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| excel add ins for statistical analysis: 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 add ins for statistical analysis: Statistical Analysis Conrad Carlberg, 2014-04-04 Use Excel 2013’s statistical tools to transform your data into knowledge Conrad Carlberg shows how to use Excel 2013 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features, including recently introduced consistency functions. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes. You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, this edition adds two more chapters on inferential statistics, covering crucial topics ranging from experimental design to the statistical power of F tests. Becoming an expert with Excel statistics has never been easier! You’ll find crystal-clear instructions, insider insights, and complete step-by-step projects—all complemented by extensive web-based resources. Master Excel’s most useful descriptive and inferential statistical tools Tell the truth with statistics—and recognize when others don’t Accurately summarize sets of values Infer a population’s characteristics from a sample’s frequency distribution Explore correlation and regression to learn how variables move in tandem Use Excel consistency functions such as STDEV.S() and STDEV.P() Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in Use ANOVA to test differences between more than two means Explore statistical power by manipulating mean differences, standard errors, directionality, and alpha Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2013 shortcuts |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: Data Analysis for Managers with Microsoft Excel S. Christian Albright, Wayne L. Winston, Christopher James Zappe, 2004 This text presents statistical concepts and methods in a unified, modern, spreadsheet-oriented approach. Featuring a wealth of business applications, this examples-based text illustrates a variety of statistical methods to help students analyze data sets and uncover important information to aid decision-making. DATA ANALYSIS FOR MANAGERS contains professional StatPro add-ins for Microsoft Excel from Palisade, valued at one hundred fifty dollars packaged at no additional cost with every new text. |
| excel add ins for statistical analysis: Data Analysis with Microsoft Excel Kenneth N. Berk, Patrick Carey, 2009 The latest book from Cengage Learning on Data Analysis with Microsoft« ExcelÖ |
| excel add ins for statistical analysis: Using Microsoft Excel for Social Research Charlotte Brookfield, 2021-01-20 Full of practical advice and real-world examples, this step-by-step guide offers you an accessible introduction to doing quantitative social research using Microsoft Excel. |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: 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 add ins for statistical analysis: Excel Data Analysis For Dummies Paul McFedries, 2018-11-13 Take Excel to the next level Excel is the world’s leading spreadsheet application. It’s a key module in Microsoft Office—the number-one productivity suite—and it is the number-one business intelligence tool. An Excel dashboard report is a visual presentation of critical data and uses gauges, maps, charts, sliders, and other graphical elements to present complex data in an easy-to-understand format. Excel Data Analysis For Dummies explains in depth how to use Excel as a tool for analyzing big data sets. In no time, you’ll discover how to mine and analyze critical data in order to make more informed business decisions. Work with external databases, PivotTables, and Pivot Charts Use Excel for statistical and financial functions and data sharing Get familiar with Solver Use the Small Business Finance Manager If you’re familiar with Excel but lack a background in the technical aspects of data analysis, this user-friendly book makes it easy to start putting it to use for you. |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: Statistical Analysis of Contingency Tables Morten Fagerland, Stian Lydersen, Petter Laake, 2017-07-28 Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website. |
| excel add ins for statistical analysis: R Through Excel Richard M. Heiberger, Erich Neuwirth, 2010-01-23 In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new programming language. |
| excel add ins for statistical analysis: Data Analysis in Plain English with Microsoft Excel Harvey J. Brightman, 1999 Harvey Brightman's accessible, easy-to-understand new book focuses on helping readers learn essential statistical concepts and data analysis. In an intuitive and non-mathematical writing style, Brightman uses actual business applications and covers practical insights in business problem solving using Microsoft Excel as the primary computational tool. His clear, to-the-point presentation gives students a 'map' for learning what data analysis techniques to use and when to use them. Brightman presents descriptive and inferential methods in sequential chapters, and introduces probability only as needed and then only on a very limited basis. |
| excel add ins for statistical analysis: R for Microsoft® Excel Users Conrad Carlberg, 2016-11-11 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. Microsoft Excel can perform many statistical analyses, but thousands of business users and analysts are now reaching its limits. R, in contrast, can perform virtually any imaginable analysis–if you can get over its learning curve. In R for Microsoft® Excel Users, Conrad Carlberg shows exactly how to get the most from both programs. Drawing on his immense experience helping organizations apply statistical methods, Carlberg reviews how to perform key tasks in Excel, and then guides you through reaching the same outcome in R–including which packages to install and how to access them. Carlberg offers expert advice on when and how to use Excel, when and how to use R instead, and the strengths and weaknesses of each tool. Writing in clear, understandable English, Carlberg combines essential statistical theory with hands-on examples reflecting real-world challenges. By the time you’ve finished, you’ll be comfortable using R to solve a wide spectrum of problems–including many you just couldn’t handle with Excel. • Smoothly transition to R and its radically different user interface • Leverage the R community’s immense library of packages • Efficiently move data between Excel and R • Use R’s DescTools for descriptive statistics, including bivariate analyses • Perform regression analysis and statistical inference in R and Excel • Analyze variance and covariance, including single-factor and factorial ANOVA • Use R’s mlogit package and glm function for Solver-style logistic regression • Analyze time series and principal components with R and Excel |
| excel add ins for statistical analysis: An Excel Companion for an Introductory Statistics Course in Social and Behavioral Sciences Alejandro A Lazarte, 2020-07-21 An Excel Companion for an Introductory Statistics Course in Social and Behavioral Sciences introduces students to the use of Excel to perform basic and intermediate data analyses that are common in the social and behavioral sciences. The companion focuses on using Excel to perform the types of analyses covered in most textbooks within the discipline. The book covers computations of descriptive statistics, hypothesis testing for means up to one-way ANOVA, correlation, and simple linear regression. Students learn how to perform summation in Excel, build pivot tables, and create compelling and accurate distribution graphs. Measures of central tendency, variability, and location are covered. Additional chapters explore normal distribution, random numbers, probability distributions, cross tabulations, and more. All Excel computations described in the companion rely on basic Excel functions and the Data Analysis ToolPak add-on that comes with Excel. Highly practical and accessible, An Excel Companion for an Introductory Statistics Course in Social and Behavioral Sciences is an ideal supplementary text for introductory statistics courses. |
| excel add ins for statistical analysis: Health Services Research and Analytics Using Excel Nalin Johri, PhD, MPH, 2020-02-01 Your all-in-one resource for quantitative, qualitative, and spatial analyses in Excel® using current real-world healthcare datasets. Health Services Research and Analytics Using Excel® is a practical resource for graduate and advanced undergraduate students in programs studying healthcare administration, public health, and social work as well as public health workers and healthcare managers entering or working in the field. This book provides one integrated, application-oriented resource for common quantitative, qualitative, and spatial analyses using only Excel. With an easy-to-follow presentation of qualitative and quantitative data, students can foster a balanced decision-making approach to financial data, patient statistical data and utilization information, population health data, and quality metrics while cultivating analytical skills that are necessary in a data-driven healthcare world. Whereas Excel is typically considered limited to quantitative application, this book expands into other Excel applications based on spatial analysis and data visualization represented through 3D Maps as well as text analysis using the free add-in in Excel. Chapters cover the important methods and statistical analysis tools that a practitioner will face when navigating and analyzing data in the public domain or from internal data collection at their health services organization. Topics covered include importing and working with data in Excel; identifying, categorizing, and presenting data; setting bounds and hypothesis testing; testing the mean; checking for patterns; data visualization and spatial analysis; interpreting variance; text analysis; and much more. A concise overview of research design also provides helpful background on how to gather and measure useful data prior to analyzing in Excel. Because Excel is the most common data analysis software used in the workplace setting, all case examples, exercises, and tutorials are provided with the latest updates to the Excel software from Office365 ProPlus® and newer versions, including all important “Add-ins” such as 3D Maps, MeaningCloud, and Power Pivots, among others. With numerous practice problems and over 100 step-by-step videos, Health Services Research and Analytics Using Excel® is an extremely practical tool for students and health service professionals who must know how to work with data, how to analyze it, and how to use it to improve outcomes unique to healthcare settings. Key Features: Provides a competency-based analytical approach to health services research using Excel Includes applications of spatial analysis and data visualization tools based on 3D Maps in Excel Lists select sources of useful national healthcare data with descriptions and website information Chapters contain case examples and practice problems unique to health services All figures and videos are applicable to Office365 ProPlus Excel and newer versions Contains over 100 step-by-step videos of Excel applications covered in the chapters and provides concise video tutorials demonstrating solutions to all end-of-chapter practice problems Robust Instructor ancillary package that includes Instructor’s Manual, PowerPoints, and Test Bank |
| excel add ins for statistical analysis: Statistical Analysis Conrad Carlberg, 2017-11-15 USE EXCEL’S STATISTICAL TOOLS TO TRANSFORM YOUR DATA INTO KNOWLEDGE Nationally recognized Excel expert Conrad Carlberg shows you how to use Excel 2016 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples and downloadable workbooks, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes. You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, Carlberg offers insightful coverage of crucial topics ranging from experimental design to the statistical power of F tests. Updated for Excel 2016, this guide covers both modern consistency functions and legacy compatibility functions. Becoming an expert with Excel statistics has never been easier! In this book, you’ll find crystal-clear instructions, insider insights, and complete step-by-step guidance. Master Excel’s most useful descriptive and inferential statistical tools Understand how values cluster together or disperse, and how variables move or classify jointly Tell the truth with statistics—and recognize when others don’t Infer a population’s characteristics from a sample’s frequency distribution Explore correlation and regression to learn how variables move in tandem Use Excel consistency functions such as STDEV.S( ) and STDEV.P( ) Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in Identify skewed distributions using Excel’s new built-in box-and-whisker plots and histograms Evaluate statistical power and control risk Explore how randomized block and split plot designs alter the derivation of F-ratios Use coded multiple regression analysis to perform ANOVA with unbalanced factorial designs Analyze covariance with ANCOVA, and properly use multiple covariance Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2016 shortcuts |
| excel add ins for statistical analysis: Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications, Third Edition Johan Gabrielsson, Daniel Weiner, 2001-11-30 This is a revised and very expanded version of the previous second edition of the book. Pharmacokinetic and Pharmacodynamic Data Analysis provides an introduction into pharmacokinetic and pharmacodynamic concepts using simple illustrations and reasoning. It describes ways in which pharmacodynamic and pharmacodynamic theory may be used to give insight into modeling questions and how these questions can in turn lead to new knowledge. This book differentiates itself from other texts in this area in that it bridges the gap between relevant theory and the actual application of the theory to real life situations. The book is divided into two parts; the first introduces fundamental principles of PK and PD concepts, and principles of mathematical modeling, while the second provides case studies obtained from drug industry and academia. Topics included in the first part include a discussion of the statistical principles of model fitting, including how to assess the adequacy of the fit of a model, as well as strategies for selection of time points to be included in the design of a study. The first part also introduces basic pharmacokinetic and pharmacodynamic concepts, including an excellent discussion of effect compartment (link) models as well as indirect response models. The second part of the text includes over 70 modeling case studies. These include a discussion of the selection of the model, derivation of initial parameter estimates and interpretation of the corresponding output. Finally, the authors discuss a number of pharmacodynamic modeling situations including receptor binding models, synergy, and tolerance models (feedback and precursor models). This book will be of interest to researchers, to graduate students and advanced undergraduate students in the PK/PD area who wish to learn how to analyze biological data and build models and to become familiar with new areas of application. In addition, the text will be of interest to toxicologists interested in learning about determinants of exposure and performing toxicokinetic modeling. The inclusion of the numerous exercises and models makes it an excellent primary or adjutant text for traditional PK courses taught in pharmacy and medical schools. A diskette is included with the text that includes all of the exercises and solutions using WinNonlin. |
| excel add ins for statistical analysis: Automated Data Analysis Using Excel Brian D. Bissett, 2020 This new edition includes some key topics relating to the latest version of MS Office, including use of the ribbon, current Excel file types, Dashboard, and basic Sharepoint integration. It shows how to automate operations, such as curve fitting, sorting, filtering, and analyzing data from a variety of sources. The book allows users to analyze data and automate the preparation of custom reports and demonstrates how to assign Excel VBA code to the new Ribbon user interface. |
| excel add ins for statistical analysis: Microsoft Business Intelligence Tools for Excel Analysts Michael Alexander, Jared Decker, Bernard Wehbe, 2014-05-05 Bridge the big data gap with Microsoft Business Intelligence Tools for Excel Analysts The distinction between departmental reporting done by business analysts with Excel and the enterprise reporting done by IT departments with SQL Server and SharePoint tools is more blurry now than ever before. With the introduction of robust new features like PowerPivot and Power View, it is essential for business analysts to get up to speed with big data tools that in the past have been reserved for IT professionals. Written by a team of Business Intelligence experts, Microsoft Business Intelligence Tools for Excel Analysts introduces business analysts to the rich toolset and reporting capabilities that can be leveraged to more effectively source and incorporate large datasets in their analytics while saving them time and simplifying the reporting process. Walks you step-by-step through important BI tools like PowerPivot, SQL Server, and SharePoint and shows you how to move data back and forth between these tools and Excel Shows you how to leverage relational databases, slice data into various views to gain different visibility perspectives, create eye-catching visualizations and dashboards, automate SQL Server data retrieval and integration, and publish dashboards and reports to the web Details how you can use SQL Server’s built-in functions to analyze large amounts of data, Excel pivot tables to access and report OLAP data, and PowerPivot to create powerful reporting mechanisms You’ll get on top of the Microsoft BI stack and all it can do to enhance Excel data analysis with this one-of-a-kind guide written for Excel analysts just like you. |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: 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 add ins for statistical analysis: 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 add ins for statistical analysis: Microsoft Excel 2013 Data Analysis and Business Modeling Wayne Winston, 2014-01-15 Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook. Solve real business problems with Excel—and sharpen your edge Summarize data with PivotTables and Descriptive Statistics Explore new trends in predictive and prescriptive analytics Use Excel Trend Curves, multiple regression, and exponential smoothing Master advanced Excel functions such as OFFSET and INDIRECT Delve into key financial, statistical, and time functions Make your charts more effective with the Power View tool Tame complex optimization problems with Excel Solver Run Monte Carlo simulations on stock prices and bidding models Apply important modeling tools such as the Inquire add-in |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: Learn Data Mining Through Excel Hong Zhou, 2020-06-13 Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help. Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages. This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data. What You Will Learn Comprehend data mining using a visual step-by-step approachBuild on a theoretical introduction of a data mining method, followed by an Excel implementationUnveil the mystery behind machine learning algorithms, making a complex topic accessible to everyoneBecome skilled in creative uses of Excel formulas and functionsObtain hands-on experience with data mining and Excel Who This Book Is For Anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended. |
| excel add ins for statistical analysis: Statistical Analysis Conrad Carlberg, 2011-04-22 Statistical Analysis: Microsoft Excel 2010 “Excel has become the standard platform for quantitative analysis. Carlberg has become a world-class guide for Excel users wanting to do quantitative analysis. The combination makes Statistical Analysis: Microsoft Excel 2010 a must-have addition to the library of those who want to get the job done and done right.” —Gene V Glass, Regents’ Professor Emeritus, Arizona State University Use Excel 2010’s statistical tools to transform your data into knowledge Use Excel 2010’s powerful statistical tools to gain a deeper understanding of your data, make more accurate and reliable inferences, and solve problems in fields ranging from business to health sciences. Top Excel guru Conrad Carlberg shows how to use Excel 2010 to perform the core statistical tasks every business professional, student, and researcher should master. Using real-world examples, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features, including its new consistency functions. Along the way, you discover the most effective ways to use correlation and regression and analysis of variance and covariance. You see how to use Excel to test statistical hypotheses using the normal, binomial, t and F distributions. Becoming an expert with Excel statistics has never been easier! You’ll find crystal-clear instructions, insider insights, and complete step-by-step projects—all complemented by an extensive set of web-based resources. • Master Excel’s most useful descriptive and inferential statistical tools • Tell the truth with statistics, and recognize when others don’t • Accurately summarize sets of values • View how values cluster and disperse • Infer a population’s characteristics from a sample’s frequency distribution • Explore correlation and regression to learn how variables move in tandem • Understand Excel’s new consistency functions • Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in • Use ANOVA and ANCOVA to test differences between more than two means • Explore statistical power by manipulating mean differences, standard errors, directionality, and alpha There is an Excel workbook for each chapter, and each worksheet is keyed to one of the book's figures. You'll also find additional material, such as a chart that demonstrates how statistical power shifts as you manipulate sample size, mean differences, alpha and directionality. To access these free files, please visit http://www.quepublishing.com/title/0789747200 and click the Downloads Tab. |
| excel add ins for statistical analysis: Advanced Analytics with Excel 2019 Manisha Nigam, 2020-06-19 Explore different ways and methods to consolidate data, complex analysis, and prediction or forecast based on trends Ê KEY FEATURESÊ _ Ê Ê Use the Analysis ToolPak to perform complex Data analysis _ Ê Ê Get well versed with the formulas, functions, and components in Excel _ Ê Ê Handy templates to give you a head start _ Ê Ê Usage of multiple examples to explain the application in a real-world scenario _ Ê Ê Implement macros for your everyday tasks that will help you save your time _ Ê Ê Explore different Charts types for Data visualization Ê Ê DESCRIPTION Book explains and simplify the usage of Excel features and functionalities, with the help of examples. It starts with ÔGetting Started with ExcelÕ and ÔPerforming functions with shortcut keysÕ which will help you in getting started with Excel. Then ÔFormulas and FunctionsÕ gives an initial understanding of what are operators, formulas, functions, their components. Further ÔData Visualization with new Charts typesÕ, ÔGantt and Milestone chartÕ, ÔSmartArt and Organization ChartÕ give details on the different chart types available in Excel. Ê In the intermediate section you will learn ÔGet creative with Icons, 3D models, Digital InkingÕ details multiple new and improved features that got introduced to enhance the visual presentation. In the end, Chapters ÔMail Merge using ExcelÕ, ÔCreate Custom Excel TemplateÕ and ÔMacros in ExcelÕ explain the Excel features that help in automating tasks. You will learn how to generate multiple documents automatically with customization, create and use your own templates and use of macros to do repeated task automatically. And at last Chapter ÔGet help for your problemÕ lists few problem statements and their probable solutions with references to the Excel feature or functionality that can be used to resolve the problem. Ê Ê Ê WHAT WILL YOU LEARN _ Ê Ê Get familiar with the most used advanced Excel formulas and functions for Data analysis _ Ê Ê Learn how to create a Gantt / Timeline / Milestone Chart in Excel _ Ê Ê Use charts for Better Data visualization _ Ê Ê Build organization charts with SmartArt tools in Excel _ Ê Ê Use the Analysis ToolPak & Power Pivots to perform complex Data analysis _ Ê Ê Learn how to link and share workbooks for automatic updates ÊÊ WHO THIS BOOK IS FOR This book is for professionals from any domain, who are searching for shortcuts & advanced methods to resolve their daily problems.Ê Ê Table of Contents 1.Ê Ê Ê Getting Started with Excel 2.Ê Ê Ê Perform Functions with Shortcut Keys 3.Ê Ê Ê Formulas and Functions 4.Ê Ê Ê Data Visualization with New Chart types 5.Ê Ê Ê Gantt and Milestone Chart 6.Ê Ê Ê SmartArt & Organization Chart 7.Ê Ê Get creative with Icons, 3D models, Digital Inking 8.Ê Ê Ê Putting Data in perspective with Pivots 9.Ê Ê Ê Complex Data Analysis using ToolPak 10.Ê Forecasting in Excel 11.Ê Mail Merge using Excel 12.Ê Create Custom Excel Template 13.Ê Macros in Excel 14.Ê Get help for your problem |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: Excel Data Analysis For Dummies Stephen L. Nelson, E. C. Nelson, 2015-11-30 Want to take the guesswork out of analyzing data? Let Excel do all the work for you! Data collection, management and analysis is the key to making effective business decisions, and if you are like most people, you probably don't take full advantage of Excel's data analysis tools. With Excel Data Analysis For Dummies, 3rd Edition, you'll learn how to leverage Microsoft Excel to take your data analysis to new heights by uncovering what is behind all of those mind-numbing numbers. The beauty of Excel lies in its functionality as a powerful data analysis tool. This easy-to-read guide will show you how to use Excel in conjunction with external databases, how to fully leverage PivotTables and PivotCharts, tips and tricks for using Excel's statistical and financial functions, how to visually present your data so it makes sense, and information about the fancier, more advanced tools for those who have mastered the basics! Once you're up to speed, you can stop worrying about how to make use of all that data you have on your hands and get down to the business of discovering meaningful, actionable insights for your business or organization. Excel is the most popular business intelligence tool in the world, and the newest update – Microsoft Excel 2016 – features even more powerful features for data analysis and visualization. Users can slice and dice their data and create visual presentations that turn otherwise indecipherable reports into easy-to-digest presentations that can quickly and effectively illustrate the key insights you are seeking. Fully updated to cover the latest updates and features of Excel 2016 Learn useful details about statistics, analysis, and visual presentations for your data Features coverage of database and statistics functions, descriptive statistics, inferential statistics, and optimization modeling with Solver Helps anyone who needs insight into how to get things done with data that is unwieldy and difficult to understand With Excel Data Analysis For Dummies, 3rd Edition, you'll soon be quickly and easily performing key analyses that can drive organizational decisions and create competitive advantages. |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: Introductory Econometrics Humberto Barreto, Frank Howland, 2006 This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics. |
| excel add ins for statistical analysis: Data Analysis with Microsoft Excel Kenneth N. Berk, 2006 |
| excel add ins for statistical analysis: Analyzing Data with Power BI and Power Pivot for Excel Alberto Ferrari, Marco Russo, 2017-04-28 Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness. How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one! By reading this book, you will: • Gain an understanding of the basics of data modeling, including tables, relationships, and keys • Familiarize yourself with star schemas, snowflakes, and common modeling techniques • Learn the importance of granularity • Discover how to use multiple fact tables, like sales and purchases, in a complex data model • Manage calendar-related calculations by using date tables • Track historical attributes, like previous addresses of customers or manager assignments • Use snapshots to compute quantity on hand • Work with multiple currencies in the most efficient way • Analyze events that have durations, including overlapping durations • Learn what data model you need to answer your specific business questions About This Book • For Excel and Power BI users who want to exploit the full power of their favorite tools • For BI professionals seeking new ideas for modeling data |
| excel add ins for statistical analysis: Excel 2016 For Dummies Greg Harvey, 2015-10-02 Excel 2016 For Dummies (9781119077015) is now being published as Excel 2016 For Dummies (9781119293439). While this version features an older Dummies cover and design, the content is the same as the new release and should not be considered a different product. Let your Excel skills sore to new heights with this bestselling guide Updated to reflect the latest changes to the Microsoft Office suite, this new edition of Excel For Dummies quickly and painlessly gets you up to speed on mastering the world's most widely used spreadsheet tool. Written by bestselling author Greg Harvey, it has been completely revised and updated to offer you the freshest and most current information to make using the latest version of Excel easy and stress-free. If the thought of looking at spreadsheet makes your head swell, you've come to the right place. Whether you've used older versions of this popular program or have never gotten a headache from looking at all those grids, this hands-on guide will get you up and running with the latest installment of the software, Microsoft Excel 2016. In no time, you'll begin creating and editing worksheets, formatting cells, entering formulas, creating and editing charts, inserting graphs, designing database forms, and more. Plus, you'll get easy-to-follow guidance on mastering more advanced skills, like adding hyperlinks to worksheets, saving worksheets as web pages, adding worksheet data to an existing web page, and so much more. Save spreadsheets in the Cloud to work on them anywhere Use Excel 2016 on a desktop, laptop, or tablet Share spreadsheets via email, online meetings, and social media sites Analyze data with PivotTables If you're new to Excel and want to spend more time on your actual work than figuring out how to make it work for you, this new edition of Excel 2016 For Dummies sets you up for success. |
| excel add ins for statistical analysis: Statistics Using Excel Succinctly Charles Zaiontz, 2017-02-01 Learn the ins and outs of Microsoft Excel's statistical capabilities. Author Charles Zaiontz will help you familiarize yourself with an often overlooked but very powerful set of tools. With Statistics Using Excel Succinctly, you will be able to maximize your Excel skills. |
| excel add ins for statistical analysis: 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 add ins for statistical analysis: Modern Data Analytics in Excel George Mount, 2024-04-26 If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains. And if you're looking to conduct rigorous data analysis, more can be done in Excel than you think. This practical book serves as an introduction to the modern Excel suite of features along with other powerful tools for analytics. George Mount of Stringfest Analytics shows business analysts, data analysts, and business intelligence specialists how to make bigger gains right from your spreadsheets by using Excel's latest features. You'll learn how to build repeatable data cleaning workflows with Power Query, and design relational data models straight from your workbook with Power Pivot. You'll also explore other exciting new features for analytics, such as dynamic array functions, AI-powered insights, and Python integration. Learn how to build reports and analyses that were previously difficult or impossible to do in Excel. This book shows you how to: Build repeatable data cleaning processes for Excel with Power Query Create relational data models and analysis measures with Power Pivot Pull data quickly with dynamic arrays Use AI to uncover patterns and trends from inside Excel Integrate Python functionality with Excel for automated analysis and reporting |
| excel add ins for statistical analysis: SAP Analysis for Microsoft Office--Practical Guide Denis Reis, 2021-01-26 Managing your SAP data in Microsoft Excel? This is your guide to using SAP Analysis for Microsoft Office! Get started with the basics, from creating your first workbook to navigating through reports. Then, follow step-by-step instructions to process data, analyze data, develop planning applications, customize reports, and work with tools such as formulas and macros. Including details on troubleshooting, UI customization, and more, this book is your all-in-one resource! In this book, you'll learn about: a. Reporting and Data Analysis Learn to work with reports in SAP Analysis for Microsoft Office: define parameters with prompts, adjust formatting and styles, and extend reports with local data. Filter, sort, and display your data using hierarchies, and refine data analysis with simple and advanced calculations. b. Planning Use your SAP data to develop planning workbooks. Plan your data both manually and with functions and sequences. Understand key settings for cell locking, the planning model, and more. c. Advanced Features Take your skills to the next level. Write formulas to use in your reports, and create and use macros in your workbooks, including steps to use API methods, callbacks, and design rules. Highlights include: 1) Workbook creation 2) Report navigation 3) Prompts 4) Data processing, organization, and analysis 5) Planning applications 6) Report customization and formatting 7) Formulas 8) Macros 9) Configuration 10) Troubleshooting |
| excel add ins for statistical analysis: Using Statistics for Better Business Decisions Justin Bateh, Bert G. Wachsmuth, 2015-12-16 More and more organizations around the globe are expecting that professionals will make data-driven decisions. Employees, team leaders, managers, and executives that can think quantitatively should be in high demand. The goal of this book is to increase ability to identify a problem, collect data, organize, and analyze data that will help aid in making more effective decisions. This book will provide you with a solid foundation for thinking quantitatively within your company. To help facilitate this objective, this book follows two fictitious companies that encounter a series of business problems, while demonstrating how managers would use the concepts in the book to solve these problems and determine the next course of action. This book is for beginners and does not require prior statistical training. All computations will be completed using Microsoft Excel. |
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 …
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 …
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 …
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 …
How to keep one variable constant with other one changing with row …
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: …
