features many pedagogical aids unique to Hibbeler texts. MasteringEngineering for Statics and Mechanics of Materials is a total learning package. This innovative online program emulates the instructor’s office–hour environment, guiding students through engineering concepts from Statics and Mechanics of Materials with self-paced individualized coaching. For introductory combined Statics and Mechanics of Materials courses found in ME, CE, AE, and Engineering Mechanics departments.
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Tuesday, September 04, 2018 , ,
R. Lyman Ott, Micheal T. Longnecker ... 1296 pages - Publisher: Cengage Learning; 7th edition (June, 2015) ... Language: English - ISBN-10: 1305269470 - ISBN-13: 978-1305269477 ...

Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Seventh 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 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.
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Saturday, September 01, 2018 , , ,
Irving Kett ... 246 pages - Publisher: CRC Press; 2nd edition (December, 2009) ... Language: English - ISBN-10: 1420091018 - ISBN-13: 978-1420091014 ...
As every civil engineer knows, Portland Cement is the most versatile and important material of construction, and will probably remain so far into the future. Yet few books, if any, exist that offer an in-depth analysis of the mixing and testing methods of this vital hydraulic cement. This statement, written about the first edition of Engineered Concrete: Mix Design and Test Methods, remains as true today as it was ten years ago. Revised and updated, the second edition of this groundbreaking resource completely covers Portland Cement, Portland Cement Concrete, and their uses. See what’s new in the Second Edition: New coverage of the latest concrete technologies such as high-performance and lightweight concrete  + Several new tests and sample tearsheets + Additional and updated data sheets. The body of the book is divided into several sections, with the first explaining how concrete batches are designed, mixed, and measured for various consistencies. Another section details the tests of the primary component materials of concrete other than water—namely Portland Cement, aggregates, and mortar—while the final section includes some of the fundamental concrete testing procedures for different strength parameters in conformity with the standards of the American Society for Testing Materials. Solidly researched and written, the book supplies a fundamental understanding of cement, concrete, and mixing and testing methods that allow readers to produce the most economical combinations of concrete materials and satisfy performance requirements and specifications.
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Thursday, August 30, 2018 , , , ,
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.
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Tuesday, August 28, 2018 , , ,
Conrad Carlberg ... 368 pages - Publisher: Que Publishing; 1st edition (May, 2016) ... Language: English - ISBN-10: 0789756552 - ISBN-13: 978-0789756558 ...

This is today’s most complete guide to regression analysis with Microsoft® Excel for any business analytics or research task. Drawing on 25 years of advanced statistical experience, Microsoft MVP Conrad Carlberg shows how to use Excel’s regression-related worksheet functions to perform a wide spectrum of practical analyses. Carlberg clearly explains all the theory you’ll need to avoid mistakes, understand what your regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples. He discusses the consequences of using each option and argument, points out idiosyncrasies and controversies associated with Excel’s regression functions, and shows how to use them reliably in fields ranging from medical research to financial analysis to operations.

You don’t need expensive software or a doctorate in statistics to work with regression analyses. Microsoft Excel has all the tools you need—and this book has all the knowledge! Understand what regression analysis can and can’t do, and why + Master regression-based functions built into all recent versions of Excel + Work with correlation and simple regression + Make the most of Excel’s improved LINEST() function + Plan and perform multiple regression + Distinguish the assumptions that matter from the ones that don’t + Extend your analysis options by using regression instead of traditional analysis of variance + Add covariates to your analysis to reduce bias and increase statistical power.
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