Statistical Inference and Hypothesis Testing in Data Science Applications

The University of Colorado Boulder, founded in 1876 and set against the Rocky Mountains, is a major research university serving more than 37,000 students with nearly 3,000 international learners. CU Boulder is recognized for academic excellence, expansive research programs and a sustainability-driven campus culture. Students benefit from an array of undergraduate, graduate and professional offerings that encourage innovation across science, engineering, business, arts and humanities.

Research, entrepreneurship and experiential learning are central to the CU Boulder experience, with extensive laboratory facilities, innovation labs and co-op or internship pathways that connect students to industry and civic partners. The university supports cross-disciplinary projects and provides robust advising, career services and student organizations that help translate academic interests into practical outcomes and start-up ventures.

Boulder's outdoor lifestyle and proximity to tech hubs create strong opportunities for networking, recreation and balanced living. International students are supported by dedicated offices for admissions, orientation and visa guidance, making the transition smoother. With a large program portfolio and a campus culture that values sustainability, creativity and collaboration, CU Boulder is well suited to students seeking high-impact research experiences and an active campus community.

This Non-degree program in Statistical Inference and Hypothesis Testing in Data Science Applications is for students who want to learn how to make informed decisions from data. It is taught in English and offered by the University of Colorado Boulder. The program helps students understand the logic of hypothesis testing and how to use it in data science applications.

The curriculum covers hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Students will learn to use hypothesis tests to make informed decisions from data and understand the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.

After completing this program, students can pursue careers as Data Scientists, Statistical Analysts, Data Analysts, Business Intelligence Developers, or Quantitative Analysts. They can work in various industries, including healthcare, finance, and technology, and can be employed by companies such as Google, Amazon, or IBM.