Health, Exercise Science, and Recreation Management

School of Applied Sciences, University of Mississippi

Health and Sports Analytics Laboratory


The Health and Sports Analytics Laboratory, directed by Dr. Minsoo Kang, is focused on application of measurement, mathematical models, statistical methods, and research methodology in the area of health, exercise science, and sports/recreation. The lab supports faculty led research projects and provides research opportunities for students in the HESRM department.

The lab is comprised of doctoral students who choose an Analytics cognate from various emphasis areas in the department (contact Dr. Kang for more information). Doctoral students in the lab receive educational training and offer statistical consulting services to students and faculty. In addition to statistics, lab members consult on and train clients in psychometrics and measurement issues as well as research design. Additionally, the lab provides an annual statistics workshop for students and faculty. Stay tuned for the event updates.

Resources Offered

In addition to general statistical consulting and training, the lab offers specialized assistance in advanced measurement and statistical analyses and a variety of software programs. Topics supported include: descriptive statistics, hypothesis testing, power analysis, T tests, chi-square tests, ANOVA, regression, item analysis, data mining, and meta-analysis. Software programs supported include: data analysis (CODA, GENOVA, SAS, SPSS, WEKA), power analysis (G*power), general (Microsoft Excel), psychometrics (Facets, Winsteps, Iteman) and meta-analysis (CMA). Another fundamental aspect of research design supported by the lab is instrumentation, including selection, development and validation.


Statistical Consultation Request:

To sign-up for an appointment, click on the following link:

For more information about research in the Health and Sports Analytics Laboratory, contact the lab faculty:

Faculty, Minsoo Kang, Ph.D.

Graduate student, Seungho Ryu, Ph.D. Student