Preface
You’re about to partake in a significant and commendable learning journey that will involve statistics, coding, and more. Before diving in, I’d like to take some time to address my learning objectives for you, how I arrived at this book, and what you should expect.
Learning Objective
By the end of this book, you should be able to conduct exploratory data analysis and hypothesis testing using a programming language. Exploring and testing relationships is core to analytics. 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.
We’ll be using Excel, R, and Python because these are powerful tools, and because they make for a seamless learning journey. Few books cover this combination, even though the progression from spreadsheets into programming is common for analysts, myself included.
Prerequisites
To meet these objectives, this book makes some technical and technological assumptions.
Technical Requirements
I am writing this book on a Windows computer with the Office 365 version of Excel for desktop. 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.
Note
While Excel offers both free and paid versions online, a paid desktop version is needed to access some ...
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