Submit an Abstract
Would you like to share your experience as a statistical practitioner solving real-world problems? If so, an electronic poster presentation is a great way to do so while having an extended face-to-face discussion with others interested in your topic. A poster presentation also serves as an excellent teaching tool, allowing for direct and immediate feedback; broad exposure; and the ability to display extensive graphics, tables, and animations.
We invite you to submit your abstract for an electronic poster presentation at the Conference on Statistical Practice 2018. The submission deadline is August 31, 2017. You will have 75–90 minutes to engage your audience in one of the following four broad themes (described more fully below):
- Communication, Collaboration, and Career Development
- Data Modeling and Analysis
- Data Science and Big Data
- Software, Programming, and Data Visualization
What to Include in Your Abstract Submission
Only a limited number of abstracts will be accepted. We are looking for abstracts that:
- Interest and entice statistical practitioners from a variety of industries
- Describe the intended audience, including the primary application area(s) and content level (introductory, intermediate, or advanced)
- Demonstrate relevance to the conference goals and themes
- State clear and specific objectives
- Provide immediate practical value to the audience (handouts and online materials encouraged), enabling them to:
- Apply a statistical technique in their job as applied statisticians
- Better communicate with their clients and customers
- Positively impact their organization or enhance their professional development
Each abstract submission should also include:
- Poster title, abstract, and poster presenter name(s) and organization(s)
- Qualifications of the presenter(s), demonstrating expertise in the poster topic (e.g., education, training, experience, or previous papers or presentations on the topic)
- List of any software you are using (Any reference to software should only be used to illustrate your ideas and demonstrate their practical implementation and applications, rather than advertise the software itself or convince conference participants to purchase it.)
Single-slide posters with hyperlinks to graphics or background information are preferred; if a multiple-slide poster is used, we recommended no more than four slides be included. Presenters should also have a one-minute “elevator pitch” prepared to orally present and summarize their material. For more information about the poster format, see Poster Presentation Tips.
Students are encouraged to submit an abstract. This year, as in previous years, there will be an award for the best student poster. All student posters presented at CSP2018 will be evaluated by a panel of four judges at the conference. The judges will appraise each student poster on the topic, methods used, and presentation of the material visually and orally. The award for the best student poster will be announced at the Closing General Session of the conference (4:15 p.m. Saturday) and reported by the ASA on Facebook and Twitter and in Amstat News. The winner will be given a certificate from the ASA and a one-year student membership.
We look forward to receiving your abstract submissions for poster presentations.
Theme Descriptions
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
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
Big Data and data science 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 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
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 communication and data discovery
- Statistical applications of general programming languages