A Complete Book on Data Interpretation & Data Analysis (eBook)


Book Description

-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.




Data Analysis, Interpretation, and Theory in Literacy Studies Research


Book Description

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




Data Interpretation & Data Sufficiency


Book Description




Data Analysis for Business, Economics, and Policy


Book Description

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.




Data Analysis for Social Science


Book Description

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--




Letting Data Lead


Book Description

"In Responding to Data, author Eileen Depka expounds on how implementing a proficient system of assessment yields actionable data. In order to better respond to student needs, educators need the know-how of conducting proper assessment design, data collection, and data interpretation. This book provides systems, processes, and specific examples that help teachers thoroughly understand how to preplan assessments and collect the data available to them. The tools and templates outline how teachers can determine if the collective data indicate a response is needed and how teachers can then turn gathered information into immediate actions. By reading this book, educators gain strategies that build a culture of data analysis and student achievement in their classrooms"--




Data Interpretation for Medical Students


Book Description

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




Rigorous Data Analysis


Book Description

In qualitative research, one can often hear the statement that research results are just (social) constructions. In criminal cases and in court hearings, we tend to expect that the true sequence of events has to be found rather than just any story. Here the author shows that qualitative social research can be conducted in the manner of police work or court proceedings. He does so by exhibiting how short pieces of transcriptions can be approached to uncover who, when, where, and how participated, what kind of social situation produced the transcription, and so on without any background knowledge other than that talk itself. Commenting on transcriptions of a researcher in the course of doing rigorous data analysis, readers learn doing ethnographically adequate accounts and critical institutional ethnography “at the elbow” of an experienced practitioners. Further topics include the role of turn sequences, the ethnomethods of knowledge-power and institutional relations, the documentary method of interpretation, and time-sensitive social analysis.




Python for Data Analysis


Book Description

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples




Humanities Data Analysis


Book Description

A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations