Beginning fall 2021, four SDS course names are changing! See below for more details about each course.

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**SDS 302 and SDS 306 are now SDS 302F, Foundations of Data Analysis!**

SDS 302F Foundations of Data Analysis (replacing SDS 302 Data Analysis for the Health Sciences) Introduction to data analysis and statistical methods. Topics may include: random sampling; principles of observational study and experimental design; data summaries and graphics; and statistical models and inference, including the simple linear regression model and one-way analysis of variance.

Credit for SDS 302F may not be earned after a student has received credit for SDS 320E, 322E (or SDS 328M or 332). Only one of the following may be counted: Statistics and Data Sciences 302, 306, 302F.

Flags: Ethics, Quantitative Reasoning

Core: Math

**SDS 328M is now SDS 320E, Elements of Statistics!**

SDS 320E Elements of Statistics (replacing SDS 328M Biostatistics) Introduction to statistics. Topics may include: probability; principles of observational study and experimental design; statistical models and inference, including the multiple linear regression model and one-way analysis of variance. R programming is introduced.

Only one of the following may be counted: Statistics and Data Sciences 320E and 328M.

Flags: Ethics, Quantitative Reasoning, Independent Inquiry

Core: Math

** **

**SDS 348 is now SDS 322E, Elements of Data Science!**

SDS 322E Elements of Data Science (replacing SDS 348 Computational Biology & Bioinformatics) Introduction to data science. Topics may include: data wrangling; exploratory data analysis, including data visualization; markdown and data workflow; simulation-based inference; and classification methods. R programming is emphasized and Python programming is introduced.

Prerequisite: Credit for an introductory statistics course.

Only one of the following may be counted: Statistics and Data Sciences 322E and 348.

**SDS 332 is now SDS 324E, Elements of Regression Analysis!**

SDS 324E Elements of Regression Analysis (replacing SDS 332 Statistical Models for Health/Behavior Sciences) A follow-up to an introductory statistics course, with an emphasis on the use of regression analysis in applied research. Topics may include: multiple linear regression; ANOVA; logistic regression; random and mixed effects models; and models for dependent data. Emphasis is placed on identification of appropriate statistical methods and interpretation of software output. R programming is introduced.

Prerequisite: SDS 302F or SDS 320E (or SDS 302, 304, 306, 328M)

Only one of the following may be counted: Statistics and Data Sciences 324E or 332.

Flag: Quantitative Reasoning

**Even though course names have changed, you can look at the past syllabi for course information!**

SDS 302F and SDS 320E: Look at the syllabus for SDS 302 (302F) or SDS 328M (320E), these are identical.

SDS 324E will be similar but not identical to SDS 332. Look at a the SDS 332 syllabus for a general example.

SDS 322E will be similar but not identical to SDS 348. Look at a SDS 348 syllabus for a general example.

https://utdirect.utexas.edu/apps/student/coursedocs/nlogon/

Have questions? Contact us at: stat.admin@austin.utexas.edu