The Undergraduate Class Project Competition (USCLAP) aims at class projects conducted by undergraduate students in their statistics and data sciences courses at the introductory or intermediate level. Project submissions are a short report/paper (up to 3 pages in length).
The USCLAP Submission Form can be found HERE.
Project Scope for USCLAP Competition:
The class project competition is for undergraduate students who conduct projects as part of an introductory or intermediate level statistics or data science course. Most projects submitted to the USCLAP competition involve analyzing real data using existing statistical techniques. Students may choose any topic on which to conduct a study and students may use existing data or collect their own.
Who may participate?
- The competition is open to any undergraduate student globally.
- Students may work individually or in groups (max group size of 5). All participants must be undergraduate students at the time they conducted their class project but may have recently graduated.
- The project must have been completed during the 2023-24 academic year as part of an undergraduate class (optional projects are permitted). Note: When submitting a project, students will be asked to indicate their instructor's name and contact information in order to verify this information.
- Each student can be the corresponding author or a co-author of only one project submitted for the USCLAP competition.
- DataFest competition projects should be submitted to USCLAP (Choose "DataFest" as the course; it will compete with projects from Intermediate level courses).
- If the project is from a summer research program, advanced senior-level course project, independent research project, Honor's College research project or methodological study or simulation study for comparing different techniques, the student should likely submit the project to the USRESP competition.
The winning projects will be featured on the CAUSE web site 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
- 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 acknowledgments section).
- 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).
- The submitted report should be a 3-page (or shorter) paper 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 summary must be no more than 3 pages (single-spaced, 11 or 12pt font with standard 1-inch margins)
- In addition to the 3-page paper, you may have (in the same file) a blinded (no author information -- see #1) title page which includes:
- The title of the project and a one-paragraph abstract of the project (recommended length of no more than 150 words).
- References should be listed at the end of the paper and do not count against the 3-page limit.
- (Optional) You may include up to 5 additional pages of information about your project in an appendix (as part of the single uploaded file). This could include secondary analysis results, charts/tables, etc. The optional appendix may be reviewed by judges at their discretion if questions arise when reading the 3-page paper. There is no guarantee of this additional review; thus no information deemed critical to the evaluation of your project should be included in the Appendix.
Example Submission Paper: You might submit a 4.5-page pdf document that consists of the title page, 3 pages of text/graphs, and a half page of references. See past winners for examples.
Complete a Submission
- To submit a project to the USCLAP competition, go to https://www.causeweb.org/usproc/usclap/submissions.
- 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 document 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 acknowledgments section - author information only belongs in the submission form.
- Author and sponsor details such as:
- 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 USCLAP 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:
- Description of the data source
- Accuracy of data analysis, conclusions, and discussion
- Overall clarity and presentation
- Originality and significance of the study
A template with a potential structure for the paper is provided here.