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| excel basics for data analysis ibm: 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 basics for data analysis ibm: Data Analysis with IBM SPSS Statistics Kenneth Stehlik-Barry, Anthony J. Babinec, 2017-09-22 Master data management & analysis techniques with IBM SPSS Statistics 24 About This Book Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data Choose the right statistical technique to analyze different types of data and build efficient models from your data with ease Overcome any hurdle that you might come across while learning the different SPSS Statistics concepts with clear instructions, tips and tricks Who This Book Is For This book is designed for analysts and researchers who need to work with data to discover meaningful patterns but do not have the time (or inclination) to become programmers. We assume a foundational understanding of statistics such as one would learn in a basic course or two on statistical techniques and methods. What You Will Learn Install and set up SPSS to create a working environment for analytics Techniques for exploring data visually and statistically, assessing data quality and addressing issues related to missing data How to import different kinds of data and work with it Organize data for analytical purposes (create new data elements, sampling, weighting, subsetting, and restructure your data) Discover basic relationships among data elements (bivariate data patterns, differences in means, correlations) Explore multivariate relationships Leverage the offerings to draw accurate insights from your research, and benefit your decision-making In Detail SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease. Style and approach Provides a practical orientation to understanding a set of data and examining the key relationships among the data elements. Shows useful visualizations to enhance understanding and interpretation. Outlines a roadmap that focuses the process so decision regarding how to proceed can be made easily. |
| excel basics for data analysis ibm: Business Statistics Using EXCEL and SPSS Nick Lee, Mike Peters, 2015-12-16 Takes the challenging and makes it understandable. The book contains useful advice on the application of statistics to a variety of contexts and shows how statistics can be used by managers in their work.′ - Dr Terri Byers, Assistant Professor, University Of New Brunswick, Canada A book about introductory quantitative analysis, the authors show both how and why quantitative analysis is useful in the context of business and management studies, encouraging readers to not only memorise the content but to apply learning to typical problems. Fully up-to-date with comprehensive coverage of IBM SPSS and Microsoft Excel software, the tailored examples illustrate how the programmes can be used, and include step-by-step figures and tables throughout. A range of ‘real world’ and fictional examples, including The Ballad of Eddie the Easily Distracted and Esha′s Story help bring the study of statistics alive. A number of in-text boxouts can be found throughout the book aimed at readers at varying levels of study and understanding Back to Basics for those struggling to understand, explain concepts in the most basic way possible - often relating to interesting or humorous examples Above and Beyond for those racing ahead and who want to be introduced to more interesting or advanced concepts that are a little bit outside of what they may need to know Think it over get students to stop, engage and reflect upon the different connections between topics A range of online resources including a set of data files and templates for the reader following in-text examples, downloadable worksheets and instructor materials, answers to in-text exercises and video content compliment the book. An ideal resource for undergraduates taking introductory statistics for business, or for anyone daunted by the prospect of tackling quantitative analysis for the first time. |
| excel basics for data analysis ibm: Interpreting Quantitative Data with SPSS Rachad Antonius, 2003-01-22 This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied. |
| excel basics for data analysis ibm: Basic Marketing Research Alvin C. Burns, Ronald F. Bush, 2004-07-01 For undergraduate Marketing Research courses. Best-selling authors Burns and Bush are proud to introduce Basic Marketing Research, the first textbook to utitlize EXCEL as a data analysis tool. Each copy includes XL Data Analyst(R), a user-friendly Excel add-in for data analysis. This book is also a first in that it's a streamlined paperback with an orientation that leans more toward how to use marketing research information to make decisions vs. how to be a provider of marketing research information. |
| excel basics for data analysis ibm: Practical Statistics David Kremelberg, 2010-03-18 Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages. |
| excel basics for data analysis ibm: IBM Cognos Dynamic Query Nigel Campbell, Henk Cazemier, Robert Hatfield, Martin Petitclerc, Glen Seeds, Jason Tavoularis, IBM Redbooks, 2013-09-12 This IBM® Redbooks® publication explains how IBM Cognos® Business Intelligence (BI) administrators, authors, modelers, and power users can use the dynamic query layer effectively. It provides guidance for determining which technology within the dynamic query layer can best satisfy your business requirements. Administrators can learn how to tune the query service effectively and preferred practices for managing their business intelligence content. This book includes information about metadata modeling of relational data sources with IBM Cognos Framework Manager. It includes considerations that can help you author high-performing applications that satisfy analytical requirements of users. This book provides guidance for troubleshooting issues related to the dynamic query layer of Cognos BI. Related documents: Solution Guide : Big Data Analytics with IBM Cognos BI Dynamic Query Blog post : IBM Cognos Dynamic Query Extensibility |
| excel basics for data analysis ibm: Data Visualization with Excel Dashboards and Reports Dick Kusleika, 2021-02-05 Large corporations like IBM and Oracle are using Excel dashboards and reports as a Business Intelligence tool, and many other smaller businesses are looking to these tools in order to cut costs for budgetary reasons. An effective analyst not only has to have the technical skills to use Excel in a productive manner but must be able to synthesize data into a story, and then present that story in the most impactful way. Microsoft shows its recognition of this with Excel. In Excel, there is a major focus on business intelligence and visualization. Data Visualization with Excel Dashboards and Reports fills the gap between handling data and synthesizing data into meaningful reports. This title will show readers how to think about their data in ways other than columns and rows. Most Excel books do a nice job discussing the individual functions and tools that can be used to create an Excel Report. Titles on Excel charts, Excel pivot tables, and other books that focus on Tips and Tricks are useful in their own right; however they don't hit the mark for most data analysts. The primary reason these titles miss the mark is they are too focused on the mechanical aspects of building a chart, creating a pivot table, or other functionality. They don't offer these topics in the broader picture by showing how to present and report data in the most effective way. What are the most meaningful ways to show trending? How do you show relationships in data? When is showing variances more valuable than showing actual data values? How do you deal with outliers? How do you bucket data in the most meaningful way? How do you show impossible amounts of data without inundating your audience? In Data Visualization with Excel Reports and Dashboards, readers will get answers to all of these questions. Part technical manual, part analytical guidebook; this title will help Excel users go from reporting data with simple tables full of dull numbers, to creating hi-impact reports and dashboards that will wow management both visually and substantively. This book offers a comprehensive review of a wide array of technical and analytical concepts that will help users create meaningful reports and dashboards. After reading this book, the reader will be able to: Analyze large amounts of data and report their data in a meaningful way Get better visibility into data from different perspectives Quickly slice data into various views on the fly Automate redundant reporting and analyses Create impressive dashboards and What-If analyses Understand the fundamentals of effective visualization Visualize performance comparisons Visualize changes and trends over time |
| excel basics for data analysis ibm: 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 basics for data analysis ibm: 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 basics for data analysis ibm: Data Science For Dummies Lillian Pierson, 2015-02-20 Discover how data science can help you gain in-depth insight into your business – the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer covering all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad aspects of the topic, including the sometimes intimidating field of big data and data science, it is not an instructional manual for hands-on implementation. Here’s what to expect in Data Science for Dummies: Provides a background in big data and data engineering before moving on to data science and how it’s applied to generate value. Includes coverage of big data frameworks and applications like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL. Explains machine learning and many of its algorithms, as well as artificial intelligence and the evolution of the Internet of Things. Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate. It’s a big, big data world out there – let Data Science For Dummies help you get started harnessing its power so you can gain a competitive edge for your organization. |
| excel basics for data analysis ibm: Microsoft Excel Functions Quick Reference Mandeep Mehta, 2021-01-08 This condensed syntax reference presents the essential Excel function syntax in a well-organized format that can be used as a quick and handy reference. You can use it to improve your Excel knowledge and increase your productivity. It will help you upgrade the quality of your data analysis, dashboards, models, and templates. The Microsoft Excel Functions Quick Reference helps you set up workbooks, enter data, and format it for easier viewing. It starts by giving an overview of Excel functions explaining the different types of Excel functions available followed by an understanding of string functions and date functions. It then covers time, lookup, aggregate, and logical functions along with practice problems. Further, you will see math functions and information functions in Excel. You will also be able to create sophisticated forecast worksheets, key performance indicators (KPIs), and timelines. Each function in the text is illustrated by helpful, illuminating examples. With this book by your side, you'll always have the answer to your Excel function syntax questions. What You Will Learn Work with basic Excel functions Use the LOOKUP function Take advantage of new functions in information functions Create a mega formula Who This Book Is For Administrators, analysts, and anyone else working with Microsoft Excel. |
| excel basics for data analysis ibm: Performing Data Analysis Using IBM SPSS Lawrence S. Meyers, Glenn C. Gamst, A. J. Guarino, 2013-08-12 Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output. Designed as a user’s guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis. The book provides in-depth chapter coverage of: IBM SPSS statistical output Descriptive statistics procedures Score distribution assumption evaluations Bivariate correlation Regressing (predicting) quantitative and categorical variables Survival analysis t Test ANOVA and ANCOVA Multivariate group differences Multidimensional scaling Cluster analysis Nonparametric procedures for frequency data Performing Data Analysis Using IBM SPSS is an excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry. |
| excel basics for data analysis ibm: Microsoft Excel 2010 Wayne L. Winston, 2011 An award-winning business professor and corporate consultant shares the best of his real-world experience in this practical, scenario-focused guide--fully updated for Excel 2010. |
| excel basics for data analysis ibm: Management Research Susan Rose, Nigel Spinks, Ana Isabel Canhoto, 2014-07-25 For many post-graduate students undertaking a research project for the first time is a daunting prospect. Gaining the knowledge and skills needed to do research typically has to be done alongside carrying out the project itself. Students often have to conduct their research independently, perhaps with limited tutor contact. What is needed in such situations is a resource that supports the new researcher on every step of the research journey, from defining the project to communicating its findings. Management Research: Applying the Principles provides just such a resource. Structured around the key stages of a research project, it is designed to provide answers to the questions faced by new researchers but without neglecting the underlying principles of good research. Each chapter includes ‘next steps’ activities to help readers apply the content to their own live research project. The companion website provides extensive resources, including video tutorials, to support the development of practical research skills. The text reflects the richness and variety of current business and management research both in its presentation of methods and techniques and its choice of examples drawn from different subject disciplines, industries and organizations. Management Research: Applying the Principles combines diversity of coverage with a singularity of purpose: to help students complete their research project to a rigorous standard. |
| excel basics for data analysis ibm: Introducing Microsoft Power BI Alberto Ferrari, Marco Russo, 2016-07-07 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introducing Microsoft Power BI enables you to evaluate when and how to use Power BI. Get inspired to improve business processes in your company by leveraging the available analytical and collaborative features of this environment. Be sure to watch for the publication of Alberto Ferrari and Marco Russo's upcoming retail book, Analyzing Data with Power BI and Power Pivot for Excel (ISBN 9781509302765). Go to the book's page at the Microsoft Press Store here for more details:http://aka.ms/analyzingdata/details. Learn more about Power BI at https://powerbi.microsoft.com/. |
| excel basics for data analysis ibm: BASIC BUSINESS ANALYTICS USING R Dr. Mahavir M. Shetiya, Prof. Snehal V. Bhambure, 2023-11-10 Buy BASIC BUSINESS ANALYTICS USING R e-Book for Mba 2nd Semester in English language specially designed for SPPU ( Savitribai Phule Pune University ,Maharashtra) By Thakur publication. |
| excel basics for data analysis ibm: IBM SPSS by Example Alan C. Elliott, Wayne A. Woodward, 2014-12-31 The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s cut to the chase IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration. |
| excel basics for data analysis ibm: Business Statistics Using EXCEL and SPSS Nick Lee, Mike Peters, 2015-12-16 Takes the challenging and makes it understandable. The book contains useful advice on the application of statistics to a variety of contexts and shows how statistics can be used by managers in their work.′ - Dr Terri Byers, Assistant Professor, University Of New Brunswick, Canada A book about introductory quantitative analysis, the authors show both how and why quantitative analysis is useful in the context of business and management studies, encouraging readers to not only memorise the content but to apply learning to typical problems. Fully up-to-date with comprehensive coverage of IBM SPSS and Microsoft Excel software, the tailored examples illustrate how the programmes can be used, and include step-by-step figures and tables throughout. A range of ‘real world’ and fictional examples, including The Ballad of Eddie the Easily Distracted and Esha′s Story help bring the study of statistics alive. A number of in-text boxouts can be found throughout the book aimed at readers at varying levels of study and understanding Back to Basics for those struggling to understand, explain concepts in the most basic way possible - often relating to interesting or humorous examples Above and Beyond for those racing ahead and who want to be introduced to more interesting or advanced concepts that are a little bit outside of what they may need to know Think it over get students to stop, engage and reflect upon the different connections between topics A range of online resources including a set of data files and templates for the reader following in-text examples, downloadable worksheets and instructor materials, answers to in-text exercises and video content compliment the book. An ideal resource for undergraduates taking introductory statistics for business, or for anyone daunted by the prospect of tackling quantitative analysis for the first time. |
| excel basics for data analysis ibm: Advanced Excel for Scientific Data Analysis Robert De Levie, 2004 This guide to Excel focuses on three areas--least squares, Fourier transformation, and digital simulation. It illustrates the techniques with detailed examples, many drawn from the scientific literature. It also includes and describes a number of sample macros and functions to facilitate common data analysis tasks. De Levie is affiliated with Bowdoin College. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com). |
| excel basics for data analysis ibm: SPSS Statistics For Dummies Jesus Salcedo, Keith McCormick, 2020-09-09 The fun and friendly guide to mastering IBM’s Statistical Package for the Social Sciences Written by an author team with a combined 55 years of experience using SPSS, this updated guide takes the guesswork out of the subject and helps you get the most out of using the leader in predictive analysis. Covering the latest release and updates to SPSS 27.0, and including more than 150 pages of basic statistical theory, it helps you understand the mechanics behind the calculations, perform predictive analysis, produce informative graphs, and more. You’ll even dabble in programming as you expand SPSS functionality to suit your specific needs. Master the fundamental mechanics of SPSS Learn how to get data into and out of the program Graph and analyze your data more accurately and efficiently Program SPSS with Command Syntax Get ready to start handling data like a pro—with step-by-step instruction and expert advice! |
| excel basics for data analysis ibm: Guerilla Data Analysis Using Microsoft Excel Bill Jelen, 2002 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. |
| excel basics for data analysis ibm: SPSS Statistics for Data Analysis and Visualization Keith McCormick, Jesus Salcedo, 2017-05-01 Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These hidden tools can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need. |
| excel basics for data analysis ibm: Exploratory and Descriptive Statistics Julie Scott Jones, Goldring,, 2022-03-01 Nervous about statistics? This guide offers you a clear, straight to the point break down of exploratory and descriptive statistics and its potential. Anchored by lots of examples and exercises to enhance your learning, this book will give you the know-how and confidence needed to succeed on your quantitative research journey. |
| excel basics for data analysis ibm: Multivariate Analysis Klaus Backhaus, Bernd Erichson, Sonja Gensler, Rolf Weiber, Thomas Weiber, 2023-06-28 Data can be extremely valuable if we are able to extract information from them. This is why multivariate data analysis is essential for business and science. This book offers an easy-to-understand introduction to the most relevant methods of multivariate data analysis. It is strictly application-oriented, requires little knowledge of mathematics and statistics, demonstrates the procedures with numerical examples and illustrates each method via a case study solved with IBM’s statistical software package SPSS. Extensions of the methods and links to other procedures are discussed and recommendations for application are given. An introductory chapter presents the basic ideas of the multivariate methods covered in the book and refreshes statistical basics which are relevant to all methods. For the 2nd edition, all chapters were checked and calculated using the current version of IBM SPSS. Contents Introduction to empirical data analysis Regression analysis Analysis of variance Discriminant analysis Logistic regression Contingency analysis Factor analysis Cluster analysis Conjoint analysis The original German version is now available in its 17th edition. In 2015, this book was honored by the Federal Association of German Market and Social Researchers as “the textbook that has shaped market research and practice in German-speaking countries”. A Chinese version is available in its 3rd edition. On the website www.multivariate-methods.info, the authors further analyze the data with Excel and R and provide additional material to facilitate the understanding of the different multivariate methods. In addition, interactive flashcards are available to the reader for reviewing selected focal points. Download the Springer Nature Flashcards App and use exclusive content to test your knowledge. |
| excel basics for data analysis ibm: Categorical and Nonparametric Data Analysis E. Michael Nussbaum, 2024-05-30 Now in its second edition, this book provides a focused, comprehensive overview of both categorical and nonparametric statistics, offering a conceptual framework for choosing the most appropriate test in various scenarios. The book’s clear explanations and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of these techniques. Basic statistics and probability are reviewed for those needing a refresher with mathematical derivations placed in optional appendices. Highlights include the following: • Three chapters co-authored with Edgar Brunner address modern nonparametric techniques, along with accompanying R code. • Unique coverage of both categorical and nonparametric statistics better prepares readers to select the best technique for particular research projects. • Designed to be used with most statistical packages, clear examples of how to use the tests in SPSS, R, and Excel foster conceptual understanding. • Exploring the Concept boxes integrated throughout prompt students to draw links between the concepts to deepen understanding. • Fully developed Instructor and Student Resources featuring datasets for the book's problems and a guide to R, and for the instructor PowerPoints, author's syllabus, and answers to even-numbered problems. Intended for graduate or advanced undergraduate courses in categorical and nonparametric statistics taught in psychology, education, human development, sociology, political science, and other social and life sciences. |
| excel basics for data analysis ibm: Knowledge into Action Danny P. Wallace, Connie J. Van Fleet, 2012-06-12 The only book currently available that comprehensively integrates research and evaluation for evidence-based library and information science practice. Numerous books cover research and evaluation in general, but not within the context of library and information science. Many others cover the field of library and information science overall but with little focus on research. Knowledge into Action: Research and Evaluation in Library and Information Science offers in a single volume, an expert introduction to these two distinct, yet deeply interrelated, phases of information-gathering as they are practiced in the information sciences. Knowledge into Action takes readers through the core principles, working processes, and practical tools for conducting and evaluating research in library and information science, enhancing the presentation with examples, informational graphics, study questions, and exercises directly relevant to this field. It is a welcomed resource for students and scholars who want to use appropriate techniques for gathering and assessing research, as well as information professionals looking to improve services at their libraries or information centers. The book is also designed to educate practitioners as consumers of the research and evaluation literature and as active participants in professional conferences, meetings, and workshops. |
| excel basics for data analysis ibm: Financial Data Science with SAS Babatunde O Odusami, 2024-06-14 Explore financial data science using SAS. Financial Data Science with SAS provides readers with a comprehensive explanation of the theoretical and practical implementation of the various types of analytical techniques and quantitative tools that are used in the financial services industry. This book shows readers how to implement data visualization, simulation, statistical predictive models, machine learning models, and financial optimizations using real-world examples in the SAS Analytics environment. Each chapter ends with practice exercises that include use case scenarios to allow readers to test their knowledge. Designed for university students and financial professionals interested in boosting their data science skills, Financial Data Science with SAS is an essential reference guide for understanding how data science is used in the financial services industry and for learning how to use SAS to solve complex business problems. |
| excel basics for data analysis ibm: Data Science from Scratch Joel Grus, 2015-04-14 Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases |
| excel basics for data analysis ibm: 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 basics for data analysis ibm: Auditor Essentials Hernan Murdock, 2018-09-21 Internal auditors must know many concepts, techniques, control frameworks, and remain knowledgeable despite the many changes occurring in the marketplace and their profession. This easy to use reference makes this process easier and ensures auditors can obtain needed information quickly and accurately. This book consists of 100 topics, concepts, tips, tools and techniques that relate to how internal auditors interact with internal constitutencies and addresses a variety of technical and non-technical subjects. Non-auditors have an easy-to-use guide that increases their understanding of what internal auditors do and how, making it easier for them to partner with them more effectively. |
| excel basics for data analysis ibm: Dynamic Warehousing Chuck Ballard, John Rollins, Jo Ramos, Andy Perkins, Richard Hale, 2007-01-01 |
| excel basics for data analysis ibm: Data Analysis Using SPSS for Windows Versions 8 - 10 Jeremy J Foster, 2001-03-20 A new edition of this best-selling introductory book to cover the latest SPSS versions 8.0 - 10.0 This book is designed to teach beginners how to use SPSS for Windows, the most widely used computer package for analysing quantitative data. Written in a clear, readable and non-technical style the author explains the basics of SPSS including the input of data, data manipulation, descriptive analyses and inferential techniques, including; - creating using and merging data files - creating and printing graphs and charts - parametric tests including t-tests, ANOVA, GLM - correlation, regression and factor analysis - non parametric tests and chi square reliability - obtaining neat print outs and tables - includes a CD-Rom containing example data files, syntax files, output files and Excel spreadsheets. |
| excel basics for data analysis ibm: EBOOK: SPSS Survival Manual Julie Pallant, 2016-05-16 The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report. For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential text. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. This sixth edition is fully revised and updated to accommodate changes to IBM SPSS procedures, screens and output. It covers new SPSS tools for generating graphs and non-parametric statistics, importing data, and calculating dates. |
| excel basics for data analysis ibm: How to Find Inter-Groups Differences Using Spss/Excel/Web Tools in Common Experimental Designs P.Y. Cheng, 2014-05-16 Book 1: How to find Inter-Groups Differences Using SPSS/Excel/Web Tools In Common Experimental Designs Book 3: Analysis of Experimental Data Using Excel as if using SPSS A Break Through English Version Book 4: ???????????????? Excel ???? SPSS |
| excel basics for data analysis ibm: Winning with Data Tomasz Tunguz, Frank Bien, 2016-05-26 Crest the data wave with a deep cultural shift Winning with Data explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Authors Tomasz Tunguz and Frank Bien draw on extensive background in big data, business intelligence, and business strategy to provide a blueprint for companies looking to move head-on into the data wave. Instrumentation is discussed in detail, but the core of the change is in the culture—this book provides sound guidance on building the type of organizational culture that creates and leverages data daily, in every aspect of the business. Real-world examples illustrate these important concepts at work: you'll learn how data helped Warby-Parker disrupt a $13 billion monopolized market, how ThredUp uses data to process more than 20 thousand items of clothing every day, how Venmo leverages data to build better products, how HubSpot empowers their salespeople to be more productive, and more. From decision making and strategy to shipping and sales, this book shows you how data makes better business. Big data has taken on buzzword status, but there is little real guidance for companies seeking everyday business data solutions. This book takes a deeper look at big data in business, and shows you how to shift internal culture ahead of the curve. Understand the changes a data culture brings to companies Instrument your company for maximum benefit Utilize data to optimize every aspect of your business Improve decision making and transform business strategy Big data is becoming the number-one topic in business, yet no one is asking the right questions. Leveraging the full power of data requires more than good IT—organization-wide buy-in is essential for long-term success. Winning with Data is the expert guide to making data work for your business, and your needs. |
| excel basics for data analysis ibm: Data Strategy Bernard Marr, 2017-04-03 BRONZE RUNNER UP: Axiom Awards 2018 - Business Technology Category Less than 0.5 per cent of all data is currently analyzed and used. However, business leaders and managers cannot afford to be unconcerned or sceptical about data. Data is revolutionizing the way we work and it is the companies that view data as a strategic asset that will survive and thrive. Data Strategy is a must-have guide to creating a robust data strategy. Explaining how to identify your strategic data needs, what methods to use to collect the data and, most importantly, how to translate your data into organizational insights for improved business decision-making and performance, this is essential reading for anyone aiming to leverage the value of their business data and gain competitive advantage. Packed with case studies and real-world examples, advice on how to build data competencies in an organization and crucial coverage of how to ensure your data doesn't become a liability, Data Strategy will equip any organization with the tools and strategies it needs to profit from Big Data, analytics and the Internet of Things (IoT). |
| excel basics for data analysis ibm: Spss Survival Manual Pallant, Julie, 2013-05-01 This bestselling guide, covering up to version 21 of the SPSS software, guides you through the entire research process. |
| excel basics for data analysis ibm: Deployment Guide for InfoSphere Guardium Whei-Jen Chen, Boaz Barkai, Joe M DiPietro, Vladislav Langman, Daniel Perlov, Roy Riah, Yosef Rozenblit, Abdiel Santos, IBM Redbooks, 2015-04-14 IBM® InfoSphere® Guardium® provides the simplest, most robust solution for data security and data privacy by assuring the integrity of trusted information in your data center. InfoSphere Guardium helps you reduce support costs by automating the entire compliance auditing process across heterogeneous environments. InfoSphere Guardium offers a flexible and scalable solution to support varying customer architecture requirements. This IBM Redbooks® publication provides a guide for deploying the Guardium solutions. This book also provides a roadmap process for implementing an InfoSphere Guardium solution that is based on years of experience and best practices that were collected from various Guardium experts. We describe planning, installation, configuration, monitoring, and administrating an InfoSphere Guardium environment. We also describe use cases and how InfoSphere Guardium integrates with other IBM products. The guidance can help you successfully deploy and manage an IBM InfoSphere Guardium system. This book is intended for the system administrators and support staff who are responsible for deploying or supporting an InfoSphere Guardium environment. |
| excel basics for data analysis ibm: Python for Data Analysis Wes McKinney, 2017-09-25 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 |
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 …
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 (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 …
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 …
