Key Dates

    Attend

  • September 29, 2016
    Early Registration and Housing Opens
  • January 10, 2017
    Early Registration Deadline
  • January 11, 2017
    Regular Registration (increased fees apply)
  • January 17, 2017
    Housing Deadline
  • February 9, 2017
    Online Registration Deadline
  • February 23, 2017 – February 25, 2017
    CSP in Jacksonville, FL

    • Participate in Program

  • April 7, 2016 – May 12, 2016
    Short Course and Tutorial Abstract Submission
  • May 13, 2016 – June 23, 2016
    Concurrent Session Abstract Submission
  • July 1, 2016 – August 18, 2016
    Practical Computing Demonstration Submission
  • July 14, 2016 – September 1, 2016
    Poster Abstract Submission
  • November 17, 2016
    Speaker Registration Deadline

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Conference Information

“ The goal of the conference is to provide participants with opportunities to learn new statistical methodologies and best practices in statistical analysis, design, consulting, and statistical programming.

The Conference on Statistical Practice aims to bring together hundreds of statistical practitioners—including data analysts, researchers, and scientists—who engage in the application of statistics to solve real-world problems on a daily basis.

The goal of the conference is to provide participants with opportunities to learn new statistical methodologies and best practices in statistical analysis, design, consulting, and statistical programming. The conference also will provide opportunities for attendees to further their career development and strengthen relationships in the statistical community.

Theme 1: Communication, Collaboration, and Career Development

The objective for this theme is to help attendees develop skills and perspectives that will improve their personal effectiveness as statisticians in their roles as managers, leaders, strategists, consultants, and collaborators. Presentations will enable participants to return to their jobs with new ideas, techniques, and strategies to improve their ability to communicate effectively, have a greater effect on their organizations, and advance their careers. Potential topics include the following:

  • Career advancement and development
  • Organizational impact
  • Leadership, mentoring, and management skills
  • Presentation and oral communication skills
  • Presenting statistical results to nonstatisticians
  • Best practices in consulting and collaboration
  • Statistical ethics
Theme 2: Data Modeling and Analysis

The objective for this theme is to provide attendees with practical knowledge and techniques related to obtaining, creating, modeling, and analyzing data sets of various forms through the application of state-of-the-art statistical methods. Sources of data might be experimental, survey, or historical. Presentations will feature information relevant to a broad range of applied statisticians, regardless of industry or field of expertise. Potential topics include the following:

  • Experimental design
  • Collection or management of data
  • Modeling, inference, or prediction
Theme 3: Big Data and Data Science

Big Data and data science are at the forefront of statistical research and practice and require a complex set of computing, statistical, and communication skills. This conference theme aims to help practitioners working in these fields 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 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
  • Model validation and comparison approaches
Theme 4: Software, Programming, and Graphics

The objective for this theme is to help attendees integrate new or existing software, statistically oriented programming languages (R, SAS, etc.), or general programming languages (Python, Java, etc.) 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 displaying and exploring data
  • Statistical applications of general programming languages
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