Data Analysis

Statistical Consulting is available in many applied fields, e.g. epidemiological studies and survey sampling. We help plan, implement, and analyze your research study using advanced statistical methodology. In a well-planned data analysis study, researchers should collaborate with statisticians and information experts during the entire project. For this reason, we especially encourage you to contact us early in your project, preferably at the design stage. We provide statistical consulting services to assist clients during various stages of the study process.
  • Designing Statistical Analysis Plan
  • Exploratory Data Analysis
  • Data Visualization and Graphical Presentation
  • Statistical Modeling
  • Multivariate Analysis Techniques
  • Analysis of Data from Designed Experiments
  • Categorical Data Analysis
  • Analysis of Clustered or Longitudinal Data
  • Survival Analysis
Software Outsourcing

We have a strong software team to meet your software outsourcing needs. Our expertise highlights on mathematical and statistical algorithms development, dynamical graphical environment, web development, and Rich Internet Applications. We provide a complete software solution to customize your software to include an incorporate data center, data mining, mathematical models, statistical analysis, animations, and web publications.
  • Software Requirements and Specifications
  • User Interface Design and Testing
  • Algorithm Development and Verification
  • Simulation and Case Studies
  • Dynamic Graphics and Animation
  • GPU and Multicorr Processing
  • JavaScript, Java, C++, R, SAS Programming
  • Informatics, Web, IntraWeb and Desktop Systems
  • Wireless Communication
  • Technical Presentation and Web Publication
Technical Training

Our current training programs focus on two kinds of professionals: data analyst and computational statistician.

Data analyst: We provide courses in regression/statistical modeling methods for analyzing univariate and multivariate data. Advanced courses in longitudinal data analysis, survival analysis, and data mining methods are also available. The emphasis is to apply commercial software in data analysis, e.g. SAS and R. We apply real data in demonstrating the applications of data analysis software.

Computational Statistician: The aim is to learn how to develop statistical software. We teach numerical methods, algorithm development and statistical computing methods.
  • Statistical programming includes R, S-PLUS and C++ languages.
  • User interface design is a part of software development.
  • Simulation techniques are critical methods for evaluating the accuracy and efficiency.
  • Sensitivity analysis and graphical methods are also important in developing statistical methods.