The Statistical Consulting Center (SCC)
offers statistical consulting to faculty, staff, graduate and undergraduate students conducting research at Miami University. The SCC is a group of statisticians who provide consultation on all aspects of data collection, analysis and interpretation. The Center is funded by the University to promote high quality statistical consulting to researchers and is staffed by a Manager and full-time statistics faculty in the Department of Statistics.
Consulting services will be provided free to Miami University students, faculty and staff who have no external support, or on a cost recovery basis to those with externally funded support. External projects are accepted on a case by case basis and will be charged competitive rates.
How to Use the Center
Contact the SCC at the earliest possible stage of your research. We recommend that potential clients contact the SCC at the earliest possible stage of research planning and manuscript or grant preparation to help ensure a successful statistical analysis. If you would like to discuss your statistical design and analysis needs with the SCC, or if you need additional information, call the Center at 529-5148 or e-mail the Manager to set up an appointment.
Services Provided by the SCC
The SCC can play an effective role as a member of your research team, providing valuable input and expertise in the analysis of your research data. Specifically, we can assist in the following areas:
- Proposal Preparation
- The SCC is happy to assist you in the preparation of research proposals, providing guidance in both the sizing of statistical studies and development of methods section writeups.
- Data Management
- We can update or manipulate research data from any one of a number of data or spreadsheet formats and can offer advice regarding how to structure your data most effectively for analysis. We can also provide assistance with many popular data analysis software applications.
- Before the Analysis
- We can assist you regarding the effective collection of your sample data, designing your experiment or survey, and advising you regarding the most appropriate statistical methodology for your data.
- Data Analysis and Statistical Modeling
- The SCC is fully qualified to provide you with data analysis capabilities ranging from the most basic standard descriptive statistical techniques to the most powerful modern inferential statistical methods. Areas of expertise include:
- Design of Experiments and Analysis of Variance (ANOVA)
- Multiple Regression (including response surface methodology and robust regression methods)
- Generalized Linear Models (including logistic/probit/Poisson regression, linear and non-linear mixed models)
- Multivariate Data Analysis techniques
- Biostatistics and Survival Analysis
- Categorical Data Analysis
- Nonparametric Statistics
- Quality Control and Industrial Statistical Methods
- Sample Survey Design Analysis
- Exploratory Data Analysis (EDA)
- Bayesian Methods
- Computational Methods (including Monte Carlo simulation and bootstrap methods)
- After the Analysis
- Once your data have been analyzed, we will assist you in interpreting analysis results into clear, understandable findings. SCC is also happy to be involved in the preparation of research manuscripts for publication.
Computing Resources Available
The SCC staff maintains expertise in many popular statistical analysis software applications, including SAS, SPSS, R and Minitab. We also provide data importation from a wide variety of data formats, including Excel spreadsheets.
SCC Staff and Affiliated Faculty
- Michael R. Hughes
- M.S., Miami University
SCC Manager and Consultant
- Dr. A. John Bailer
- Ph.D., University of North Carolina
Biostatistics, Quantitative Risk Estimation, Statistical Methods for Environmental & Occupational Health
- Dr. Robert Davis (Hamilton Campus)
- Ph.D., University of Southwestern Louisiana
Statistical Process Control, Environmental Statistics
- Dr. Charles Dunn
- Ph.D., Texas A&M University
Statistics, Multivariate Analysis
- Dr. Thomas Fisher
- Ph.D., Clemson University
Multivariate Analysis, Time Series Analysis
- Dr. SeonJin Kim
- Ph.D., Pennsylvania State University
Time Series, Longitudinal data, Quantile regression
- Dr. Douglas Noe
- Ph.D., University of Illinois
Data Mining, Bayesian Methods
- Dr. Byran Smucker
- Ph.D., Pennsylvania State University
- Dr. Stephen E. Wright
- Ph.D., University of Washington
Mathematical Optimization, Applications of Optimization in Science and Statistics
- Dr. Jing Zhang
- Ph.D., University of Missouri-Columbia
Bayesian Statistics, Spatial Analysis, Statistical Modeling for Environmental & Biological Study