AT Math: Data Analytics and Visualization

The future of technology belongs to data analysts and that could be you! In this course, you will learn statistical programming and coding, how to critically think about the data you see in the news, and how to create your own story about data.

What are the major projects you will complete in this course?

Semester 2 Student Driven Study: students will conduct their own quantitative study and present their research question, methods, findings, and implications in front of a panel of experts. The panel will ask students to defend their thesis question, methods, processes, conclusions, and recommendations, including their Quantitative methods analysis, such as Analysis of Variance, Chi-Square testing, etc. 

This course is offered by the Quest program in SAS.

Students are able to receive credit through the Quest program. For more information on Quest, please click here.

Course Details

Darlene Poluan

"You should take this course if you are interested in learning how to critically think about data and how to use a programming language to help analyze data and make informed decision. "

AT Math: Data Analytics and Visualization

ID: 48528 Grade: 11-12 Length: Year
Credit: Math
Prerequisite: Completion of Algebra 2/Trig or higher level math course with Semester I grade of B or higher; or recommendation of Quest advisor.
Note: The Advanced Topic (AT) designation indicates a course is at university level, putting it at or above the level of a traditional Advanced Placement (AP) course. This course has a grade point weighting of 0.5.

In order to receive credit in Math: Data Analytics, students are required to demonstrate their learning in interpreting categorical and quantitative data, making inferences and justifying conclusions and using probability to make decisions. Students do not need to dwell on the details of computation - the main focus is on understanding a few deep concepts and interpreting data and the results of statistical analysis. Students are required to collect, organize, represent, and analyze data through the use of statistical software or programming language.

Students who wish to earn Advanced Topic credit will individually be held to a higher standard of skill acquisition and will need to demonstrate a high level of data processing and analyzing skills. Students are required to collect, organize, represent, and analyze their own data through the use of statistical software or programming language. Students will also be defining their learning objectives and how they personally go beyond the requirements.

What Our Students Say


The AT Data Analytics course is the perfect introduction to a critical field of work. Data can be analyzed to help make decisions and to predict future trends, which is more important than ever in our fast-paced world.”

Jennifer Han,
Class of 2019

Results that Matter


Advanced Placement (AP) courses and exams


of 3's, 4's, and 5's received in AP exams in 2018


Advanced Topics (AT) courses


of the Class of 2018 graduates were awarded cum laude commendations

What Our Alumni Say


Taking AT Data Analytics was one of the best decisions I made in high school. Currently, I am starting research with a professor partly due to the experiences I had in AT Data Analytics. This course forces you to take responsibility for your learning which is a skill that many do not learn until later in college.

Jacqueline Routhier, Class of 2017