Chapter 10 Study Questions

  1. What is the difference between descriptive and inferential statistics? Which do we use to assess statistical significance in fMRI?
  2. What are Type I and Type II errors? Which is typically minimized in fMRI data analysis?
  3. What is an alpha value? Does it relate to Type I or Type II errors?
  4. What is a t-test used for in statistical testing? How does this relate to the idea of “contrast”?
  5. What is a correlation coefficient used for in statistical testing? How does this relate to the idea of a “model,” which is the second core concept of fMRI data analysis?
  6. What does a Fourier transform do to a time series of data? For what sorts of experimental designs might it be useful?
  7. Write the basic model for a regression analysis (using the general linear model).
  8. What are the four types of matrices used in an fMRI regression analysis?
  9. What is a nuisance regressor? List some common nuisance regressors included in an fMRI model.
  10. What does it mean to orthogonalize two regressors? Describe a situation in which an experimenter might use orthogonalization.
  11. What two approaches might an fMRI experimenter take when dealing with an independent variable that could take any of several levels?
  12. What does it mean to include a set of basis functions in a model?
  13. Why must fMRI researchers correct for multiple comparisons?
  14. What are the differences between controlling for the family-wise error rate and controlling for the false discovery rate? Which tends to involve a more stringent statistical threshold?
  15. What are the advantages and disadvantages of region-of-interest analysis?
  16. Why do fMRI analyses typically use a random-effects statistical model?
  17. What is a reverse inference? When is it justified, and when is it not justified?
  18. What is the difference between radiological and neurological conventions for displaying MRI data?
  19. Describe some of the common ways in which fMRI data are displayed.
Back to top