BL08 P-Values

The Logic of P-values + Adjusting P-values for Multiple Tests

This lecture explains the logic of p-values, and how they measure TYPE I error -- the probability of rejecting the null hypothesis of a match between the model and the reality WHEN the null hypothesis is true. NEXT it discusses how multiple tests expand the Rejection Region, which must be considered as a whole to arrive at the p-value. In case of INDEPENDENT test, it is easy to come up with a combined p-value. This is demonstrated with daily exchange rate data for Chinese Yuans versus US Dollars. Various types of MATCH hypotheses are tested in the context of this data. Does the probability remain the same across periods, Is there clustering of up and down returns, and others.