Our statistical collaborators are trained to help design experiments, analyze and plot data, run statistical software, interpret results, and communicate statistical concepts to non-statisticians. Our assistance is free for University faculty, staff, and students on academic research projects. The collaborators are faculty and students in the Department of Statistics. The earlier in your research you request statistical advice, the better; so learn more about our collaboration service or Request a Collaboration Meeting.

A statistical consultant will be available when classes are in session to answer your quick questions or to help with research projects requiring less than 30 minutes of assistance. Walk-In Consulting appointments will be conducted via zoom. Request a Virtual Walk-in Appointment. When you sign up a link will be sent to your @vt.edu account.

For more in-depth questions or longer projects, complete the Collaboration Request Form and a team of statistical collaborators will be assigned to work with you. Note: Our collaborators do not assist with class projects or homework. Learn more.

We provide a series of evening short courses to help graduate students use statistics in their research. The focus of these two-hour courses is on teaching practical statistical techniques for analyzing or collecting data. Each course may have assignments to complete BEFORE attending. Registration is required for each course separately through NLI. View course list and register.

**Faculty are welcome to register and attend, but the courses are designed for graduate students.

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Sound Design.  Whether you are working on social  science or rocket science, we can create the study or experimental design to achieve your research objectives. We can maximize information given your resources with sound design.

Appropriate Analytics.  How do I demonstrate statistical significance? What do I do with my non-normal data?  Logistic regression or tree model? Text mining? Bayesian or frequentist? We can sort these issues out by collaborating on appropriate analytics.

Intelligent Interpretation. So, you have statistical results and you are ready to publish or report to your sponsor. You ask: What is the proper way to communicate my conclusions? What visuals support my data analysis? We’ve got your back with intelligent interpretation.

Growth. Onward and upward with SAIG. Sound statistical design, appropriate analytics, and intelligent interpretation are key elements in producing your best proposals and publications. Partner with SAIG and the sky is the limit on your research growth.

The topic of co-authorship can be a touchy subject. SAIG provides this document to express views on co-authorship. 

Co-authorship is not required for SAIG collaboration projects; however, if collaborators perform the work of a co-author, they should receive the credit of co-authorship. 

It is important to have a discussion about what work is to be completed and if it qualifies for a co-authorship.

SAIG bases co-authorship guidelines on those of the International Committee of Medical Journal Editors (ICMJE) which states that authorship credit should be based on 1) substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; 2) drafting the article or revising it critically for important intellectual content; and 3) final approval of the version to be published. Authors should meet conditions 1, 2, and 3. 1  

Another authorship guideline is the Galindo-Leal guide for explicit authorship 2. All individuals who work on a paper are assigned points based on their contribution (see Figure 1). If an individual reaches 25 points, he/she deserves to be a co- author. Points are per individual and can total over 100 for the entire paper.

1. http://www.icmje.org/icmje-recommendations.pdf
   http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html
2. http://www.academia.edu/1323050/Explicit_authorship