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.