As noted by scientist and philosopher William Whewell (1794–1866), "invention, sagacity, [and] genius" are required at every step. Formulation of a question The question can refer to the explanation of a specific observation, as in "Why is the sky blue?" but can also be open-ended, as in "How can I design a drug to cure this particular disease?" This stage frequently involves finding and evaluating evidence from previous experiments, personal scientific observations or assertions, as well as the work of other scientists. If the answer is already known, a different question that builds on the evidence can be posed. When applying the scientific method to research, determining a good question can be very difficult and it will affect the outcome of the investigation. Hypothesis A hypothesis is a conjecture, based on knowledge obtained while formulating the question, that may explain any given behavior. The hypothesis might be very specific; for example, Einstein's equivalence principle or Francis Crick's "DNA makes RNA makes protein", or it might be broad; for example, "unknown species of life dwell in the unexplored depths of the oceans". See § Hypothesis development A statistical hypothesis is a conjecture about a given statistical population. For example, the population might be people with a particular disease. One conjecture might be that a new drug will cure the disease in some of the people in that population, as in a clinical trial of the drug. A null hypothesis would conjecture that the statistical hypothesis is false; for example, that the new drug does nothing, and that any cure in the population would be caused by chance (a random variable). An alternative to the null hypothesis, to be falsifiable, must say that a treatment program with the drug does better than chance. To test the statement a treatment program with the drug does better than chance, an experiment is designed in which a portion of the population (the control group), is to be left untreated, while another, separate portion of the population is to be treated. t-Tests could then specify how large the treated groups, and how large the control groups are to be, in order to infer whether some course of treatment of the population has resulted in a cure of some of them, in each of the groups. The groups are examined, in turn by the researchers, in a protocol. Strong inference could alternatively propose multiple alternative hypotheses embodied