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Elementary Statistical Methods

In this introductory statistics course, high school students have the opportunity to develop the quantitative reasoning skills and habits of mind necessary to use data science and mathematical thinking effectively across multiple disciplines. This course will hone relevant mathematical and critical thinking skills through scaffolded learning experiences and statistical methodologies. Students will learn the foundations of data science by engaging in hands-on analysis of real data, methods to extract key insights, and coding skills aligned to the expectations of higher education and today’s workplace.

Students will experience interactive applications built into the high-quality curriculum designed by the faculty at the University of Texas at Austin (UT Austin), allowing them to discover a more intuitive understanding of concepts. Collaborative problem-solving will be used to strengthen mathematical connections while individual depth of understanding will be reflected in regular assessments. Students can earn three hours of UT Austin credit with feedback and assessment provided by UT Austin course staff.



Discussions on experimental design help students understand how data is collected. Data analysis begins with determining the type of variables contained in the data, then describing and visualizing them in an appropriate way.


Decisions about populations are made by assessing sample data. First, a question is asked, then data is collected, and finally, the data is used to infer something about the population.


Summarizing data, creating graphical displays, and analyzing dependence and correspondence help students develop an understanding of how two variables are associated with one another. With this information, students can better understand models that are used to predict outcomes and be informed about the accuracy of analyses.

  • TCCN: MATH 1342
  • UT Course Code: SDS 301
    • 3 College Credits

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