Goal: Review of core statistics for psychophysiology research

• Recall basic statistical concepts (from high school or from statistics at university or from Wikipedia: Statistics and Statistical_hypothesis_testing). As a guideline, you can follow the keywords included with the Q&A session below.

1. Q&A Session – a short series of keywords to “warm up”. Describe (in a few words) what are:
   1. Null hypothesis and Alternative hypothesis (and how they change when the t-test is one-tailed or two-tailed)
   2. Normal distribution
   3. Significance level (alpha)
   4. p-value
   5. Type 1 and Type 2 errors
   6. Student's t-test
   7. Analysis of Variance (ANOVA)
   8. Multiple comparisons
   9. Post-hoc tests

Statistics 101 lecture notes by J. Ochab

1. Practice session:
   1. Practice the basics of statistics by using Student's t-test and ANOVA to verify some statistical hypotheses in the Jupyter Notebook: Statistics 101

• Statistics Hell-P – nice introduction into core statistical concepts
• P-values Explained By Data Scientist – how to understand the p-values
• Interactions | Matt Golder – a very detailed explanation of what interactions in linear models are and are not
• Different types of error rates | mumfordbrainstats – explanation and visual comparison of PCER, FWER, and FDR for multiple comparisons problem in voxelwise testing of fMRI