A Complete Book On Data Interpretation Data Analysis Ebook

Author : Adda247 Publications
Publisher : Adda247 Publications
Page : 456 pages
File Size : 45,6 Mb
Release : 2019-02-01
Category : Electronic
ISBN : 9788194032632

Get Book

A Complete Book on Data Interpretation & Data Analysis (eBook) by Adda247 Publications Pdf

-2000+ Questions Based on Latest Pattern with detailed Solutions -Covers all the types of DI such as Table| Pie | Bar | Line | Caselet |Radar -Includes Arithmetic Based & Missing DI asked in IBPS/SBI Mains Examinations -Includes Previous year questions asked in SBI Po mains 2018, IBPS PO mains 2018 and other exams. -Essential for both Prelims and Mains exams A Complete Book on Data Interpretation and Analysis eBook’ is an effort to assist all the government job aspirants with a comprehensive, reliable and satisfactory source of offline practice materials to improve their proficiency in Quantitative Aptitude. This ebook is a unique approach towards fulfilling the needs of our dedicated aspirants who wish to clear any obstacle with ease. We should never be confined by the limits of our brain and this eBook which is thoroughly revised and covers every crucial aspect of all the Banking and Insurance examinations assures you that it will help you in transcending your limits. The ebook comprises more than 300 DIs which include 2000+ Questions covering all the patterns and topics that the IBPS, SBI and other banking exams have been surprising us with for last few years. The ebook is elegantly divided into different chapters namely Table, Bar Graph, Line Graph, Pie Graph, Mixed Graph, Arithmetic and Caselets. Each chapter is further categorized into four parts – Solved Examples, Previous years’ exercises, Level 1 exercise (Basic to Moderate) and Level 2 exercise (Advance). There are new methods and approach to solving the latest pattern questions within a short time limit. Detailed solutions are provided to every question for better CONCEPTUAL learning. In the second edition, we have includes more than 500 Questions based on latest pattern and questions asked in recent exams like SBI PO 2018, IBPS PO 2018, RRB PO 2018 and other exams. The questions are duly framed and prepared by our best faculties in this field. While preparing, all the necessities including minute details have been taken care of. The questions are preferably selected based on their quality, inculcating different levels and types that are being asked in the banking and insurance examinations. The ebook will be extremely helpful in preparing for all the Banking and Insurance examinations like IBPS PO, SBI PO, BANK OF BARODA PO, SYNDICATE BANK PO, RBI ASSISTANT, OICL, UIIC, etc.

Author : Srivastava, Vijay Shankar
Publisher : S. Chand Publishing
Page : 128 pages
File Size : 51,8 Mb
Release : 2024-06-05
Category : Study Aids
ISBN : 9789352830084

Get Book

Data Analysis & Interpretation by Srivastava, Vijay Shankar Pdf

This book provides the reader with new concepts and techniques to solve the problems of Data Analysis & Interpretation in a jiffy. The book provides comprehensive concept-building illustrated with several examples in each chapter. A systematic approach to the study of the Data Analysis and Interpretation is divided into nine chapters.

Author : Gérard Govaert
Publisher : John Wiley & Sons
Page : 265 pages
File Size : 45,5 Mb
Release : 2013-03-04
Category : Mathematics
ISBN : 9781118617861

Get Book

Data Analysis by Gérard Govaert Pdf

The first part of this book is devoted to methods seeking relevant dimensions of data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data. After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in the first part, to synthesize and to analyze the data. The book concludes by examining the links existing between data mining and data analysis.

Author : Gloria Rosenthal,James A. Rosenthal, PhD
Publisher : Springer Publishing Company
Page : 512 pages
File Size : 53,8 Mb
Release : 2011-12-16
Category : Social Science
ISBN : 9780826107213

Get Book

Statistics and Data Interpretation for Social Work by Gloria Rosenthal,James A. Rosenthal, PhD Pdf

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to provide a solid foundation in statistics. It also addresses tools used by researchers to describe and summarize data ranging from single variables to assessing the relationship between variables and cause and effect among variables. The second section focuses on inferential statistics, describing how researchers draw conclusions about whole populations based on data from samples. This section also covers confidence intervals and a variety of significance tests for examining relationships between different types of variables. Additionally, tools for multivariate analyses and data interpretation are presented. Key Features: Addresses the role of statistics in evidence-based practice and program evaluation Features examples of qualitative and quantitative analysis Each chapter contains exercise problems and questions to enhance student learning Includes electronic data sets taken from actual social work arenas Offers a full ancillary digital packet including a student guide to SPSS with accompanying Data Set, an Instructor's Manual, PowerPoint slides, and a Test Bank

Author : Michele Knobel,Judy Kalman,Colin Lankshear
Publisher : Myers Education Press
Page : 236 pages
File Size : 43,9 Mb
Release : 2020-04-17
Category : Language Arts & Disciplines
ISBN : 9781975502157

Get Book

Data Analysis, Interpretation, and Theory in Literacy Studies Research by Michele Knobel,Judy Kalman,Colin Lankshear Pdf

Novice and early career researchers often have difficulty with understanding how theory, data analysis and interpretation of findings “hang together” in a well-designed and theorized qualitative research investigation and with learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Data Analysis, Interpretation, and Theory in Literacy Studies Research demonstrates how to design, conduct and analyze a well put together qualitative research project. Using their own successful studies, chapter authors spell out a problem area, research question, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

Author : Tiffany Bergin
Publisher : SAGE
Page : 381 pages
File Size : 45,8 Mb
Release : 2018-10-15
Category : Social Science
ISBN : 9781526452313

Get Book

An Introduction to Data Analysis by Tiffany Bergin Pdf

Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media. It includes advice on: - Data analysis frameworks - Validity and credibility of data - Sampling techniques - Data management - The big data phenomenon - Data visualisation - Effective data communication Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.

Author : Hector Cuesta,Dr. Sampath Kumar
Publisher : Packt Publishing Ltd
Page : 338 pages
File Size : 53,6 Mb
Release : 2016-09-30
Category : Computers
ISBN : 9781785286667

Get Book

Practical Data Analysis by Hector Cuesta,Dr. Sampath Kumar Pdf

A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 40,5 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

Get Book

Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Author : Lidia Ogiela
Publisher : Springer
Page : 115 pages
File Size : 51,9 Mb
Release : 2009-07-10
Category : Computers
ISBN : 9783642026935

Get Book

Cognitive Techniques in Visual Data Interpretation by Lidia Ogiela Pdf

The extremely rapid progress of science dealing with the design of new computer systems and the development of intelligent algorithmic solutions for solving c- plex problems has become apparent also in the field of computational intelligence and cognitive informatics methods. The progress of these new branches of inf- matics has only started a few years ago, but they are already making a very s- nificant contribution to the development of modern technologies, and also forming the foundations for future research on building an artificial brain and systems i- tating human thought processes. We are already able to build robots with basic machine intelligence, which can sometimes perform complex actions and also - erate by adapting to changing conditions of their surroundings. This very impr- sive development of intelligent systems is manifested in the creation of robotic devices which use artificial intelligence algorithms in their operations, mo- ments, when solving difficult problems or communicating with humans. It is also evidenced by the introduction of new methods of reasoning about and interpreting objects or events surrounding the system. One of the fields in which the need to deploy such modern solutions is obvious are cognitive vision systems used both in mobile robots and in computer systems which recognise or interpret the meaning of recorded signals or patterns.

Author : Paul Hamilton
Publisher : PasTest Ltd
Page : 468 pages
File Size : 52,5 Mb
Release : 2006
Category : Medical
ISBN : 1904627668

Get Book

Data Interpretation for Medical Students by Paul Hamilton Pdf

"This book is written for all medical students and is ideal for OSCE practice, during ward rounds and clinical years ..." -- BOOK COVER.

Author : Ananta Ashisha, Sandeep Bajaj
Publisher : Arihant Publications India limited
Page : 418 pages
File Size : 48,7 Mb
Release : 2020-09-17
Category : Electronic
ISBN : 9789324197245

Get Book

Data Interpretation & Data Sufficiency by Ananta Ashisha, Sandeep Bajaj Pdf

Author : Peter Bruce,Andrew Bruce
Publisher : "O'Reilly Media, Inc."
Page : 395 pages
File Size : 41,8 Mb
Release : 2017-05-10
Category : Computers
ISBN : 9781491952917

Get Book

Practical Statistics for Data Scientists by Peter Bruce,Andrew Bruce Pdf

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Author : Jaggan Saneja
Publisher : Notion Press
Page : 306 pages
File Size : 43,8 Mb
Release : 2016-10-14
Category : Study Aids
ISBN : 9781945688034

Get Book

Data Interpretation Simplified by Jaggan Saneja Pdf

Data Interpretation questions derive good scores in any competition examination. The book Data Interpretation Simplified has been authored by Jaggan Saneja. This book has been specially prepared for various competive examinations keeping in mind the importance of Data questions. The questions on data problems have been prepared and presented in a simple manner with sufficient examples - where the level of questions go from easy to tough. The book contains a good number of examples, practice exercises followed by Tests. The questions have been taken from old examination papers - for thorough practice and better understanding - which will help students in understanding the tricks and short cuts of problem solving better.

Author : Jerome L. Myers,Arnold D. Well,Robert F. Lorch Jr
Publisher : Routledge
Page : 821 pages
File Size : 49,8 Mb
Release : 2013-01-11
Category : Psychology
ISBN : 9781135811631

Get Book

Research Design and Statistical Analysis by Jerome L. Myers,Arnold D. Well,Robert F. Lorch Jr Pdf

Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book’s goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them. Changes in the New Edition: Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed. A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations. A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study. A new chapter (27) on common errors in data analysis and interpretation. Increased emphasis on power analyses to determine sample size using the G*Power 3 program. Many new data sets and problems. More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages. A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only. Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory. This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers.

Author : Tony Fischetti
Publisher : Packt Publishing Ltd
Page : 388 pages
File Size : 44,7 Mb
Release : 2015-12-22
Category : Computers
ISBN : 9781785286445

Get Book

Data Analysis with R by Tony Fischetti Pdf

Load, wrangle, and analyze your data using the world's most powerful statistical programming language About This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics A practical guide to performing data analysis in practice Who This Book Is For Whether you are learning data analysis for the first time, or you want to deepen the understanding you already have, this book will prove to an invaluable resource. If you are looking for a book to bring you all the way through the fundamentals to the application of advanced and effective analytics methodologies, and have some prior programming experience and a mathematical background, then this is for you. What You Will Learn Navigate the R environment Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Employ hypothesis tests to draw inferences from your data Learn Bayesian methods for estimating parameters Perform regression to predict continuous variables Apply powerful classification methods to predict categorical data Handle missing data gracefully using multiple imputation Identify and manage problematic data points Employ parallelization and Rcpp to scale your analyses to larger data Put best practices into effect to make your job easier and facilitate reproducibility In Detail Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it's easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone's career as a data analyst. Style and approach Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach.