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Statistical Consulting

About

Welcome to the statistical consulting page. This page has information about scheduled and walk-in consultations, on-line statistical resources, and frequently asked questions. Please let us know if you were hoping to find something that wasn't available on this page, and we'll do our best to add it or to help you find another source for that information.

The Psychology Department's statistical consulting program is intended for graduate students, post doctoral fellows, and faculty in the Psychology Department. We are not generally able to provide consultation for students and faculty from outside of the department; however, those decisions are made on a case by case basis

Undergraduate students, please note that the Psychology Department's statistical consulting service cannot be used to get help with course work or to provide tutoring. Statistical tutoring can be arranged through the ASUU Tutoring Center (http://tutoringcenter.utah.edu/). The Marriott Library also offers assistance getting started with different statistics programs (Stata, SPSS, SAS). Their statistics graduate TA is available in Marriott Library 2110S on Monday 9 - 11:30 am, Tuesday 8:30 am - 11:30 am, Thursday noon - 4 pm, Friday 8:30 - 11:30 am, or by appointment (email: mlib-statistics@lists.utah.edu).

Scheduled Consultations

Now that we have a four person consultation team (Brian, Pascal, Nick, and Maddi) we are implementing a centralized system for scheduled consultation. Upon receiving a request, the four of us will compare who is available at the time to maximize our ability to provide timely and useful assistance. In order for this system to work effectively, we ask that requests for scheduled consultation be made well in advance of any deadline. Additionally, please make requests for scheduled consultation at least a week in advance during busier times of the year, such as shortly before standard NIH and NSF grant deadlines as well as before conferences heavily attended by students and faculty, such SPSP, ABCT, Psychonomics, and SRCD/SRA. We have noted these times of the year on the calendar below along with times when any of us are unavailable.

While we are always happy to provide consultation for any issue, we want to make sure that we preserve availability for advanced issues that often require longer amounts of consultation time. Please direct less advanced consultation questions to the graduate student consultant during walk-in hours if possible. To submit a request, please send an email to statsconsulting@psych.utah.edu with the following information:

  1. A brief description of your consultation question. If you have a question about a specific statistical procedure, please let us know.
  2. Is this request related to a paper, conference, grant submission, masters thesis, or dissertation? If applicable, what is the deadline for the request?

The four of us will work behind the scenes to match availability and expertise to the requests that we receive. We will aim to reply to emails sent to statsconsulting@psych.utah.edu within 2-3 business days with follow up questions or to schedule an appointment.

Walk-in Consulting

Maddi will be available for walk-in consultations hours.

Hours:
Tuesdays: 12:50pm - 2:00pm, 512 BEHS
Thursdays: 11:00am - 1:30pm and 2:30pm - 3:30pm512 BEHS

The availability of walk-in hours is intended to make it possible to get consultation on short-notice. It is expected that these will generally be less advanced consultation questions. Please consult the calendar above for days when office hours are cancelled (due to conference travel, etc.).

On-line Statistical Resources

Helpful Websites

  • UCLA Statistical Consulting - wealth of information about SPSS, SAS, Stata, R, MPlus, and HLM. Annotated examples of most statistical procedures in multiple packages.
  • Andrew Hayes' website - information on mediation and moderation. Code for mediation and moderation related procedures in SPSS, SAS, and MPlus.
  • David Kenny's website - information on mediation, moderation, and dyadic data analysis.

Mailing lists

Last Updated: 4/5/17