This chapter introduces three applications of Bayesian inference to common and novel issues in second language research. After a review of the critiques of conventional hypothesis testing, our focus centers on ways Bayesian inference can be used for dealing with missing data, for testing theory-driven substantive hypotheses without a default null…

Answers to theoretical questions about the place of input in a formal second language acquisition model are dependent on a distinction between two kinds of learner hypotheses. Type-N hypotheses require "negative evidence" for testing, while Type-P hypotheses are tested on the basis of "positive data" alone. (Author/CB)