Statistical Consulting Lab
The Statistical Consulting Lab at KSU was founded in 1946 to help KSU researchers who need statistical expertise. This proud tradition continues today.
Who we help
All KSU faculty, staff, graduate students and undergraduates who are doing research may seek statistical help.
- Researchers are expected to know the basics of statistics and are responsible for data entry and checking.
- Students, particularly graduate students, are strongly encouraged to take STAT 703 and/or 705, at a minimum.
- Researchers are encouraged to run as much of the computer analyses as possible. The courses STAT 725 and STAT 726 are especially useful for students who plan a research career after completion of their KSU degree.
What consulting services we provide
- Prior to data collection: Help with experimental design, survey design, sample size calculation.
- After data collection: Help with choice of proper statistical analyses, use of software (SAS, R), interpretation and presentation of results.
- It is always best to visit with us before data are collected.
How we provide consulting help and collaborative research
- Statistics faculty are available who have joint appointments with K-State Research & Extension (KSRE) to provide general statistical consulting or focused help with specific areas of statistics.
- Appointments may be made by contacting these faculty directly.
- As faculty are very engaged with existing projects, please plan for at least two (2) working days lead-time to schedule a meeting.
- Statistical Consulting Lab, Room 12, Dickens Hall
- Consulting is provided by Statistics graduate students under the supervision of Statistics faculty.
- There are no drop-in hours during Summer 2015.
- Please print and fill out our Consulting Project Form and email it to email@example.com or send via campus mail to The Statistics Consulting Lab, Dickens Hall.
- Statistics faculty, in general, engage in collaborative research with a wide variety of KSU researchers to develop new statistical methods or to apply established statistical methods to novel situations.