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
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
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:
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: