Key Dates
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April 8 – May 12, 2015
Short Course and Tutorial Abstract Submission -
May 14 – June 25, 2015
Concurrent Session Abstract Submission -
July 1 – August 11, 2015
Practical Computing Demo Submission -
July 15 – August 27, 2015
Poster Abstract Submission -
October 1, 2015 – January 5, 2016
Early Registration -
November 4, 2015 – January 5, 2016
Abstract Editing -
January 6 – February 4, 2016
Regular Registration -
January 19, 2016
Housing Deadline -
February 18 – 20, 2016
CSP in San Diego
Conference Information
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, Impact, 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:
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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:
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Theme 3: Big Data Prediction and Analytics
The objective for this theme is to share current methods for solving inference, prediction, decision making, classification, and pattern recognition problems from extremely large, unconventional, or complex data. Presentations will involve large data applications, and topic surveys focused on tools and algorithms for large data applications are welcome. Potential topics include the following:
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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:
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