The efficacy of teaching statistics and data science with real, diverse and relatable datasets

Prince Afriyie Speaker
University of Virginia
 
Monday, Aug 7: 11:35 AM - 11:55 AM
Invited Paper Session 
Metro Toronto Convention Centre 
A fundamental quest of statistics and data science is drawing robust conclusions about our world with incomplete data. This makes statistics and data science unique and applicable in almost every field of work or study. Teaching statistics and data science with real, diverse and relatable data reinforces the practicality and applicability of statistics. In fact, teaching statistics with real data with context and purpose (2016 GAISE report) is an effective teaching technique because data drives the motivation behind most statistical concepts. This technique enhances students' conceptual understanding of topics and helps them perceive the relevance of statistics and data science. As a consequence, we can capture students' attention and pique their interest in statistics and data science.
In this presentation, we will share examples of how to find, collect, or scrape real, diverse and relatable datasets to use in the introduction of fundamental topics in statistics and data science. Some of the real data used in this presentation are also relatable to students as they touch on issues relating to justice, equity, diversity, and inclusion. We will approach statistics and data science