Well Rinku,
The scientific method, a system of hypothesis generation and testing, is the same whether used by laboratory scientists, epidemiologists, wildlife biologists, or others. A scientist begins with a curiosity about some particular topic and a question. Based on the scientist's previous observations and experience, she develops a hypothesis about how, why, or whether a particular phenomenon occurs. Next, she develops a test, or an experiment, to see how her hypothesis holds ap in the face of the evidence. In fact she is testing two hypotheses: the second, called the null hypothesis, is essentially the negative of the hypothesis she has developed. If, for example, her hypothesis is that (1) treating rats with the solvent toluene will result in birth defects in their offspring, the null hypothesis will state that (2) treating rats with toluene will not result in birth defects. Although it may seem counterintuitive, the scientist proceeds from the assumption that the null hypothesis is true.
Many nonscientists are not aware of the role of the null hypothesis in the scientific method which can lead to misunderstandings between scientists and nonscientists. In the logic of the scientific method, a scientist looking for evidence to support a hypothesis must do so by disproving the corresponding null hypothesis. In other words if she finds in her experiment that rats treated with toluene do in fact give birth to many more offspring with birth defects than do untreated rats, then she can no longer say that treating rats with toluene will not lead to birth defects. She then rejects the null hypothesis, and her experimental results support, but do not prove, the original hypothesis.
When deciding whether she can reject the null hypothesis, the scientist will use specific statistical techniques to assess the results of her experiment to determine whether the results are statistically significant. Statistical significance is a measure of the likelihood that a result did not occur due to chance alone. If the scientist decides that her result is not statistically significant, she fails to reject the null hypothesis. She states that nothing statistically significant happened in her experiment to support her original hypothesis, and she must go on to develop another hypothesis or refine the current one.
If, however, she decides that her result is statistically significant, she rejects the null hypothesis. Now she is in a curious position: she has shown that her on nag hypothesis has been supported, but she leas riot roved her hypothesis. She has simply shown that she has not found any result that disagrees with her original hypotheses. This is the scientists' dilemma: they can only support, but never prove a hypothesis. With more research and further experimentation the original hypothesis can be refined and further supported, elevated to the status of a theory, but in the end, the truth of a hypothesis is a matter of judgement rather than h proof.
Nonscientists can be frustrated when scientists are unwilling to give absolute answers. The inability to provide such answers is one of the limitations of the scientific method. The scientist, knowing that her method of analyzing cannot absolutely prove a hypothesis, will tend to be conservative in making a statement about the truth of a hypothesis. She knows that further research may reveal that the hypothesis is inadequate in some way, and so will state that the science is incomplete. The scientist may feel fairly confident that her hypothesis is valid if there is a good body of research supporting it and numerous other researchers have confirmed her results, but she still cannot say that she is absolutely sure. Many of the difficulties in using science in the decisionmaking process thus have their roots in the very nature of the scientific method.
source site :
http://www.mindfully.org/Precaut ion/Role-Of-Science.htm
Answered by
Priyanka C
, an ibibo Master,
at
11:02 PM on September 03, 2008