As of July 1, 2024 the Center for Student Analytics has merged into the Office of Data and Analytics.
Degrees and Certificates Awarded
First-Time, Full-Time Retention Rate
Depending on the project or activity, our work is directed on the following types of data analytics and BIG questions.
Descriptive (What Happened?)This is where data is collected and presented in a summarized format (that’s the aggregation part) and is “mined” to discover patterns. The data is then presented in a way that can be easily understood by a wide audience (not just data experts).
Predictive (What is likely to happen?)Predictive analytics estimates the likelihood of a future outcome based on historical data and probability theory, and while it can never to completely accurate, it does eliminate much of the guesswork from key decisions.
Diagnostic (Why did it happen?) For this type of analysis, several techniques are utilized: probability theory, regression analysis, filtering, and time - series data analytics. Anomalies are identified and causal relationships are explored.
This type analysis considers a range of possible scenarios and assesses different actions that could be applied. Thease analytics is more complex and may involve working with algorithms, machine learning, and computational modeling procedures.
In 2024 USU created a new Office of Data and Analytics which merged the former Center for Student Analytics with the Office of Analysis, Assessment, and Accreditation.
An archive of previous work of the Center for Student Analytics is available on USU Digital Commons.
Utah State University VALUES PRIVACY and remains trustworthy by working with institutional data in an intentional and secure way. As part of these efforts, USU has a transparent privacy policy regarding the ethical use of data collected from the USU community, including procedures that prevent the unauthorized access or disclosure of private data.
The value of data is increased by its widespread and appropriate use. Institutional data officers use a transparent, collaborative approach to safeguard data against being used inappropriately. The controls and procedures utilized by the Office of Data and Analytics align with federal and state laws regarding the protection of privacy and also adhere to the highest standards of student data ethics.
