The WSU Data Science and Computational Statistics Certificate of Proficiency will provide students the opportunity to study a variety of applications of data using statistics across a range of disciplines while providing a theoretical framework and tools for managing data. The rapidly evolving digital landscape has made data the cornerstone of decision-making across industries, amplifying the demand for skilled data professionals who can adeptly handle, analyze, and interpret this data. This program is tailored to equip students with these very competencies. The program is designed to be a comprehensive blend of both theory and practice, with a focus on hands-on experience, collaborative learning, and ethical data usage. More broadly this will empower students to think critically with data while analyzing the world around them in their chosen discipline.
- Program Prerequisite: Application for admission to Weber State University and/or current degree-seeking status.
- Grade Requirements: Students must complete all certificate courses with a grade of “C” or higher.
- Credit Hour Requirements: 19-21
- Program Code: 6071CP
- CIPC: 307099
Advisement
Navigating the multidisciplinary landscape of Data Science and Applied Statistics requires a robust support system. Our advisement for this certificate program is carefully crafted to cater to this emerging field. Recognizing the interdisciplinary nature of Data Science and the specialized nuances of Applied Statistics, our advisement team provides tailored guidance. Students will receive one-on-one consultations to help them align their coursework with career aspirations or advanced study intentions. Please contact math@weber.edu to schedule advising appointment or visit the mathematics website.
Program Learning Outcomes
The program aims to roughly follow the guidelines put forth by the American Statistical Association (ASA) for data science. Additionally, the ASA states that, “Framing questions statistically allows us to leverage data resources to extract knowledge and obtain better answers.” The learning outcomes based on these recommendations are as follows:
- Students will apply data analysis methods and critical thinking to understand data in the world around them or their fields of study.
- Students will use data management and statistical software to prepare data and perform data analysis.
- Students will learn mathematical and statistical foundations of data science and data analysis.
Students will effectively communicate the findings from data.
