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Author: Anthony Peter Macmillan Coxon
Publisher: SAGE
ISBN: 9780803972377
Category : Mathematics
Languages : en
Pages : 108
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Book Description
How to collect, describe, compare and analyze data.
Author: Anthony Peter Macmillan Coxon
Publisher: SAGE
ISBN: 9780803972377
Category : Mathematics
Languages : en
Pages : 108
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Book Description
How to collect, describe, compare and analyze data.
Author: Maria Langer
Publisher: Flying M Productions
ISBN: 1886637067
Category : Computers
Languages : en
Pages : 120
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Book Description
Author: Mark Gardener
Publisher: Pelagic Publishing Ltd
ISBN: 1784270091
Category : Computers
Languages : en
Pages : 376
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Book Description
Microsoft Excel is a powerful tool that can transform the way you use data. This book explains in comprehensive and user-friendly detail how to manage, make sense of, explore and share data, giving scientists at all levels the skills they need to maximize the usefulness of their data. Readers will learn how to use Excel to: * Build a dataset – how to handle variables and notes, rearrangements and edits to data. * Check datasets – dealing with typographic errors, data validation and numerical errors. * Make sense of data – including datasets for regression and correlation; summarizing data with averages and variability; and visualizing data with graphs, pivot charts and sparklines. * Explore regression data – finding, highlighting and visualizing correlations. * Explore time-related data – using pivot tables, sparklines and line plots. * Explore association data – creating and visualizing contingency tables. * Explore differences – pivot tables and data visualizations including box-whisker plots. * Share data – methods for exporting and sharing your datasets, summaries and graphs. Alongside the text, Have a Go exercises, Tips and Notes give readers practical experience and highlight important points, and helpful self-assessment exercises and summary tables can be found at the end of each chapter. Supplementary material can also be downloaded on the companion website. Managing Data Using Excel is an essential book for all scientists and students who use data and are seeking to manage data more effectively. It is aimed at scientists at all levels but it is especially useful for university-level research, from undergraduates to postdoctoral researchers.
Author: NB Venkateswarlu | EV Prasad
Publisher: S. Chand Publishing
ISBN: 8121932475
Category : Computers
Languages : en
Pages : 1067
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Book Description
A Snap Shot Oriented Treatise with Live Engineering Examples. Each chapter is is supplemented with concept oriented questions with answers and explanations. Some practical life problems from Education, business are included.
Author: Duncan A. Buell
Publisher: Jones & Bartlett Publishers
ISBN: 1449628079
Category : Computers
Languages : en
Pages : 409
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Book Description
Data Structures & Theory of Computation
Author: Michael McMillan
Publisher: "O'Reilly Media, Inc."
ISBN: 1449373968
Category : Computers
Languages : en
Pages : 252
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Book Description
As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C♯ and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms--including linked lists, stacks, queues, and graphs--within the constraints of the JavaScript environment. Determine which data structures and algorithms are most appropriate for the problems you're trying to solve, and understand the tradeoffs when using them in a JavaScript program. An overview of the JavaScript features used throughout the book is also included. This book covers: Arrays and lists: the most common data structures Stacks and queues: more complex list-like data structures Linked lists: how they overcome the shortcomings of arrays Dictionaries: storing data as key-value pairs Hashing: good for quick insertion and retrieval Sets: useful for storing unique elements that appear only once Binary Trees: storing data in a hierarchical manner Graphs and graph algorithms: ideal for modeling networks Algorithms: including those that help you sort or search data Advanced algorithms: dynamic programming and greedy algorithms.
Author: Susan C. Weller
Publisher: SAGE Publications
ISBN: 1506349757
Category : Social Science
Languages : en
Pages : 110
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Book Description
The process of collecting accurate data through interviewing, questionnaires, and other methods has not always been clear. However, data collection in field settings can be done in a structured, systematic and scientific way. These authors show us how. First, they focus on the importance of finding the right questions to ask. By providing a variety of formats - triadic comparisons and rating scales for data collection, both oral and written methods - and stressing cultural relativity, Weller and Romney suggest ways to improve not only the data collected, but also the interpretation and analysis of such data. Primarily addressed to qualitative social scientists, this volume is also appropriate for anyone who wants to study attitudes and beliefs. In particular, it is an ideal text for courses in anthropology, linguistics, qualitative research methods, health care, and survey research.
Author: Bill Jelen
Publisher: Tickling Keys, Inc.
ISBN: 0972425802
Category : Computers
Languages : en
Pages : 156
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Book Description
Jelen uses his combined experience and analytical ingenuity to demystify the arduous task of dealing with downloaded data. He uses real-life examples of real-life management requests, and then walks users through the maze of Excel tools and formulas.
Author: Américo Moreira
Publisher: Jose Americo Paiva Moreira
ISBN:
Category : Computers
Languages : en
Pages : 145
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Book Description
Mastering Microsoft Excel : a Comprehensive Guide is a comprehensive and user-friendly book that aims to help readers become proficient in using Microsoft Excel 2022. Whether you are a beginner or an experienced user, this book provides step-by-step instructions and practical examples to enhance your Excel skills. From basic functions to advanced formulas, data analysis, and automation, this guide covers all the essential features and techniques of Excel 2022. With a clear and concise writing style, this book offers a structured approach to learning Excel 2022. Each chapter focuses on a specific topic, providing explanations, examples, and exercises to reinforce your understanding. You will learn how to create and format spreadsheets, use formulas and functions effectively, analyze data using charts and pivot tables, and automate tasks with macros and VBA programming. Additionally, this guide covers the latest features and updates in Excel 2022, ensuring that you stay up-to-date with the software's capabilities. Whether you are a student, professional, or business owner, mastering Microsoft Excel 2022 is essential for improving productivity and making informed decisions. This comprehensive guide equips you with the knowledge and skills needed to navigate Excel with confidence. By the end of this book, you will have a solid foundation in Excel 2022 and be able to leverage its powerful features to streamline your work and achieve your goals.
Author: Mahmoud Parsian
Publisher: "O'Reilly Media, Inc."
ISBN: 1491906138
Category : Computers
Languages : en
Pages : 842
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Book Description
If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. Topics include: Market basket analysis for a large set of transactions Data mining algorithms (K-means, KNN, and Naive Bayes) Using huge genomic data to sequence DNA and RNA Naive Bayes theorem and Markov chains for data and market prediction Recommendation algorithms and pairwise document similarity Linear regression, Cox regression, and Pearson correlation Allelic frequency and mining DNA Social network analysis (recommendation systems, counting triangles, sentiment analysis)
