Testing:

Then, the scientist performs the experiment to see if the predicted results are obtained. If the expected results are obtained, that supports (but does not prove) the hypothesis. In science when testing, when doing the experiment, it must be a controlled experiment. The scientist must contrast an “experimental group” with a “control group”. The two groups are treated EXACTLY alike except for the ONE variable being tested. Sometimes several experimental groups may be used. For example, in an experiment to test the effects of day length on plant flowering, one could compare normal, natural day length (the control group) to several variations (the experimental groups). When doing an experiment, replication is important. Everything should be tried several times on several subjects. For example, in the experiment just mentioned, a student scientist would have at least three plants in the control group and each of the experimental groups, while a “real” researcher would probably have several dozen. If a scientist had only one plant in each group, and one of the plants died, there probably would be no way of determining if the cause of death was related to the experiment being conducted. The experimenter gathers actual, quantitative data from the subjects. For example, it’s not enough to say, “I’m going to see how the dog reacts in this situation.” Rather, in that experiment, the scientist might have a list of certain behaviors, and record how often each of the dogs tested exhibits each of those pre-defined behavior patterns. Data for each of the groups are then averaged and compared statistically. It’s not enough to say that the average for group “X” was one thing and the average for group “Y” was another, so they were different or not. The scientist must also calculate the standard deviation or some other statistical analysis to document that any difference is statistically significant.