The.Hotest.Resources

Math Wizo ... 60 pages - Publisher: Independently Published; (February, 2019) ... Language: English - ISBN-10: 1793436789 - ISBN-13: 978-1793436788.

In this introductory guide, you will easily learn: An overview on data sampling + The calculation of measures of central tendency (mean, median, mode, and range). + How to calculate the measure of data dispersion (standard deviation) on both a population and on a sample. + Calculating the best fit line using the Least Squared Method. + Constructing Box-Whisker Plots, and how to calculate the 3 quartile values. + All about false positive and false negative results and how to calculate confidence intervals using the data information and z-scores. + How to calculate the margin of error and how to conduct Chi square p-values to measure the significance of test results. + And Much More!

F. B. J. Barends ... 158 pages - Publisher: Routledge; (November, 2017) ... Language: English - AmazonSIN: B078RRH98G.

This volume provides an overview of the proceedings of the XIIth ECSME Conference 1999. It covers a wide variety of topics, from summaries of workshops and sessions, to the emergence of information technology and information retrieval and communication.

Leonid Burstein ... 284 pages - Publisher: Woodhead Publishing; (February, 2020) ... Language: English - AmazonSIN: B084L22J54.

A MATLAB Primer for Technical Programming for Materials Science and Engineering draws on examples from the field, providing the latest information on this programming tool that is targeted towards materials science. The book enables non-programmers to master MATLAB in order to solve problems in materials science, assuming only a modest mathematical background. In addition, the book introduces programming and technical concepts in a logical manner to help students use MATLAB for subsequent projects. This title offers materials scientists who are non-programming specialists with a coherent and focused introduction to MATLAB. Provides the necessary background, alongside examples drawn from the field, to allow materials scientists to effectively master MATLAB. + Guides the reader through programming and technical concepts in a logical and coherent manner. + Promotes a thorough working familiarity with MATLAB for materials scientists. + Gives the information needed to write efficient and compact programs to solve problems in materials science, tribology, mechanics of materials and other material-related disciplines.

Gary Mavko, Tapan Mukerji, Jack Dvorkin ... 524 pages - Publisher: Cambridge University Press; 2nd edition (May, 2009) ... Language: English - ISBN-10: 0521861365.

This fully updated text addresses the relationships between geophysical observations and the underlying physical properties of rocks. It distills a vast quantity of background theory and laboratory results into a series of concise chapters that provide practical solutions to problems in geophysical data interpretation. Now in its second edition, major new chapters are presented on statistical rock physics and velocity-porosity-clay models for clastic sediments. Other new and expanded topics include anisotropic seismic signatures, borehole waves, models for fractured media, poroelastic models, and attenuation models. Also new to this edition is an enhanced set of appendices with key empirical results, data tables, and an atlas of reservoir rock properties - extended to include carbonates, clays, gas hydrates, and heavy oils. Supported by a website hosting MATLAB routines for implementing the various rock physics formulas, this book is a vital resource for advanced students and university faculty, as well as petroleum industry geophysicists and engineers.

Galit Shmueli, Peter C. Bruce, Nitin R. Patel ... 560 pages - Publisher: Wiley; 3rd edition (April, 2016) ... Language: English - ISBN-10: 1118729277 - ISBN-13: 978-1118729274.

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods + End-of-chapter exercises that help readers better understand the presented material + Data-rich case studies to illustrate various applications of data mining techniques + Completely new chapters on social network analysis and text mining + A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com + Free 140-day license to use XLMiner for Education software.

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology.

Iain Pardoe .. 346 pages - Publisher: Wiley; 2nd edition (July, 2012) ... Language: English - ISBN-10: 1118097289 - ISBN-13: 978-1118097281.

Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling.

In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction + Testing model assumptions + Nonconstant variance + Autocorrelation + Variable selection methods + Model building and graphical interpretation. Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos.

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