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| excel data sets for practice: Managing Data Using Excel Mark Gardener, 2015-04-20 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. |
| excel data sets for practice: Excel 2016 Bible John Walkenbach, 2015-10-09 The complete guide to Excel 2016, from Mr. Spreadsheet himself Whether you are just starting out or an Excel novice, the Excel 2016 Bible is your comprehensive, go-to guide for all your Excel 2016 needs. Whether you use Excel at work or at home, you will be guided through the powerful new features and capabilities by expert author and Excel Guru John Walkenbach to take full advantage of what the updated version offers. Learn to incorporate templates, implement formulas, create pivot tables, analyze data, and much more. Navigate this powerful tool for business, home management, technical work, and much more with the only resource you need, Excel 2016 Bible. Create functional spreadsheets that work Master formulas, formatting, pivot tables, and more Get acquainted with Excel 2016's new features and tools Customize downloadable templates and worksheets Whether you need a walkthrough tutorial or an easy-to-navigate desk reference, the Excel 2016 Bible has you covered with complete coverage and clear expert guidance. |
| excel data sets for practice: Introduction to Econometrics Christopher Dougherty, 2011-03-03 Taking a modern approach to the subject, this text provides students with a solid grounding in econometrics, using non-technical language wherever possible. |
| excel data sets for practice: Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) Wayne Winston, 2021-12-17 Master business modeling and analysis techniques with Microsoft Excel and transform data into bottom-line results. Award-winning educator Wayne Winston's hands-on, scenario-focused guide helps you use today's Excel to ask the right questions and get accurate, actionable answers. More extensively updated than any previous edition, new coverage ranges from one-click data analysis to STOCKHISTORY, dynamic arrays to Power Query, and includes six new chapters. Practice with over 900 problems, many based on real challenges faced by working analysts. Solve real problems with Microsoft Excel—and build your competitive advantage Quickly transition from Excel basics to sophisticated analytics Use recent Power Query enhancements to connect, combine, and transform data sources more effectively Use the LAMBDA and LAMBDA helper functions to create Custom Functions without VBA Use New Data Types to import data including stock prices, weather, information on geographic areas, universities, movies, and music Build more sophisticated and compelling charts Use the new XLOOKUP function to revolutionize your lookup formulas Master new Dynamic Array formulas that allow you to sort and filter data with formulas and find all UNIQUE entries Illuminate insights from geographic and temporal data with 3D Maps Improve decision-making with probability, Bayes' theorem, and Monte Carlo simulation and scenarios Use Excel trend curves, multiple regression, and exponential smoothing for predictive analytics Use Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook |
| excel data sets for practice: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-09 Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it! |
| excel data sets for practice: Storytelling with Data Cole Nussbaumer Knaflic, 2019-10-22 Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become—or teach others to be—a powerful data storyteller. Let’s practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller storytelling with data’s foundational lessons, Let’s practice! delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes: ● Practice with Cole: exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation ● Practice on your own: thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions ● Practice at work: practical guidance and hands-on exercises for applying storytelling with data lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact The lessons and exercises found within this comprehensive guide will empower you to master—or develop in others—data storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories! |
| excel data sets for practice: Creating and Verifying Data Sets with Excel Robert E. McGrath, 2014-01-21 Accurate data entry and analysis can be deceptively labor-intensive and time-consuming. Creating and Verifying Data Sets with Excel is a focused, easy-to-read guide that gives readers the wherewithal to make use of a remarkable set of data tools tucked within Excel—tools most researchers are entirely unaware of. Robert E. McGrath’s book is the first to focus exclusively on Excel as a data entry system. It incorporates a number of learning tools such as screenshots, text boxes that summarize key points, examples from across the social sciences, tips for creating professional-looking tables, and questions at the end of each chapter. Providing practical strategies to improve and ease the processes of data entry, creation and analysis, this step-by-step guide is a brief, but invaluable resource for both students and researchers. |
| excel data sets for practice: Data Science in Theory and Practice Maria Cristina Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela, 2021-10-12 DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia. |
| excel data sets for practice: Data Smart John W. Foreman, 2013-10-31 Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the data scientist, toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know. |
| excel data sets for practice: Data Analysis Using SQL and Excel Gordon S. Linoff, 2010-09-16 Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like. |
| excel data sets for practice: Statistics for Ecologists Using R and Excel Mark Gardener, 2017-01-16 This is a book about the scientific process and how you apply it to data in ecology. You will learn how to plan for data collection, how to assemble data, how to analyze data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs. Statistical approaches covered include: data exploration; tests for difference – t-test and U-test; correlation – Spearman’s rank test and Pearson product-moment; association including Chi-squared tests and goodness of fit; multivariate testing using analysis of variance (ANOVA) and Kruskal–Wallis test; and multiple regression. Key skills taught in this book include: how to plan ecological projects; how to record and assemble your data; how to use R and Excel for data analysis and graphs; how to carry out a wide range of statistical analyses including analysis of variance and regression; how to create professional looking graphs; and how to present your results. New in this edition: a completely revised chapter on graphics including graph types and their uses, Excel Chart Tools, R graphics commands and producing different chart types in Excel and in R; an expanded range of support material online, including; example data, exercises and additional notes & explanations; a new chapter on basic community statistics, biodiversity and similarity; chapter summaries and end-of-chapter exercises. Praise for the first edition: This book is a superb way in for all those looking at how to design investigations and collect data to support their findings. – Sue Townsend, Biodiversity Learning Manager, Field Studies Council [M]akes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel – Mark Edwards, EcoBlogging A must for anyone getting to grips with data analysis using R and excel. – Amazon 5-star review It has been very easy to follow and will be perfect for anyone. – Amazon 5-star review A solid introduction to working with Excel and R. The writing is clear and informative, the book provides plenty of examples and figures so that each string of code in R or step in Excel is understood by the reader. – Goodreads, 4-star review |
| excel data sets for practice: Development Research in Practice Kristoffer Bjärkefur, Luíza Cardoso de Andrade, Benjamin Daniels, Maria Ruth Jones, 2021-07-16 Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University |
| excel data sets for practice: Excel 2019 Bible Michael Alexander, Richard Kusleika, John Walkenbach, 2018-09-20 The complete guide to Excel 2019 Whether you are just starting out or an Excel novice, the Excel 2019 Bible is your comprehensive, go-to guide for all your Excel 2019 needs. Whether you use Excel at work or at home, you will be guided through the powerful new features and capabilities to take full advantage of what the updated version offers. Learn to incorporate templates, implement formulas, create pivot tables, analyze data, and much more. Navigate this powerful tool for business, home management, technical work, and much more with the only resource you need, Excel 2019 Bible. Create functional spreadsheets that work Master formulas, formatting, pivot tables, and more Get acquainted with Excel 2019's new features and tools Whether you need a walkthrough tutorial or an easy-to-navigate desk reference, the Excel 2019 Bible has you covered with complete coverage and clear expert guidance. |
| excel data sets for practice: Statistical Testing with Jamovi and JASP Open Source Software Cole Davis, 2019 This book teaches statistics in a cheerful, straightforward manner, cherry-picking from two similar, easy-to-use open source software packages, which are being adopted by universities across the world. Without mathematical formulae, no previous statistical knowledge is assumed. Yet the lucid writing and clear structure takes the reader quickly and logically from beginner to graduate level. All tests come with worked examples from psychology. Tests include t tests, one-way ANOVA, and their non-parametric equivalents; correlations and regression; categorical analyses including binomial, chi square and more; factorial ANOVA; MANOVA; principal components analysis and factor analysis; logistic regression; partial correlations; the Kaplan-Meier curve; an introduction to Bayesian statistics. The book takes a consistent approach to effect sizes, as well as covering data assumptions and confidence intervals. This should appeal to students, academics and practitioners. |
| excel data sets for practice: Microsoft Excel 2019 Data Analysis and Business Modeling Wayne Winston, 2019-03-28 Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with Excel—and build your competitive advantage: Quickly transition from Excel basics to sophisticated analytics Use PowerQuery or Get & Transform to connect, combine, and refine data sources Leverage Office 365’s new Geography and Stock data types and six new functions Illuminate insights from geographic and temporal data with 3D Maps Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts Use Excel trend curves, multiple regression, and exponential smoothing Delve into key financial, statistical, and time functions Master all of Excel’s great charts Quickly create forecasts from historical time-based data Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams Run Monte Carlo simulations on stock prices and bidding models Learn about basic probability and Bayes’ Theorem Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook Automate repetitive analytics tasks by using macros |
| excel data sets for practice: OpenIntro Statistics David Diez, Christopher Barr, Mine Çetinkaya-Rundel, 2015-07-02 The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources. |
| excel data sets for practice: Introductory Business Statistics 2e Alexander Holmes, Barbara Illowsky, Susan Dean, 2023-12-13 Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License. |
| excel data sets for practice: Statistics Applied With Excel Franz Kronthaler, 2022-11-17 This book shows you how to analyze data sets systematically and to use Excel 2019 to extract information from data almost effortlessly. Both are (not) an art! The statistical methods are presented and discussed using a single data set. This makes it clear how the methods build on each other and gradually more and more information can be extracted from the data. The Excel functions used are explained in detail - the procedure can be easily transferred to other data sets. Various didactic elements facilitate orientation and working with the book: At the checkpoints, the most important aspects from each chapter are briefly summarized. In the freak knowledge section, more advanced aspects are addressed to whet the appetite for more. All examples are calculated with hand and Excel. Numerous applications and solutions as well as further data sets are available on the author's internet platform. This book is a translation of the original German 2nd edition Statistik angewandt mit Excel by Franz Kronthaler, published by Springer-Verlag GmbH Germany, part of Springer Nature in 2021. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors. |
| excel data sets for practice: Excel Data Analysis Hector Guerrero, 2018-12-14 This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations. |
| excel data sets for practice: Biplots in Practice Michael J. Greenacre, 2010 Este libro explica las aplicaciones específicas y las interpretaciones del biplot en muchas áreas del análisis multivariante. regresión, modelos lineales generalizados, análisis de componentes principales, análisis de correspondencias y análisis discriminante. |
| excel data sets for practice: Excel Power Pivot & Power Query For Dummies Michael Alexander, 2016-03-18 A guide to PowerPivot and Power Query no data cruncher should be without! Want to familiarize yourself with the rich set of Microsoft Excel tools and reporting capabilities available from PowerPivot and Power Query? Look no further! Excel PowerPivot & Power Query For Dummies shows you how this powerful new set of tools can be leveraged to more effectively source and incorporate 'big data' Business Intelligence and Dashboard reports. You'll discover how PowerPivot and Power Query not only allow you to save time and simplify your processes, but also enable you to substantially enhance your data analysis and reporting capabilities. Gone are the days of relatively small amounts of data—today's data environment demands more from business analysts than ever before. Now, with the help of this friendly, hands-on guide, you'll learn to use PowerPivot and Power Query to expand your skill-set from the one-dimensional spreadsheet to new territories, like relational databases, data integration, and multi-dimensional reporting. Demonstrates how Power Query is used to discover, connect to, and import your data Shows you how to use PowerPivot to model data once it's been imported Offers guidance on using these tools to make analyzing data easier Written by a Microsoft MVP in the lighthearted, fun style you've come to expect from the For Dummies brand If you spend your days analyzing data, Excel PowerPivot & Power Query For Dummies will get you up and running with the rich set of Excel tools and reporting capabilities that will make your life—and work—easier. |
| excel data sets for practice: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
| excel data sets for practice: Collect, Combine, and Transform Data Using Power Query in Excel and Power BI Gil Raviv, 2018-10-08 Using Power Query, you can import, reshape, and cleanse any data from a simple interface, so you can mine that data for all of its hidden insights. Power Query is embedded in Excel, Power BI, and other Microsoft products, and leading Power Query expert Gil Raviv will help you make the most of it. Discover how to eliminate time-consuming manual data preparation, solve common problems, avoid pitfalls, and more. Then, walk through several complete analytics challenges, and integrate all your skills in a realistic chapter-length final project. By the time you’re finished, you’ll be ready to wrangle any data–and transform it into actionable knowledge. Prepare and analyze your data the easy way, with Power Query · Quickly prepare data for analysis with Power Query in Excel (also known as Get & Transform) and in Power BI · Solve common data preparation problems with a few mouse clicks and simple formula edits · Combine data from multiple sources, multiple queries, and mismatched tables · Master basic and advanced techniques for unpivoting tables · Customize transformations and build flexible data mashups with the M formula language · Address collaboration challenges with Power Query · Gain crucial insights into text feeds · Streamline complex social network analytics so you can do it yourself For all information workers, analysts, and any Excel user who wants to solve their own business intelligence problems. |
| excel data sets for practice: Analyzing Social Media Networks with NodeXL Derek Hansen, Ben Shneiderman, Marc A. Smith, 2010-09-14 Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology. This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies. Part I provides background in the history and concepts of social media and social networks. Also included here is social network analysis, which flows from measuring, to mapping, and modeling collections of connections. The next part focuses on the detailed operation of the free and open-source NodeXL extension of Microsoft Excel, which is used in all exercises throughout this book. In the final part, each chapter presents one form of social media, such as e-mail, Twitter, Facebook, Flickr, and Youtube. In addition, there are descriptions of each system, the nature of networks when people interact, and types of analysis for identifying people, documents, groups, and events. - Walks you through NodeXL, while explaining the theory and development behind each step, providing takeaways that can apply to any SNA - Demonstrates how visual analytics research can be applied to SNA tools for the mass market - Includes case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and wikis - Download companion materials and resources at https://nodexl.codeplex.com/documentation |
| excel data sets for practice: Beginning Excel, First Edition Barbara Lave, Diane Shingledecker, Julie Romey, Noreen Brown, Mary Schatz, 2020 This is the first edition of a textbook written for a community college introductory course in spreadsheets utilizing Microsoft Excel; second edition available: https://openoregon.pressbooks.pub/beginningexcel19/. While the figures shown utilize Excel 2016, the textbook was written to be applicable to other versions of Excel as well. The book introduces new users to the basics of spreadsheets and is appropriate for students in any major who have not used Excel before. |
| excel data sets for practice: Compositional Data Analysis in Practice Michael Greenacre, 2018-07-17 Compositional data are quantitative descriptions of the parts of some whole, conveying exclusively relative information. Examples are found in various fields, including geology, medicine, chemistry, agriculture, economics, social science, etc. This concise book presents a very applied introduction to compositional data analysis, focussing on the use of R for analysis. It includes lots of real examples, code snippets, and colour figures, to illustrate the methods. |
| excel data sets for practice: Practice R Edgar J. Treischl, 2023-05-08 Many students learn to analyze data using commercial packages, even though there is an open-source software with cutting-edge possibilities: R, a programming language with countless cool features for applied empirical research. Practice R introduces R to social science students, inspiring them to consider R as an excellent choice. In a non-technical pragmatic way, this book covers all typical steps of applied empirical research. Learn how to prepare, analyze, and visualize data in R. Discover how to collect data, generate reports, or automate error-prone tasks. The book is accompanied by an R package. This provides further learning materials that include interactive tutorials, challenging you with typical problems of applied research. This way, you can immediately practice the knowledge you have learned. The package also includes the source code of each chapter and templates that help to create reports. Practice R has social science students in mind, nonetheless a broader audience may use Practice R to become a proficient R user. |
| excel data sets for practice: Microsoft Excel 2013 Alberto Ferrari, Marco Russo, 2013 Transform your skills, data, and business and create your own BI solutions using software you already know and love: Microsoft Excel. Two business intelligence (BI) experts take you inside PowerPivot functionality for Excel® 2013, with a focus on real world scenarios, problem-solving, and data modeling. You'll learn how to quickly turn mass quantities of data into meaningful information and on-the-job results?no programming required! |
| excel data sets for practice: Data Science in Theory and Practice Maria Cristina Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela, 2021-09-30 DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia. |
| excel data sets for practice: #MakeoverMonday Andy Kriebel, Eva Murray, 2018-10-02 Explore different perspectives and approaches to create more effective visualizations #MakeoverMonday offers inspiration and a giant dose of perspective for those who communicate data. Originally a small project in the data visualization community, #MakeoverMonday features a weekly chart or graph and a dataset that community members reimagine in order to make it more effective. The results have been astounding; hundreds of people have contributed thousands of makeovers, perfectly illustrating the highly variable nature of data visualization. Different takes on the same data showed a wide variation of theme, focus, content, and design, with side-by-side comparisons throwing more- and less-effective techniques into sharp relief. This book is an extension of that project, featuring a variety of makeovers that showcase various approaches to data communication and a focus on the analytical, design and storytelling skills that have been developed through #MakeoverMonday. Paging through the makeovers ignites immediate inspiration for your own work, provides insight into different perspectives, and highlights the techniques that truly make an impact. Explore the many approaches to visual data communication Think beyond the data and consider audience, stakeholders, and message Design your graphs to be intuitive and more communicative Assess the impact of layout, color, font, chart type, and other design choices Creating visual representation of complex datasets is tricky. There’s the mandate to include all relevant data in a clean, readable format that best illustrates what the data is saying—but there is also the designer’s impetus to showcase a command of the complexity and create multidimensional visualizations that “look cool.” #MakeoverMonday shows you the many ways to walk the line between simple reporting and design artistry to create exactly the visualization the situation requires. |
| excel data sets for practice: Python Data Science Handbook Jake VanderPlas, 2016-11-21 For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms |
| excel data sets for practice: Statistical Computing with R Maria L. Rizzo, 2007-11-15 Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditiona |
| excel data sets for practice: Econometrics in Practice Paul Turner, 2021-05-13 This book covers the econometric methods necessary for a practicing applied economist or data analyst. This requires both an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of topics which form the basis of more advanced option modules, such as time series methods in applied econometrics. To get the most out of these topics, companion files include Excel datasets and 4-color figures. It includes pull down menus to graph the data, calculate sample statistics and estimate regression equations. FEATURES: Integration of econometrics methods with statistical foundations Worked examples of all models considered in the text Includes Excel datasheets to facilitate estimation and application of models Features instructor ancillaries for use as a textbook The companion files and/or instructor resources are available online by emailing the publisher with proof of purchase at info@merclearning.com. |
| excel data sets for practice: DATA MINING K. P. SOMAN, SHYAM DIWAKAR, V. AJAY, 2006-01-01 Data Mining is an emerging technology that has made its way into science, engineering, commerce and industry as many existing inference methods are obsolete for dealing with massive datasets that get accumulated in data warehouses. This comprehensive and up-to-date text aims at providing the reader with sufficient information about data mining methods and algorithms so that they can make use of these methods for solving real-world problems. The authors have taken care to include most of the widely used methods in data mining with simple examples so as to make the text ideal for classroom learning. To make the theory more comprehensible to the students, many illustrations have been used, and this in turn explains how certain parameters of interest change as the algorithm proceeds. Designed as a textbook for the undergraduate and postgraduate students of computer science, information technology, and master of computer applications, the book can also be used for MBA courses in Data Mining in Business, Business Intelligence, Marketing Research, and Health Care Management. Students of Bioinformatics will also find the text extremely useful. CD-ROM INCLUDE’ The accompanying CD contains Large collection of datasets. Animation on how to use WEKA and ExcelMiner to do data mining. |
| excel data sets for practice: Generative Adversarial Networks in Practice Mehdi Ghayoumi, 2023-12-20 This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts. Key Features: Guides you through the complex world of GANs, demystifying their intricacies Accompanies your learning journey with real-world examples and practical applications Navigates the theory behind GANs, presenting it in an accessible and comprehensive way Simplifies the implementation of GANs using popular deep learning platforms Introduces various GAN architectures, giving readers a broad view of their applications Nurture your knowledge of AI with our comprehensive yet accessible content Practice your skills with numerous case studies and coding examples Reviews advanced GANs, such as DCGAN, cGAN, and CycleGAN, with clear explanations and practical examples Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject Takes you through GAN applications across different data types, highlighting their versatility Inspires the reader to explore beyond this book, fostering an environment conducive to independent learning and research Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge Empowers you with the skills and knowledge needed to confidently use GANs in your projects Prepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice. This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners. |
| excel data sets for practice: Evidence-Based Training Methods, 3rd Edition Ruth Colvin Clark, 2019-12-30 Let evidence guide your training. Your training is much more effective when your methods are based on evidence. In this third edition of Evidence-Based Training Methods, Ruth Colvin Clark offers concrete training guidance as she connects research to practice. This book is rich with examples of how research enhances training, and with it as your guide, you can incorporate evidence and learning psychology into your program design, development, and delivery decisions. New in this edition, Clark examines research on feedback with application tips for training as well as on using animations in critical thinking exercises. Games have also inspired a great deal of recent research, leading to updated information about which ones are effective and why. Ultimately, Clark advises focusing on instructional methods that are relatively inexpensive to implement and offers simple, effective changes. |
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| excel data sets for practice: The Practice of Research in Criminology and Criminal Justice Ronet D. Bachman, Russell K. Schutt, 2019-01-08 The authors are proud sponsors of the 2020 SAGE Keith Roberts Teaching Innovations Award—enabling graduate students and early career faculty to attend the annual ASA pre-conference teaching and learning workshop. Very practical approach to teaching research methods and very student friendly. This text breathes life into the research process. —Sherill Morris-Francis, Mississippi Valley State University The Practice of Research in Criminology and Criminal Justice, Seventh Edition demonstrates the vital role research plays in criminology and criminal justice by integrating in-depth, real-world case studies with a comprehensive discussion of research methods. By pairing research techniques with practical examples from the field, Ronet D. Bachman and Russell K. Schutt equip students to critically evaluate and confidently conduct research. The Seventh Edition of this best-selling text retains the strengths of previous editions while breaking ground with emergent research methods, enhanced tools for learning in the text and online, and contemporary, fascinating research findings. This edition incorporates new topics like intelligence-led policing, social network analysis (SNA), the evolution of cybercrime, and more. Students engage with the wide realm of research methods available to them, delve deeper into topics relevant to their field of study, and benefit from the wide variety of new exercises to help them practice as they learn. Give your students the SAGE edge! SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning. |
| excel data sets for practice: Integrating Research and Practice in Software Engineering Stan Jarzabek, Aneta Poniszewska-Marańda, Lech Madeyski, 2019-08-02 In this book, the authors highlight recent findings that hold the potential to improve software products or development processes; in addition, they help readers understand new concepts and technologies, and to see what it takes to migrate from old to new platforms. Some of the authors have spent most of their careers in industry, working at the frontiers of practice-based innovation, and are at the same time prominent researchers who have made significant academic contributions. Others work together with industry to test, in industrial settings, the methods they’ve developed in the lab. The choice of subject and authors represent the key elements of this book. Its respective chapters cover a wide range of topics, from cloud computing to agile development, applications of data science methods, re-engineering of aging applications into modern ones, and business and requirements engineering. Taken together, they offer a valuable asset for practitioners and researchers alike. |
| excel data sets for practice: Veridical Data Science Bin Yu, Rebecca L. Barter, 2024-10-15 Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science. Most textbooks present data science as a linear analytic process involving a set of statistical and computational techniques without accounting for the challenges intrinsic to real-world applications. Veridical Data Science, by contrast, embraces the reality that most projects begin with an ambiguous domain question and messy data; it acknowledges that datasets are mere approximations of reality while analyses are mental constructs. Bin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to assess the trustworthiness and relevance of data-driven results relative to three sources of uncertainty that arise throughout the data science life cycle: the human decisions and judgment calls made during data collection, cleaning, and modeling. By providing real-world data case studies, intuitive explanations of common statistical and machine learning techniques, and supplementary R and Python code, Veridical Data Science offers a clear and actionable guide for conducting responsible data science. Requiring little background knowledge, this lucid, self-contained textbook provides a solid foundation and principled framework for future study of advanced methods in machine learning, statistics, and data science. Presents the Predictability, Computability, and Stability (PCS) methodology for producing trustworthy data-driven results Teaches how a data science project should be conducted from beginning to end, including extensive discussion of the data scientist's decision-making process Cultivates critical thinking throughout the entire data science life cycle Provides practical examples and illuminating case studies of real-world data analysis problems with associated code, exercises, and solutions Suitable for advanced undergraduate and graduate students, domain scientists, and practitioners |
What does the "@" symbol mean in Excel formula (outside a table)
Oct 24, 2021 · Excel has recently introduced a huge feature called Dynamic arrays. And along with that, Excel also started to make a " substantial upgrade " to their formula language. One …
excel - How to show current user name in a cell? - Stack Overflow
if you don't want to create a UDF in VBA or you can't, this could be an alternative. =Cell("Filename",A1) this will give you the full file name, and from this you could get the user …
How to represent a DateTime in Excel - Stack Overflow
The underlying data type of a datetime in Excel is a 64-bit floating point number where the length of a day equals 1 and 1st Jan 1900 00:00 equals 1. So 11th June 2009 17:30 is about …
excel - Check whether a cell contains a substring - Stack Overflow
Sep 4, 2013 · Is there an in-built function to check if a cell contains a given character/substring? It would mean you can apply textual functions like Left/Right/Mid on a conditional basis without …
How to keep one variable constant with other one changing with …
The $ tells excel not to adjust that address while pasting the formula into new cells. Since you are dragging across rows, you really only need to freeze the row part: =(B0+4)/A$0
Excel: Searching for multiple terms in a cell - Stack Overflow
Feb 11, 2013 · In addition to the answer of @teylyn, I would like to add that you can put the string of multiple search terms inside a SINGLE cell (as opposed to using a different cell for each …
How to freeze the =today() function once data has been entered
Aug 2, 2015 · Excel's default format handling doesn't know to format this as date - so you would need to do this separately. More work than Ctrl + ; , but there might be some other use-cases …
excel - Return values from the row above to the current row
Jun 15, 2012 · To solve this problem in Excel, usually I would just type in the literal row number of the cell above, e.g., if I'm typing in Cell A7, I would use the formula =A6. Then if I copied that …
Assign a value to a cell depending on content of another cell
Jan 16, 2020 · I am trying to use the IF function to assign a value to a cell depending on another cells value So, if the value in column 'E' is 1, then the value in column G should be the same as …
excel - Remove leading or trailing spaces in an entire column of …
Mar 6, 2012 · I've found that the best (and easiest) way to delete leading, trailing (and excessive) spaces in Excel is to use a third-party plugin. I've been using ASAP Utilities for Excel and it …
What does the "@" symbol mean in Excel formula (outsid…
Oct 24, 2021 · Excel has recently introduced a huge feature called Dynamic arrays. And along with that, Excel also started to make a " …
excel - How to show current user name in a cell? - Stack O…
if you don't want to create a UDF in VBA or you can't, this could be an alternative. =Cell("Filename",A1) this will give you the full file name, and …
How to represent a DateTime in Excel - Stack Overflow
The underlying data type of a datetime in Excel is a 64-bit floating point number where the length of a day equals 1 and 1st Jan 1900 00:00 …
excel - Check whether a cell contains a substring - Stack O…
Sep 4, 2013 · Is there an in-built function to check if a cell contains a given character/substring? It would mean you can apply textual …
How to keep one variable constant with other one chan…
The $ tells excel not to adjust that address while pasting the formula into new cells. Since you are dragging across rows, you really only need to …
