Created by:   Johns Hopkins University, University of Colorado Boulder

  • Martin Lindquist, PhD, MSc

    Taught by:    Martin Lindquist, PhD, MSc, Professor, Biostatistics

    Bloomberg School of Public Health | Johns Hopkins University

  • Tor Wager

    Taught by:    Tor Wager, PhD

    Department of Psychology and Neuroscience, The Institute of Cognitive Science | University of Colorado at Boulder
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.5 stars
Average User Rating 4.5See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Ratings and Reviews
Rated 4.5 out of 5 of 116 ratings

It goes a bit too much into the details sometimes. Personal researches are sometimes required to understand what is explained.

This is a great course to have available. However, I do think that in order to truly grasp many of the concepts, you need to either have a good baseline statistical background (ie, more than one college stats course), or be willing to spend a lot more time looking up many of the concepts (though many can only be found referenced in papers). For those who are engaged in applied statistics/signal processing, this would probably be fine. The course was very interesting, but I do wish they spent a bit more time breaking down the statistical measures and more examples/figures/analogies to make the course overall more coherent, and encourage a deeper understanding from a big picture perspective. It would be helpful if they had optional supplementary videos that dive deeper into the stats for those who could use it.

Great course. Great overview of fMRI, including the background for statistical tests used.

Great course!