Terms commonly associated with statistical hypotheses are null hypothesis and alternative hypothesis. Thus a theory is a hypothesis explaining various other hypotheses. The former assumes that the operator of implication between two hypotheses produces a hypothesis. Data is collected and analyzed to answer questions, test hypotheses or disprove theories. A variety of hypotheses and theories suggests multiple factors contributing to stuttering. Collected and systematized data allowed exposing to empirical testing a number of existing hypotheses. It is an ensemble of all the hypotheses in the hypothesis space. Scientists have proposed several plausible hypotheses, which share some common elements. Methods of verifying statistical hypotheses are called "statistical tests". None of these hypotheses can explain the experimental data entirely. Quantitative methods can be used to verify which of such hypotheses are true. This view is challenged by others, who dismiss such hypotheses as insupportable supposition. Opinion is currently divided between these conflicting hypotheses. They argued that Theobald's test was insufficient to distinguish between the competing hypotheses. In a confirmatory analysis clear hypotheses about the data are tested.