On this page you will learn more about using my book Advancing into Analytics: From Excel to Python and R in an academic setting. If your class is looking to dive from spreadsheets into statistics and data analytics using R and Python, this is the book for you.
Download a PDF brochure of this content here:
An overview of the book along with some resources follows.
Accessing the book
You can preview the book using this link from O’Reilly Media for a free trial subscription. Be sure to check if your institution’s library has a subscription to O’Reilly Online Learning; if they do, everyone can read for free.
You can also contact me at the form below if you would like a desk copy.
Should you choose to use the book in your course, be sure to get in touch so O’Reilly can provide the title at 40% off to students.
Description
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. Advancing into Analytics will lower your learning curve.
Author 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. This book demonstrates key statistical concepts from spreadsheets and pivots your existing knowledge about data manipulation into R and Python programming.
With this practical book at your side, you’ll learn how to:
- Explore a dataset for potential research questions to check assumptions and to build hypotheses
- Make compelling business recommendations using inferential statistics
- Load, view, and write datasets using R and Python
- Perform common data wrangling tasks such as sorting, filtering, and aggregating using R and Python
- Navigate and execute code in Jupyter notebooks
- Identify, install, and implement the most useful open source packages for your needs
- And more
Table of contents
I. Foundations of Analytics in Excel
1. Foundations of Exploratory Data Analysis
2. Foundations of Probability
3. Foundations of Inferential Statistics
4. Correlation and Regression
5. The Data Analytics Stack
II. From Excel to R
6. First Steps with R for Excel Users
7. Data Structures in R
8. Data Manipulation and Visualization in R
9. Capstone: R for Data Analytics
III. From Excel to Python
10. First Steps with Python for Excel Users
11. Data Structures in Python
12. Data Manipulation and Visualization in Python
13. Capstone: Python for Data Analytics
14. Conclusion and Next Steps
Companion repo
The companion repository for the book is publicly available on GitHub. This contains all datasets, workbooks, scripts, exercise solutions, and other files used in the book.
You can download a compressed folder of the files or, if you are familiar with GitHub, clone it to your computer.
Instructor’s practice bank
The exercises and solutions from the end-of-chapter exercises are publicly available in the repo. If you would like similar exercises for your class without giving away the solutions, check out this repo.
Contact me to get access to a private repo containing solutions to these exercises.
Presentations
Advancing into Analytics was launched during the coronavirus pandemic, so all presentations have thus far been virtual. That’s not all bad, as with the assistance of technology I’ve been able to present to meetups across the world. Some highlights:
London Excel Meetup (London, UK)
Microsoft Excel and Data Analysis Learning Community (Lagos, Nigeria)
Financial Modelling in Excel Meetup (Sydney, Australia)
Guest lectures
Speaking with groups near and far is possibly the best part about writing a book. If you are interested in having me guest lecture for your class, please connect below.
What people are saying
Our world is awash in data. It is not awash in knowledge. Understanding of statistics and of how to develop knowledge from data are fundamental for anyone who is truly educated: what can one justifiably conclude from observations, and what are the limits of what one can learn? George Mount’s approach gives both the theoretical understanding needed, and the practical tools and steps to put it to work. Advancing into Analytics is appropriate for the beginner, but rigorous and serious enough to hold the interest of those of us with substantial experience. Highly recommended.”
CHARLES N. STEELE, PHD, CHAIRMAN, DEPARTMENT OF ECONOMICS, BUSINESS AND ACCOUNTING, HILLSDALE COLLEGE
Read for free
Use this link to read my book with a 30-day FREE membership to O’Reilly Online Learning. I can also get you a desk copy for your review.
Promo code
If you decide to use the book in your course, O’Reilly can set up a custom promo code for students to purchase the title at 40% off on the Google Play store.
Get started
If you’re interested in using the book in your course having me present to your class, or something else, drop me a line below or schedule a call on Microsoft Bookings. I look forward to becoming savvier about data with you and your students.
