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Download or read book 24 years CAT Topic wise Solved Papers 2017 1994 with 6 Online Practice Sets 11th edition written by Deepak Agarwal, Shipra Agarwal and published by Disha Publications. This book was released on 2018-04-25 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title contains an Access Code along with instructions to access the Online Material. The thoroughly revised & updated 11th edition of 24 years CAT Topic-wise Solved Papers (2017-1994) with 6 Online Practice Sets consists of past years solved papers of CAT from 1994 to 2017 distributed into 3 Units, which are further divided into 24 topics. The book contains more than 3000+ Milestone Problems for CAT with detailed solutions. Alternative solutions are provided at various places. The focus of the book is to provide shortcuts and techniques which are a must to Crack CAT. Finally the book provides 6 Online tests - 3 Sectional and 3 Full Practice Sets based on the latest patten with Solutions.

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Download or read book Scientific Writing written by Jennifer Peat and published by John Wiley & Sons. This book was released on 2013-07-01 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and practical book covers the basics of grammar as well as the broad brush issues such as writing a grant application and selling to your potential audience. The clear explanations are expanded and lightened with helpful examples and telling quotes from the giants of good writing. These experienced writers and teachers make scientific writing enjoyable.

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Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

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