3. Data Analysis Principles

Trait #3 – Data Analysis Principles

How to Score Yourself

As you fill out your self-assessment worksheet or dashboard, take into account the following statements to more accurately gauge your own level of proficiency in this trait, as well as its importance to your success in the near future:

Proficiency

Rate yourself high in proficiency in this critical trait in the Knowledge category if you can say yes to all or most of the following statements:

Importance

Rate the importance of this trait highly if you can say yes to most of the following statements

Resources to Help You Improve

The following resources will help you increase your proficiency in this third of the 17 Key Traits of Data Literacy:

• Videos
  • MIT OpenCourseWare: 1. Introduction to Statistics
  • MIT Center for Brains, Mind + Machines: Tutorial: Statistics and Data Analysis
• Courses
  • Data Literacy Fundamentals: Understanding the Power & Value of Data
  • MIT OpenCourseWare: Statistics for Applications
• Books
  • Data Literacy Fundamentals (Ben Jones, 2020)
  • Naked Statistics: Stripping the Dread from the Data (Charles Wheelan, 2014)
  • The Art of Statistics: How to Learn from Data (David Spiegelhalter, 2021)
• Papers
  • ‘Elements and Principles of Data Analysis,’ (Stephanie C. Hicks & Roger Peng (March 2019)
• Websites
  • Harvard Business Review: 5 Essential Principles for Understanding Analytics (Thomas Davenport)