HYPOTHESIS TESTING

Statistical hypothesis is a statement while on a population or more. In statistics, hypothesis testing is an important part to make a decision. By testing the hypothesis of the researchers will be able to answer questions posed by declaring the rejection or acceptance of the hypothesis. Hypothesis is certainly truth may never be known unless the observation of the entire population. To do this it is not efficient especially when the population size is very large.
Withdrawal of a random sample from a population, the observed characteristics and then compared with the hypothesis put forward is a step to test the hypothesis. If the random sample is an indication that support the hypothesis then the hypothesis is accepted, whereas if the random sample indicated that contrary to the hypothesis, the hypothesis is rejected.
In hypothesis testing there are two types of errors are errors of type I and type two errors. Type I errors are errors that occur due to reject H0 when H0 is true, whereas type II errors are errors that occur due to accepting H0 when H1 is true.

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