The James Rocco Data Research Scholarship provides up to $5,000 to support innovative, student-designed quantitative research projects to be carried out during the summer or the academic year. The purpose of the scholarship is to encourage the development of skills in using quantitative methods to derive information from data. This set of skills is increasingly important in many career paths and academic fields. Enormous amounts of data are now available in almost every academic field, providing numerous opportunities for quantitatively-based research projects that mine data for information.
Applicants must be a current student at Lake Forest College to be considered eligible for a Rocco scholarship. Students interested in applying for a James Rocco Data Research Scholarship are encouraged to speak with Professor Muris Hadzic, Assistant Professor of Finance before submitting a proposal.
Proposals for a James Rocco Data Research Scholarship should include the following:
- A set of well-defined questions to be answered. The answers will constitute the information generated from the project.
- A description of the data that will be used in the project. The applicant needs to show that the data is or will be accessible in a timely manner for the project to proceed.
- A description of the methodology to be used in the project. The applicant needs to show that they are capable of applying a scientific method to deriving information from the data. For example, if the project is using hypothesis testing, the applicant should show that they possess sufficient statistical knowledge to test the hypothesis. Examples of evidence of statistical/data analysis skills include but are not limited to formal course(s) in statistics/data analysis at Lake Forest College or other institutions, course(s) from online learning platforms such as Coursera, Udemy, Udacity etc., or prior experience working on data-intensive research project(s).
- A description of the tools to be used in the project. The applicant needs to show that they either are or will be capable of using the tools (e.g. a programming language, statistical package, machine learning library) needed to do the project.
- The name of a faculty member who has agreed to supervise the project and is willing to provide a recommendation.
The project may be done in the summer, or any other time in the academic calendar. Depending on the nature of the project, it could form the subject for a credit-bearing independent study, research project, or senior thesis. Alternatively, the project can be non credit-bearing.
Funding is not guaranteed for any proposal. All proposals will be evaluated by a committee appointed by the Provost and Dean of the Faculty, in consultation with the sponsor of the scholarship. Successful applicants will be expected to provide regular status reports and/or presentations on their projects to the selection committee. The final results of the projects will be made available on a platform to be determined by the panel.
For projects to be completed during the summer, applicants need to show that, during the term of the scholarship, they will not undertake any additional commitments (such as part-time job, internship, enrollment in summer school courses, on-campus job etc.) that might conflict with or impair their ability to complete their research agenda. Any additional commitments need to be limited to a maximum of 10 hours per week
Assistant Professor of Finance
Data Science Instructor