Academic Sections
The Call for Abstracts for SESUG 2025 is currently open! You can submit a proposal here:
SESUG encourages inclusion of papers involving any software products that relate to data manipulation and/or statistical computing.
Careers, Training, and Education (CTE)
- Career development, opportunities, and associated skill development for programmers, statisticians, data scientists, and related careers.
- Training methods for professionals—in person or virtual, individual or group.
- Classroom use of software including but not limited to the following.
- SAS in the classroom – SODA, Workbench for Learners, or any other platform.
- R for classroom use with Markdown, Quarto, or any other application.
- Early-career introduction to Git
Foundational Coding Skills (FCS)
- Basic concepts necessary for entry-level programming tasks including but not limited to the following.
- Basic data concepts: accessing metadata, concatenating/interleaving, match merge, applying simple functions, filtering, subsetting, conditional logic, sorting, etc.
- Simple numeric and graphical tools
- Controlling the programming environment, creating custom output
- Basic integration with other platforms, e.g., Power BI and Tableau
Intermediate and Advanced Coding Skills (IACS)
- Concepts necessary or mid- or high-level programming tasks including but not limited to the following.
- SQL and federated SQL
- User-defined functions
- SAS macro language or PROC DS2
- Efficient data handling with BY processing, arrays, hash objects, loops, etc.
- Reading and writing text files that require customized processing
- Specialized processes like PROC TEMPLATE in SAS or creating a package in R/Python
- Integration or comparison of software platforms including (but not limited to): SAS, Python, R, Tableau, Power BI, Microsoft Office, various RDBMS products, etc.
Data Collection, Management, and Manipulation (DCMM)
- As opposed to what might fall into FCS or IACS, topics that use any tools to:
- Comply with standards, such as CDISC
- Interact with APIs or do web scraping
- Work with RDBMS products
- Work with other types of non-native SAS/R/Python structures
- In addition to the above, projects that involve:
- Search techniques for data anomalies or errors and/or repair methods for the same
- Storage and retrieval strategies, especially as they relate to efficiency
Hands on Workshops (HOW)
- Interactive topics that fit into a 90 minute window
- Presentations must include “live coding” opportunities. E.g.,
- Pre-worked examples attendees can modify and execute to explore behavior of certain coding elements
- Exercises/activities for attendees to work on their own
Statistics, Modeling, and Analytics (SMA)
- Predictive modeling of any type
- Inferential methods/models
- Classification, clustering, dimension reduction
- Trial/experimental design
- Survey methodology
- Other statistics/analytics
Visualizations and Reporting (VR)
- Graphs, charts, maps
- Tables and reports (styles, structures)
- Dynamic versions of either of the above
- Automation of large sets of either of the above