New Course! Introduction to Data Science, STAT/DATA:1015


Dr. Haley Jeppson will join the department as a Visiting Assistant Professor in the Fall 2023 and will be the instructor of Introduction to Data Science.

Dr. Jeppson received her PhD from Iowa State University in 2021. She was a research associate at the National Institute of Statistical Sciences for the past two years. Her research interests include statistical computing, statistics education and visualization. 

We just recently opened this class and this course does full fill the General Educational Requirement for Quantitative or Formal Reasoning .  It is offered on Monday, Wednesday, and Friday at 2:30-3:20 in 15 Schaeffer Hall. 

In today's world, massive amounts of data are increasingly collected and leveraged for knowledge discovery, policy assessment, and decision-making across many fields, including business, natural sciences, social sciences, and humanities. For example, by digitizing and analyzing vast collections of written records, we can uncover valuable insights into societal changes and even discover more about authorship.

The main goal of this course is to empower students with essential data literacy skills, a crucial component of general education. Students will develop a strong foundation in exploring, interpreting, and visualizing data, as well as effectively communicating their findings through reports. By focusing on quantitative and formal reasoning, this course is particularly advantageous for students in humanities and social sciences.

The course will cover the following topics:

1. Data collection, visualization, and data wrangling.

2. Basics of probability and statistical inference.

3. Fundamentals of data learning, including regression, classification, prediction, and cross-validation.

4. Computing, learning, and reporting in the R environment.

5. Literate programming and reproducible research.

By the end of this course, students will learn the fundamentals of exploring the world of data, making informed decisions, and contributing meaningfully to their respective fields.