Submit an Abstract

Abstracts are being accepted until June 21, 2018, for a limited number of concurrent session presentations. Each presentation will be for 40 minutes and should focus on any one of the following four broad themes.

Theme 1: Communication, Collaboration, and Career Development

The objective for this theme is to help conference participants develop skills and perspectives that will improve their personal and professional effectiveness as statisticians and increase their organizational impact as managers, leaders, strategists, consultants, or collaborators.

Presentations will enable participants to return to their jobs with new ideas, techniques, and strategies for improving their ability to assume leadership roles, communicate effectively, forge productive professional relationships, and develop and advance their careers.

Potential topics include the following:

  • Organizational impact and influence
  • Leadership and management
  • Mentoring
  • Effective communication
  • Presenting statistical results to nonstatisticians
  • Best practices in consulting and collaboration
  • Career development and advancement
  • Statistical ethics
Theme 2: Data Modeling and Analysis

The objective for this theme is to provide attendees with practical knowledge about modeling and analyzing data of various forms through the application of state-of-the-art statistical methods. Presentation methods should use illustrative data analysis examples reproducible across several statistical packages and may focus on a variety of data types from varied applied settings.

Presentations will feature information relevant to a broad range of applied statisticians working in diverse settings. Potential topics include the following:

  • Modeling
  • Inference
  • Prediction
Theme 3: Data Science and Big Data

Data science and big data are at the forefront of statistical practice and require a complex set of computing, statistical, and communication skills. This conference theme aims to help practitioners working in these fields to stay current with state-of-the-art methods for solving inference; prediction; decision-making; classification; and pattern-recognition problems from extremely large, unconventional, or complex data.

Presentations pertaining to this theme will involve large data applications; overviews/surveys of methodological tools; and algorithms for solving such applications and best practices for gathering, structuring, exploring, visualizing, and analyzing large amounts of data.

Potential topics include the following:

  • Capturing, exploring, and visualizing large amounts of raw data
  • Processing, tidying, and cleaning raw data to produce analyzable data structures
  • Scaling up statistical models for big data and data science applications
  • Analysis techniques for high-throughput screening
  • Text analytics and sentiment analysis
  • Applications of machine learning and deep learning
  • Model validation and comparison approaches
Theme 4: Software, Programming, and Data Visualization

The objective for this theme is to help attendees integrate new or existing software, statistically oriented programming languages (e.g., R, SAS), or general programming languages (e.g., Python, Java) into their current processes.

Presentations will focus on the practical application of such technology for the statistician or data analyst.

Potential topics include the following:

  • Software and programming methods to obtain, clean, describe, or analyze data
  • Methods for interactively sharing analysis results with other analysts or end users
  • Visualization methods for communication and data discovery
  • Statistical applications of general programming languages

What to Include in Your Submission

There are a limited number of slots available. Successful presentations have the following characteristics:

  • Immediate practical value
  • Clearly relevant to the conference goals and themes
  • Objective(s) are clear and specific
  • Evidence there will be audience engagement/participation with interactive exercises
  • Titles/content that create interest and/or clearly describe the deliverable

Each submission must include the following:

  • Presentation title, abstract, and presenter name(s) and affiliation(s)
  • Qualifications of the presenter(s) that demonstrate expertise in the practical application of the presentation topic, which may include education, special training or study, work experience, or previous papers or presentations on the topic
  • Abstracts must include an explanation of the following:
    • How the presentation will immediately help the participants:
      • Learn statistical techniques that apply to their job as an applied statistician
      • Better communicate with their clients and customers
      • Have a positive impact on their organization or enhance their professional development
    • How the material presented could apply across industries
  • An indication of whether the presentation is of an introductory nature

Note that the use of software in a presentation should only be to highlight the application or technique, not to promote or sell software. Also note that while we encourage ‘showcase’ applications from all industries (e.g., agricultural, biological, chemical, engineering, environmental, financial, government, marketing, software), the technique, lesson, or message presented should be applicable or spark thought across several industries.


Submit an Abstract


Key Dates

    Attend

  • September 28, 2018
    Early Registration and Housing Opens
  • January 10, 2019
    Early Registration Deadline
  • January 11, 2019
    Regular Registration (increased fees apply)
  • January 12, 2019
    Housing Deadline
  • February 14, 2019 – February 16, 2019
    CSP in New Orleans, LA
  • Program Participants

  • April 5, 2018 – May 10, 2018
    Short Course and Tutorial Proposal Submission
  • May 17, 2018 – June 21, 2018
    Concurrent Abstract Submission
  • July 12, 2018 – August 30, 2018
    Poster Abstract Submission
  • November 15, 2018
    Speaker Registration Deadline