Statistical Consulting Center
Welcome to SDSU’s Statistical Consulting Center (SCC). Our members are faculty in the Statistics Division of the Department of Mathematics and Statistics, and graduate research assistants. We provide advice, project management, data management and statistical analysis for the university and private research community.
The SCC has a wide range of expertise in statistics and biostatistics and in the use of statistical packages such as SAS, SPSS and S-PLUS.
We are located in GMCS 520 (Geology, Mathematics and Computer Science building). To contact the consulting center: phone or send an email message to the current director. You will normally get a reply within 2 working days.
The Department of Mathematics and Statistics offers a course in Statistical Consulting (STAT 795) for advanced statistics graduate students. University graduate students and researchers may use the consulting course for free consulting services. Please contact the instructor of the course for these services.
To enhance university research efforts by offering quality statistical advice to faculty and student projects
To provide interdisciplinary research and collaboration opportunities for students and faculty from all departments
To train statisticians to communicate effectively with professionals from other disciplines
To develop collaborations with San Diego businesses through consulting projects
Type of Assistance Provided
The SCC offers a broad range of services including:
· Advice on experimental design
· Project management
· Data management
· Statistical analysis
· Assistance with statistical software and programming
· Guidance with Master’s theses and Doctoral dissertations
We do not do statistical tutoring.
Who Can Use Our services?
Our services are available to students and faculty of San Diego State University, and to industry, businesses, and individuals outside of the university.
For Business clients:
Initial consultation and subsequent analyses will both be billed at an hourly rate. Current rates may be obtained by calling the current director.
For University clients:
The initial consultation is free. Subsequent visits and analyses will be billed at an hourly rate. By mutual agreement, alternative forms of compensation may take the place of hourly billing.
For university clients with limited budgets and fewer time constraints, statistical analysis can be handled by graduate students in the Statistical Consulting course (STAT 795).
Graduate students looking for help with their thesis or dissertation are welcome but should first obtain the approval of their advisors.
Timeline for Projects
It is important to understand that very few consultations are resolved in the first meeting. This initial meeting is a chance for the SCC staff to become familiar with the research problem, after which we should be able to outline a course of action and provide an estimate of the time and cost involved. With most projects, we will have results in 2-4 weeks, at which point we will arrange a follow-up meeting to present the results. Occasionally, we will require three or more meetings, depending upon the depth and breadth of our involvement.
Preparing for the Initial Meeting
All statistical consultations begin with an Initial Meeting. This meeting includes the new client, a graduate student consultant and a faculty member of the SCC. The purpose of this meeting is to describe the relevant background, research. We encourage you to contact us before data is collected. This way we can help develop a data collection plan that meets your time and budget needs and will yield statistically meaningful data.
Course Syllabus Statistical Consulting
Applied statisticians typically work in collaboration with professionals in other fields. To prepare students better for such collaborations, Statistics 795 will challenge students to integrate and apply the knowledge they acquire elsewhere in the graduate statistics curriculum. We will also discuss professional standards and the interpersonal skills necessary for effective statistical consulting.
Thus, Statistics 795 will serve as a practicum in statistical communication and problem solving. The course is highly recommended for second-year graduate students in statistics. The stated prerequisite is Statistics 670B, but interested students may also be admitted with the consent of the instructor. In addition to gaining experience in the application of statistics, students may encounter problems that suggest areas of inquiry suitable for M.S. theses in Statistics.
Through course readings and viewing videotapes of consulting sessions, we will discuss heuristics for effective problem identification and positive interaction with clients, as well as oral and written presentation skills. This orientation phase will comprise approximately 25 percent of the course. In the practicum phase (the other 75 percent) students will spend most of their time working with clients, usually graduate students in other departments.
Students will be required to prepare and maintain client files that include a description of the client’s problem and recommendations for solution made by the student consultant. In consulting activities students will be evaluated on three aspects: (1) the student’s professional behavior, (2) the process of the student’s interactions with clients, and (3) the content of those interactions. Short papers and exercises will also be assigned on topics related to statistical consulting.
Note that this is a two-unit course. Students wishing to enroll for three units are encouraged to register also for the Statistics 720 seminar on current topics in statistics. The activities in Statistics 795 will be coordinated with the SDSU Statistical Consulting Center.
C.D. (Joey) Lin, Associate Professor
Spatial statistics, longitudinal data analysis, statistical computing,
global optimization, and statistical modeling in clinical trials.
GMCS 515, (619) 594-6186
SCC Consulting Statisticians
Barbara Bailey, Ph.D. (North Carolina State)
Kristin Duncan, Ph.D. (Ohio State)
Juanjuan Fan, Ph.D (University of Washington)
Ming Ji, Ph.D. (UC Davis)
Richard A. Levine, Ph.D. (Cornell University)
C.D. (Joey) Lin, Ph.D. (Texas A&M University)
Kung-Jon Lui, Ph.D. (UCLA)