Students’ informal statistical inferences through data modeling with a large multivariate dataset

Abstract

In today’s age of information, the use of data is very powerful in making informed decisions. Data analytics is a field that is interested in identifying and interpreting trends and patterns within big data to make data-driven decisions. We focus on informal statistical inference and data modeling as a means of developing students’ data analytics skills in school. In this study, we examine how students apply the data modeling process to draw informal inferences when exploring trends, patterns and relationships in a real dataset using technological tools, such as CODAP and Excel. We analyzed 17–18-year-old students’ written reports on their explorations of data supplied by third parties. Students used a variety of statistical measures and visualizations to account for variability in analyzing data. They tended to make statements with certainty in their inferences and predictions beyond the data. When the pattern in the data was uncertain, they were inclined to use contextual knowledge to remain certain in their claims.