EMSW21-VIGRE Project: VIGRE-II - "Integrated and Mentored Program of Research and Education in Statistical Sciences" (IMPRESS)

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EMSW21 VIGRE Project: Integrated and Mentored Program of Researchand Education in Statistical Sciences (IMPRESS).The NC State Department of Statistics' second VIGRE program (IMPRESS) will continue development of the model training program for statisticians begun under the Department's first VIGRE award (VIGRE-I). Through participation of undergraduates, graduate students and postdoctoral trainees in faculty-mentored teams, our VIGRE program places problem-solving, research, consulting, and communication at the core of the learning process. Project IMPRESS will continue and expand upon the program of ambitious mentoring, research skills training, and practicum courses developed under VIGRE-I. IMPRESS will encourage participation by quantitatively-oriented students from diverse backgrounds and with diverse prior training, thus resulting in a net gain for the mathematical sciences of students from both traditional and under-represented student groups. IMPRESS will enhance the quality of statistics education at NC State and, through national dissemination, increase the number and improve the quality of statistical scientists in the professional workforce and the academy. The intellectual merits of our VIGRE program have been and will be manifest in the significance of the VIGRE trainees' and their mentors' contributions to statistical theory, methods and applications. Equally important are the indirect effects that the program will have on the conduct of data-dependent research in numerous fields of science and technology. Well-trained statisticians skilled at interacting with scientists from other disciplines are crucial to the advance of science. The human and societal impacts of Project IMPRESS include the current and future impact of our trainees' research on the conduct of science in numerous fields of science and technology, an increase in the number of statistically-trained scientists, and a broadening of the composition of the next generation of statistical scientists in terms of gender, ethnicity, and prior academic background.