In the simplest case, scientists want to determine a binary outcome for a hypothesis of interest: *true* or *false*. In more complicated cases, there may be many mutually exclusive hypotheses, and scientists want to determine which one is true. For example, which among different locomotion methods is the most comfortable? Proceeding with the simpler case, suppose that a potentially better locomotion method has been determined in terms of VR sickness. Let denote the use of the original method and let denote the use of the new method.

The set
is the independent variable. Each is sometimes called the *treatment* (or *level* if takes on real values). The subjects who receive the original method are considered to be the *control group*. If a drug were being evaluated against applying no drug, then they would receive the *placebo*.

Recall from Section 12.3 that levels of VR sickness could be assessed in a variety of ways. Suppose, for the sake of example, that EGG voltage measurements averaged over a time interval is chosen as the dependent variable . This indicates the amount of gastrointestinal discomfort in response to the treatment, or .

The hypothesis is a logical true/false statement that relates to . For example, it might be

(12.1) |

in which each denotes the ``true'' average value of at the same point in the experiment, by applying treatment to all people in the world.

(12.2) |

which implies that the new method has an impact on gastrointestinal discomfort; however, it could be better or worse.

Steven M LaValle 2020-11-11