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USRESP Competition

The Undergraduate Research Project Competition (USRESP) is a competition for research projects conducted by undergraduate statistics and data science students.

The USRESP Submission Form can be found HERE.

Project Scope for USRESP Competition:

The research project competition is for undergraduate statistics and data science students who conduct research projects coming from activities like summer research projects, advanced senior-level course research projects, independent research projects (e.g., independent studies), Honors or capstone research projects, or extensions of class research projects.  Some submissions to USRESP are applied research projects using existing statistical/analytical techniques to solve real world problems, while others are methodological research involving statistical applications or simulation studies evaluating different techniques.

Who may participate?

  1. The competition is open to any undergraduate student globally.
  2. Students may work individually or in groups (max. 5). All participants must be undergraduate students at the time they conducted the research but may have recently graduated.
  3. Research must have been completed between May 1, 2023 and June 21, 2024. 
  4. Each student can be the author or a co-author of only one USRESP project submitted.
  5. DataFest projects should be submitted to the USCLAP competition (choose "DataFest" as the course; it will compete with projects from Intermediate level courses).
  6. If your project is a class project that is required or optional for intermediate-level statistics or data science course(s) that you are taking, and your project involves analyzing real data using the techniques learned from the current or earlier courses, you may want to consider submitting your project to the USCLAP competition instead.

The winning projects will be featured on the CAUSE website and announced in the Amstat News journal published by the American Statistical Association. The authors of the winning projects may also be invited to present their work at the Electronic Undergraduate Statistics Conference. Cash prizes of up to $250 will be awarded to winning projects!

Prepare a Submission

  1. Submissions will be blind-reviewed. 
  • Please remove faculty sponsor name(s), author name(s), college/university name(s), or any other information that links to the identity of the authors on your title page and in the text of the report (including any acknowledgment sections).
  • If the data used is specific to the institution, replace the institution's name with a general phrase, such as  "Institution".
  • Make sure the report follows the following guidelines.
    • The submitted report needs to be in pdf format (most files can be exported or printed to pdf).
    • A paper of no more than 20 pages reporting the results of your project that includes the following:
      • The research question(s).
      • Background/significance of the research.
      • The methods used to obtain and analyze the data.
      • The results of the analysis (tables, charts, graphs, significance, confidence intervals, descriptive text).
      • A discussion of the research, the limitations of the current research, reasonableness of any assumptions made, possibilities of future work/studies that should be conducted, etc.
    • The entire written report (excluding references and the title page) must be no more than 20 pages (single-spaced, 11 or 12pt font with standard 1-inch margins).
    • References should be listed at the end of the report and do not count against the 20-page limit.
    • In addition to the 20 pages with the main content, you should have a separate blinded title page (no author information -- see #1) which includes:
      • The title of the project and a one-paragraph abstract of the entire project with a recommended length of no more than 150 words.

    Example Submission Paper: You might submit a 20-page pdf document that consists of the title page, 18 pages of text/graphs, and a page of references. See past winners for examples.

    Complete a Submission

    1. To submit a project to the USCLAP competition, go to
    2. On the submission page you will be asked to provide the following:
    • Author and sponsor details such as:
      • Contact information and the names of project co-authors.
      • The name and email address of the instructor who sponsored your project. This individual will be contacted for additional details about the class (or DataFest) where the project took place.
    • A report file that follows the guidelines listed above in a pdf format (only pdf accepted).
      • Important: Submissions will be blind-reviewed. Names of authors, university/college information, or any information linked to authors should NOT be placed in the report file (including any acknowledgment sections) - author information only belongs in the submission form.

    Important notes:

    • Submissions that fail to adhere to the guidelines described above may be returned without review and consideration for awards.
    • CAUSE reserves the right to use the projects and abstracts for promoting undergraduate statistics and data science education. No material will be used for commercial purposes.
    • If data are collected on human subjects, it is the responsibility of the author(s) or their sponsor instructor(s) to ensure that IRB approval has been secured from their institution.
    • If fewer than 5 submissions are received in a category, then these submissions will be rolled into the next round of submissions.

    Assessment of the USRESP projects:

    Each project will be judged by multiple judges. The judges have expertise in statistics but do not necessarily have expertise in the applied domain of your paper. Therefore, you should construct a paper that is understandable to a reader with little knowledge of any applied domains that relate to your paper.

    Some general criteria that the judges may use include:

    1. Overall clarity and presentation
    2. Originality, creativity, and significance of the study
    3. Accuracy of data analysis, conclusions, and discussion

    A template with a potential structure for the paper is provided here.