Michael M. Granaas
Walk-in Advising Fall 2012: No Appointment Necessary
I am continuing with my practice of posting open advising times and advising students on a "first come, first served" basis. No need to book an appointment, just show up during one of the times listed and we'll chat about your schedule.
Advising is best done a few days before you are scheduled to enroll.
When you arrive if there is already someone in my office, (or at my table in the MUC) make yourself known. Advising for most students is enhanced when 2-3 student are being advised at the same time. Often one student will ask a question or bring up an issue where the answer benefits another student.
Remember to bring a copy of your Webadvisor program of study.
I have created a simple advising worksheet to help you prepare for our meeting.
2012 - 2013 Catelog bachlor's degree requirements
(older catelogs may be accessed from the linked page)
A narrative accompanying the gen ed requirements is available.
might also want to look at Psychology major requirements.
ContentsSPSS Information and Handouts
Teaching and research. My primary teaching is in the area of research methods and statistics as they apply to psychology. I teach a range of courses from the sophomore level Introduction to Research to the graduate Multivariate. My research interests are primarily congruent with my teaching activities. See my current projects section for more information. I also serve the university on a variety of committees.
Psychology, College of
Arts & Sciences,
Electronic mail address: email@example.com
Heimstra Research Labs
Office phone: 605-677-5295
I am interested in a variety of methodological and statistical questions especially as they relate to psychological research. I am currently focusing on modeling as an alternative to null hypothesis testing and on the interpretation of interactions in Analysis of Variance.
I also have some interest in Human-Computer Interaction, but am not currently active in this line of research.
Finally, I have an ongoing interest in regression methods appropriate for data in which both predictor and response variables are measured with error. Combine this with my interest in modeling as an alternative to null hypothesis testing and my interest in Structural Equation Modeling is easy to understand.
B.A. 1981, Gustavus Adolphus College, Psychology and Computer Science
Look for interesting sites here sometime in the future