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Center of Actuarial Excellence Actuarial Science at Illinois State University
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Projects from prior years' competitions are posted at:

Illinois State University Predictive Analytics Competition

This competition used to be called: Statistical Project Competition until July 1, 2018.

Starting with the 2014/2015 academic year, Illinois State University administers an annual Predictive Modeling Competition open to all students at at Illinois State University. This competition is a joint initiative of the Department of Mathematics, Actuarial Program, and the Katie School of Insurance and Financial Services.

The 2020/2021 competition can be entered by an individual student, or a group of students together, but if a project is given a monetary award, its amount will be unaffected by whether the project was submitted by an individual or a group.

Students who want to participate are expected to develop an advanced level statistical project, senior level (comparable to projects done in the MAT 353 class) or graduate level, with a clearly defined hypothesis analyzed with data, and with clearly specified statistical methodology used in the process. Students are responsible for creating a proposal, obtaining data, and developing the project. Students can consult Illinois State University faculty, members of the Project Committee, data sources made available by Katie School, and any other sources they have access to, but academic integrity is expected, and all data sources must be verifiable and obtained legitimately.

We have obtained external funding for this competition that may be used to pay awards for projects that address public policy issues. Also, Open The Books, a Project of American Transparency, a non-profit organization dedicated to transparency in government, has offered to share the data they hava available, and other data sources on public policy issues can also be used, as long as the data is legitimate.

Students (or teams) who want to participate in this competition must submit a proposal for a project by November 1 in the Fall semester. The proposals will be evaluated by the Predictive Modeling Competition Committee, identified below, and students will be notified in early December if their projects have been approved. Then in the following Spring semester, students whose projects have been approved can (but will not be required to) take MAT 390 (undergraduate) or MAT 490 (graduate), and work on the project. The projects must be submitted by April 1, and submission must include:

- A paper presenting the work,

- Powerpoint presentation of main points of the work,

- Full documentation of data sources, data used, and statistical analysis done. 

The work submitted should be done by the individual or group participating in the competition, and not by anyone else. Students will be required to sign a statement certifying that.

Three projects chosen by the Project Committee will receive a yet unspecified monetary award and will be recognized on the web sites of the Actuarial Program and the Katie School. More projects may be awarded some form of recognition, if the Project Committee so decides. All decisions of the Project Committee are final. Students may contact the Project Committee to ask for advice or guidance, but we ask that such contacts be first initiated through Dr. Ostaszewski or Dr. Cheng. 

The Project Committee has the following membership:

 Chair: Krzysztof Ostaszewski, Professor of Mathematics and Actuarial Program Director, Illinois State University,

 Statistical adviser for students and Vice Chair: Fuxia Cheng, Professor of Statistics, Illinois State University,

Askar Choudhury, Professor of Management & Quantitative Methods, College of Business, Illinois State University,

 Jeffrey Cole, Sentry Insurance,

Jim Jones, Director of Katie School of Insurance and Financial Services at Illinois State University,

Sunish Memon, State Farm Insurance,
Drew Lawyer, Earnix

Lois She-Ton, Country Financial
Klayton Southwood, Willis Towers Watson.

Questions on this Statistical Project Competition are welcome and can be sent to: