Get Your Bearings with Data Literacy


Data literacy is the ability to read, understand, create, and communicate data as information. This ability is essential to become a critical consumer of data, and a basic skills for many jobs on the current market. This course introduces data management and interpretation in an accessible manner, using simple examples from everyday life. The content and teaching style are geared toward novice data users, including people who self-identify as being “afraid of numbers.” In a dynamic and autonomy-supportive learning context, we will develop critical thinking skills related to data literacy, learn how to produce and visualize basic statistics, and discuss best practices in reporting data. Using accessible and simple statistical software (e.g., StatsCloud), we will also explore the fundamentals of descriptive statistical methods (frequency distributions, measures of central tendency, measures of association, etc.) and briefly introduce inferential statistics (hypothesis testing, sampling distributions, analyzing variance, etc.) in an applied context.


Topic Relevance

Whether it is a tweet, a like, an online purchase, results from a poll, a YouTube video, a text message, or a song being streamed, billions of data points are being generated online every minute of every day. The ability to manage, interpret, and communicate results from this data is a critical skill in our everyday and professional lives.

The Data Literacy Laboratory was founded in 2020 by a group of researchers who love quantitative methods and are passionate about teaching it in accessible and non-threatening ways to others. We strive to create a learning environment that promotes data literacy outcomes for learners, providing them with the tools and confidence they need to successfully interpret, interact, and share data in their careers and everyday lives.


Learning Outcomes

  • Understand the basic principles governing quantitative analysis
  • Chose the right statistical tool for a given problem
  • Use software to carry out basic tasks related to data management and analysis
  • Develop an appropriate interpretation following a quantitative analysis
  • Critically evaluate visual representations of data in the media



  • This course is appropriate for anyone interested in getting more familiar with working in a data rich environment. We welcome participants from all backgrounds, regardless of experience. The course is tailored for the uninitiated data user who might feel anxiety at the thought of having to deal with numbers.



12 hours


  • $1095 (plus tax)


Featured Instructors

Dr. Meredith Rocchi is an award-winning quantitative methods professor with expertise in effective interpersonal communication, measurement validation, and data literacy education. She is committed to teaching excellence through reducing the stigma surrounding methods courses, making quantitative methods education more accessible, and helping alleviate students’ anxiety towards math and numbers. As an assistant professor in the Department of Communication at uOttawa, Meredith is overseeing a large multi-year project (The Data Literacy Project) aimed at improving quantitative methods courses for students in the humanities and social sciences.

Dr. Simon Beaudry is an award-winning quantitative methods professor and the 2021 Chair in University Teaching at uOttawa. His teaching practices are centred on providing students with the relational support they need to develop autonomy and confidence to succeed. As Manager of Research Infrastructure at the School of Psychology, Simon is responsible for overseeing cutting-edge social science research and providing instrumental support to faculty. He has over a decade of teaching experience across disciplines. His expertise lies in pedagogy, methodology, data analysis, and infrastructure management.