Discussion of error rates and statistical power in hypothesis testing, along with a deeper investigation behind how the Student's t-test and the Chi-square test work and why they require the assumptions they do. An example paired-difference t-test with power analysis is done, and then lecture closes with a discussion of the multiple comparisons problem (applied to simulation problems) and tools, such as Bonferroni correction, that can be used to prevent "statistical fishing." Many Halloween-inspired examples are given during the lecture, and the relationship between ghost busting and statistics is exploited.