ABSTRACT
This chapter addresses the problem of assessing candidates for a job that requires certain skills. The idea is that candidates will take a multiple-choice test and we will use model-based machine learning to determine which skills each candidate has (and with what probability) given their answers in the test. When designing a model of some data, one must make assumptions about the process that gave rise to the data. Incorrect assumptions will lead to models that give inaccurate predictions due to these faulty assumptions. Poor assumptions about scope often lead to unsatisfactory results of the inference process, such as reduced accuracy in making predictions. The scope of a model is an assumption that should be critically assessed during the model design process, if only to identify aspects of the problem that are being ignored.
