What type of control charts are based on attribute data?

C. Fraction defective charts are indeed the correct choice when it comes to control charts based on attribute data. Attribute data typically represents qualities that are counted in categories, such as the number of defective items in a batch or the presence/absence of a feature. Fraction defective charts specifically track the proportion of defective items in a sample, making them a vital tool in quality control processes, particularly when it comes to monitoring processes that yield binary outcomes (pass/fail, good/bad).

In contrast, variable control charts (which are associated with the second choice) are utilized for data that is measured rather than counted. These charts focus on characteristics that can take on a continuous range of values, such as weight or temperature.

Type A control charts and range control charts pertain more to measures of variability and continuous data, where characteristics are measured and the data is subject to various statistical analyses. They are therefore not applicable for monitoring categorical data like the proportion of defective items. Fraction defective charts, however, are specifically designed for such attributes, making them the appropriate option in the context of the question.