Data Science

Data Science Foundations (DSF) will introduce you to the exciting opportunities available at the intersection of data analysis, computing, and mathematics through hands-on activities. Data are everywhere, and this class will prepare you to live in a world of data. The class focuses on practical applications of data analysis to develop concrete and applicable skills. Instead of using small, tailored, curated data sets we will engage with a wider world of data that fall into the "Big Data" paradigm and are relevant to our lives. In DSF, statistical inference is taught algorithmically, using modern randomization and simulation techniques. You will find and communicate meaning in data, and to think critically about arguments based on data.

Data science is a blend of quantitative reasoning, statistics, and computer science to gain meaningful insights from data. The difference between data science and statistics is that where statistics focuses on explaining the data, data science focuses on using data to make predictions and decisions. Students will reason with and think critically about data in all forms. They will develop their understanding of data analysis, sampling, correlation/causation, bias and uncertainty, probability, modeling with data, making and evaluating data-based arguments, the power of data in society, and more. Students will learn how to code using R, a programming language for statistical computing and graphics.

The course teaches students to reason with and think critically about data in all forms. Ohio’s Learning Standards for Mathematics relevant to data science are taught along with the data demands of good citizenship in the 21st century. It includes things such as describing big data; usability and usefulness of data; structured vs unstructured data; data extraction techniques; data storage; privacy issues; and data mining.