Applied Statistics
Topics And Advisors
| Topic Area | Faculty Advisor(s) |
|---|---|
| Applied Probability | A. C. Heinricher, H. Sayit |
| Bayesian Statistics | B. Nandram |
Biostatistics | R. Kim |
| Industrial Applications | J. D. Petruccelli |
| Multivariate Analysis | J. D. Wilbur |
| Non-Parametric Statistics | J. D. Wilbur |
| Statistical Computation Stochastic Models | B. Nandram, J. D. Petruccelli |
| Survey Sampling Theory | B. Nandram |
| Time Series | J. D. Petruccelli |
Some Recent Probability and Statistics MQPs
- Hearing Data
- Students: Barber, Gary Paul Kulasekaran, Nedunceliyan
Advisor: PETRUCCELLI, J. D. (MA)
Sonification, the representation of data in an auditory format, has already found use in Electrocardiograms and Geiger Counters, which suggests potential applications in realms dominated by visually-based analysis methods. This project developed and studied three approaches to the sonification of time series data, using the Additive Classical Decomposition of time series as the starting point, with its own statistical analysis-and- mapping and sonification programs. Results of investigations by controlled experiment using human subjects suggest the sonification methods are effective. - Statistical Analysis of the MCAS
- Students: Darling, Gwenevere Lorraine Mwaura, Frida Wambui
Advisor: PETRUCCELLI, J. D. (MA)
This MQP modeled the MCAS (Massachusetts Comprehensive Assessment System scores in relation to certain socio- economic and demographic variables (our predictors) identified through our research. We employed multivariate statistical methods to build a multivariate regression model to identify the form of the association between scores and predictors. We specified a set of regressors that are functions of the predictors. Our analysis identified the statistically significant variables as well as investigated the evolution of MCAS scores over time.
Last modified: October 25, 2007 14:03:51