Program Overview
Program Type
Minor
Credit Hours
15
The minor in Statistics and Data Science gives students experience manipulating, summarizing, and visualizing data and applying statistical and machine learning methods. Students are exposed to the principles of and tools for conducting reproducible data analysis and are taught to think critically about relevant ethical issues (e.g., data privacy, misrepresentation of findings). The program bolsters students' training in statistics and data science to enhance their preparation in their major field as well as strengthen their position to enter the workforce or graduate school.
SDS majors are not eligible to receive credit for the minor. However, students who drop the major may be able to count certain courses toward the minor (see below).
The SDS minor will open in Fall 2024. More information on how to enroll coming soon.
Prerequisites
The SDS minor is open to all UT undergraduate students. To be successful in the minor, students should have sufficient background in mathematics such that they could succeed in a college-level calculus course. For example, they should have earned an appropriate score on the Mathematics placement exam to place into calculus, or completed Mathematics 305G with a grade of at least B-, or a mathematics exam (e.g., AP, CLEP) credit accepted by UT Austin, or a course transfer credit accepted by UT Austin for a calculus course or Math 305G equivalent. While calculus is not a prerequisite for the minor, it may be required for some of the elective courses.
Requirements
The minor requires 15 semester hours of coursework with a grade of at least a C- in each course.
No credit-by-exam may be used to fulfill minor course requirements. The following courses are required:
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1
Three core courses in each of the following areas (9 credit hours total):
Statistics
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SDS 320E Elements of Statistics
Students may replace this requirement with SDS 320H or SDS 315*; but not AP statistics, SDS 302, or SDS 301
Data Science
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SDS 322E Elements of Data Science
Students may replace this requirement with SDS 313*
Programming
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C S 303E Elements of Computers and Programming
Students may replace this requirement with CS 312 or CS 312H
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-
2
Two additional elective courses. One each from any two of the following areas (6 credit hours total):
Regression/Statistical Modeling
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SDS 324E Elements of Regression Analysis
Students may replace this course with SDS 334*
Machine Learning
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SDS 326E** Elements of Statistical Machine Learning
Students may replace this course with SDS 336*
Databases
- C S 327E Elements of Databases
Probability/Mathematical Statistics/Statistical Inference
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SDS 321 Introduction to Probability and Statistics
Students may replace this course with SDS 431*, M 362K or M 378K
Data Visualization
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SDS 366*** Data Visualization in R
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* Required course for the SDS major, not open for non-majors
** SDS 326E has previously been offered as SDS 323. Credit for SDS 323 can replace SDS 326E as a minor elective.
*** SDS 366 has previously been offered as SDS 375 (Topic: Data Visualization in R). Credit for SDS 375 (Topic: Data Visualization in R) can replace SDS 366 as a minor elective.