Data analytics may seem daunting, but if you’re an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you’ll be able to conduct exploratory data analysis and hypothesis testing using a programming language.
Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you’ll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming.
This practical book guides you through:
- Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics
- From Excel to R: Cleanly transfer what you’ve learned about working with data from Excel to R
- From Excel to Python: Learn how to pivot your Excel data chops into Python and conduct a complete data analysis
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