In the podcast, Jessica describes common statistical pitfalls in genomic data analysis & the statistical reasoning required to correct these mistakes.

Common themes throughout include:

• hypothesis-driven science & critical scientific reasoning over data
• p-values and non-sensical null hypotheses/distributions
• the value of appearing statistically rigorous
• researchers cutting intellectual corners & digging themselves into local minima