Quantitative Understanding and Empirical Scientific Thinking (QUEST) is a group of four courses: Quantitative Reasoning, Scientific Inquiry, Programming for Data Science and Visualization, and Introduction to Statistics. Students are required to take only one course from this group.
Quantitative Reasoning For A Digital Age
Digital technology transforms how we live: from how we travel, to what we use for money, to how we swipe to find love. At the heart of these social, cultural, and economic changes lie mathematics and computer science. But how do we gather the information, interpret the data, and construct the algorithms that drive these advances and affect our lives?
Quantitative Reasoning in a Digital Age not only develops foundational skills in mathematics and computer science, but demonstrates how computer programming and algorithmic thinking inform issues in fields as diverse as economics, psychology, history, and philosophy. Structured around project-based teamwork, you’ll examine how the toolkit of computational thinking can model human behavior and address real-world problems in business, education, public health, government, and other sectors.
By understanding how quantitative reasoning affects modern society and modern society often affects our quantitative reasoning, you’ll learn to question your own assumptions about data big and small and think critically about the abundance of quantitative information that defines the decisions we make.
Scientific Inquiry
From the smallest atom to the most distant star, what do we know about our universe, and how do we know it? Scientific Inquiry unlocks the door to discovery and explores how humans acquired our fundamental knowledge of the sciences.
This course introduces you to the scientific method through engagement with groundbreaking experiments from the likes of Galileo, Newton, and Pavlov and provides hands-on experience with projects that reflect everyday, real-world problems relevant to fields such as biology, chemistry, physics, earth science, and neuroscience.
Through this project and inquiry-based approach to answering scientific questions across the various disciplines of the natural sciences, we will understand how to make, interpret, and challenge scientific claims rigorously and responsibly. Creating connections across the Fulbright core curriculum, this course emphasizes how scientific inquiry informs public debates past and present, challenging you not only to understand the world from a scientific perspective, but also to understand how our scientific perspective is shaped and informed by the world.
Programming for Data Science and Visualization
The Programming for Data Science and Visualization course isn’t just about turning numbers into charts; it’s your key to unlocking the transformative power of data. This course transcends your major, equipping you with the skills of a data analyst. Imagine crafting informative visualizations that bring data to life, revealing hidden patterns and trends. The course delves into data visualization, fostering a critical approach to how data is generated, analyzed, and used. By mastering key concepts and techniques, you’ll be able to create compelling data stories that not only expose hidden insights but also inform effective data-driven decisions. The exploration goes beyond the visual. With Python’s extensive libraries, you can extract valuable insights and make informed decisions in any field. To further elevate your understanding, the course provides a glimpse into the fascinating world of machine learning algorithms – the cornerstone of data science and artificial intelligence. This introduction equips you to explore these dynamic fields and harness their power to tackle real-world challenges with innovative solutions. This course isn’t just about data; it’s your passport to a future powered by insights. Unlock the secrets hidden within information and become a leader in the data-driven revolution.
Introduction to Statistics
How do we know which Covid-19 vaccine is the best? Which combination of social policies could help promoting start-up companies? These questions could be answered with the help of Data analysis. Social scientists need to process survey results. Natural scientists want to analyze experiment’s outcomes. Modern statistical methods and state of the art computing software can help finding valuable information from a large and confusing data set. This course will provide students with basic statistics concepts and methods, as well as practical coding skill in modern programming languagues. Students will be able to describe and find characteristic of the data, explore, and confirm relationship among data, and draw answer for questions from their own discipline via hand-on experience with various projects. Some main topics are data visualization, descriptive statistics, parameter estimation, hypothesis testing, ANOVA.
