1. ORC ffice of esearch onsultation

2. Consulting Becoming a consultant Versus Needing a consultant

3. Resources There are many resources available to both consultants and those seeking consulting Cabrera, J., & McDougall, A. (2002). Statistical consulting. New York: Springer-Verlag. Balian, E. S. (1994). The graduate research guidebook. Lanham, MD: University Press of America.

4. A statistical consultant… Can quickly learn essential facts of the area and specific project under study Has the knowledge and skill to critique and advise on design and analysis options Has experience with multiple data analysis software programs – is computer literate Has strong verbal and written communication skills (Cabrera & McDougall, 2002)

5. Beginning the consulting session Initial interaction: Questions and answers Problem clarification: –Background –Current status –Project goals Expectations of the client Expectations of the consultant (Cabrera & McDougall, 2002)

6. Clients and consultants: Work toward… Defining your research philosophy Knowing what you are capable of Knowing what you need Knowing at what stage you need support Knowing when to seek a consultant Consultation Framework

7. There are as many research paradigms out there as there are researchers. However, a general statistical research paradigm embodied at the ORC is one that values theory driven, values quantitative and qualitative approaches to evidence gathering, but focuses on for quantitative data and. model building estimation of parameters tests of model fit A Research Paradigm Example

8. The philosophy of ORC is based on the consultantship model, which promotes the idea that the consultant does not simply solve problems for a client, but rather works collaboratively with the client to solve problems. ORC Philosophy

9. Come in the form of specific questions Developing testable research hypotheses Selecting an appropriate (workable) design Selecting or developing data collection instruments Planning data collection strategies Selecting appropriate statistical analyses Using computing packages Interpreting data analysis results Common Productive Requests

10. Will you edit my literature review – my grammar is not so great? Can you run the regression for me? You can do it so much faster. If I send you the output, can you write a couple of sentences of interpretation? Sample Unproductive Requests

11. Learning from experience –What works –What doesn’t work Exemplar Cases

12. Some Final Advice Plan ahead for what you would like to accomplish from each meeting Clarify timelines and terms of payment Document agreements from each meeting Follow-up each meeting with a message summarizing any agreements Make note of questions that arise when they arise to discuss at the next meeting

13. Go forth and consult www.tc.umn.edu/~orc orc@umn.edu