As long as you have a paid version of Excel 2010 or greater for either Windows or Mac installed on your machine, you should be able to follow along with the majority of the instruction in this book, with some variations, particularly with PivotTables and data visualization. To meet the book’s objectives, I make some technical and technological assumptions: Technical RequirementsĪdvancing into Analytics was written on a Windows computer with the Office 365 version of Excel for desktop. Few books cover this combination, even though the progression from spreadsheets into programming is common for analysts, myself included. We’ll be using Excel, R, and Python because these are powerful tools, and because they make for a seamless learning journey. With the tools and frameworks you’ll pick up in this book, you will be well positioned to continue learning more advanced data analysis techniques. Exploring and testing relationships is core to analytics. To that end, I include a learning objective in the preface of Advancing into Analytics.īy the end of this book, you should be able to conduct exploratory data analysis and hypothesis testing using a programming language.
#Xlminer analysis toolpak. code#
This book demonstrates key statistical concepts from spreadsheets and pivots your existing knowledge about data manipulation into R and Python programming. Advancing into Analytics will lower your learning curve.Īuthor George Mount, founder and CEO of Stringfest Analytics, clearly and gently guides intermediate Excel users to a solid understanding of analytics and the data stack. Data analytics may seem daunting, but if you’re familiar with Excel, you have a head start that can help you make the leap into analytics.
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