Statistics, Modeling, and Computation
This summer research program at MIT focuses on Mathematical Statistics, more specifically including descriptive statistics, modeling construction, and numerical computation. Especially, several classical methods related to mathematical statistics in decision-making process will be detailly introduced, such as AHP, TOPSIS, RSR, etc. Whilst some commonly used mathematical software package such as MATLAB, SPSS, and LINGO will also introduced in the course of the statistics learning. Moreover, the research apprentics will introduced the usage of EndNote, a commercial reference management software package, used to manage bibliographies and references when writing essays and articles. Overall, by attending this program, the apprentics will have a large improvement in discovering, analyzing and solving practical problems from the mathematical perspective, that are closely related to their future studies.
Session 1: Introduction to statistics, modeling, and computation
Task 1: Summarize the overview (data, methodology, results) of the recommended papers, install some
Session 3: Analytic Hierarchy Process (AHP) Session 4: Entropy method
Session 6: Rank-sum ratio
Highlights: RSR, short for Rank-sum ratio, is a statistic analysis method originally proposed by F.T. Tian in 1993. It integrates the strongpoints of classical parametric estimations and modern nonparametric estimations. Since its first introduction in 1988, RSR has been quickly recognized as a powerful and promising statistical analysis research tool for mathematical modeling of operational processes. In this session, the apprentics will have a comprehensive understanding in the application of RSR for grouping in monitoring process.
Session 7: Clustering Analysis (CA) ............
Task 7: Apply the CA to solve a grouping problem related to a specific project (benchmarking road safety).