This book over the years has proved to be a great architect in shaping student's ability to master Logical Reasoning and Data Interpretation for CAT examination. The fifth edition covers all the fundamental and advanced topics, supported by ample number of worked out examples, caselets, and exercises . It also provides clarity and knowledge of the concepts and questions that are asked in various MBA entrance examinations such as XAT, SNAP, IIFT, IRMA, MAT, NMAT, etc.

The Pearson Guide to Quantitative Aptitude for CAT 2/e has everything you need to secure a top score in the quantitative aptitude papers of the CAT and other MBA entrance examinations. Written in a student-friendly style, this book explains concepts in a concise manner and includes numerous examples and worked-out problems. It also contains ample practice problems, scientifically designed and arranged in four levels (in an increasing order of difficulty). The text also contains a chapter on Vedic mathematics, which provides unique time-saving and easy techniques for complex calculations.

This book, 'MOST EXPECTED MCQ ON PAPER 1', was created using the most up-to-date syllabus and pattern for the UGC NET General Paper 1. The book is organized into ten units according to the latest syllabus (Teaching Aptitude, Research Aptitude, Comprehension, Communication, Mathematical Reasoning and Aptitude, Logical Reasoning, Data Interpretation, Information and Communication Technology, People and Environment, and Higher Education System). Features of the Book • Comprehensive Coverage: The book covers all aspects of General Paper 1, ensuring that readers have a thorough understanding of the subject. It includes theories, models, strategies, and methodologies relevant to the exam. • Practice Questions: With over 3000 multiple-choice questions (MCQs), the book provides ample practice opportunities for readers. These questions cover a wide range of topics to test the reader's knowledge and understanding. • Answer Keys and Explanations: The book would provide detailed answer keys and Explanations for all the MCQs, to help readers understand the correct answer and the reasoning behind it. • Pedagogical Approach: The book adopts a pedagogical approach, presenting information in a structured and organized manner, with clear and concise Explanations of key concepts. • Exam-Oriented Approach: The book is specifically tailored to cater to the needs of candidates preparing for competitive exams that include General Paper 1 questions. Whether you are appearing for NTA UGC NET JRF, PGT, TGT, CTET, GIC, B.Ed., M.Ed., Ph.D., or other similar exams, this book will help you prepare effectively.

The 3rd edition of the revised & updated book “Koncepts of LR - Logical Reasoning for CAT & Other MBA Exams” is the benchmark in the learning process for Logical Reasoning. The book is the result of an extensive analysis of the past year exams papers. It now incorporates CAT questions from the past 20 years and 8 years of IIFT, & XAT questions. The book introduces Critical Reasoning for the first time. The books major focus is on Problem Solving Caselets and it provides numerous examples, past questions and practice caselets. The entire book has been divided into 21 chapters which provide conceptual inputs along with Solved Examples followed by Exercises in 5 difficulty levels viz. Concept Applicator, Concept Builder, Concept Cracker, Concept Deviator and Data Sufficiency, with detailed solutions. The Author has taken the onus of formulating questions on his own with his expertise in the domain. The result being, more than 1600+ questions incorporated in the book each with detailed solution, a feature not available anywhere otherwise. This book serves the purpose for all the aptitude test takers looking to crack exams like CAT, XAT, SNAP, IIFT & other MBA exams.

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.