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This article provides a short note on null hypotheses.
The alternative hypotheses and the null hypotheses together constitute the framework for the statistical testing of hypotheses. Fuller significance of null hypothesis can be grasped by the students at later stage.
Suffice it here to say that the null hypothesis in its simplest form asserts that there is no difference between two populations in respect of some property and that the difference found between the sample drawn from these populations is only accidental and unimportant. H. E. Garrett remarks:
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“The null hypothesis is akin to the legal principle that a man is innocent until he is proved guilty. It constitutes a challenge and the function of a (research) is to give facts a chance to refute this challenge.”
A null hypothesis in its other form may assert that the results found in research do not differ significantly from the results to be expected on a probability basis or as stipulated in terms of a certain theory. An alternative hypothesis may state,’ for instance, that:
H1:
The females commit suicide more often than the males.
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The null hypothesis (Ho) may be stated as:
Ho:
The females and males do not differ in respect of the rate of suicide. A null hypothesis is decidedly more useful than other hypotheses because it is exact. It is easier to disprove the contrary of an hypothesis than to prove it with complete certainty.
In other words, while a hypothesis cannot be shown to be true without factual consequences, it may be falsified conclusively if the expected consequences fail to occur.
This enables the researcher to eliminate some of the alternative hypotheses and while this does not finally establish the one he thinks to be true, he can never be sure that he has identified and eliminated all the alternatives; still his confidence in it will grow if it continues un-refuted.
It might also be the case that it cannot possibly be refuted, but in this case it would not be of much practical use. According to Karl Popper, the real basis of science is the possibility of empirical disproof. No amount of positive confirmation of the hypothesis, in Popper’s view, entails its truth.
One can only say that certain statement are definitely incorrect. Besides, the statistical techniques available to us are better adapted to test a null hypothesis.