From Triola, 2009, it is: "The null hypothesis (dented by H0) is a statement that the value of a population parameter (such as proportion, mean, or standard deviation) is equal to some claimed value.".
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Power analysis can be used to calculate statistical significance. It compares the null hypothesis with the alternative hypothesis and looks for evidence that can reject the null hypothesis.
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
No. The null hypothesis is not considered correct. It is an assumption, and hypothesis testing is a consistent meand of determining whether the data is sufficiently strong to say that it may be untrue. The data either supports the alternative hypothesis or it fails to reject it. See examples in links. Also note this quote from Wikipedia: "Statistical hypothesis testing is used to make a decision about whether the data contradicts the null hypothesis: this is called significance testing. A null hypothesis is never proven by such methods, as the absence of evidence against the null hypothesis does not establish it."
The null hypothesis is an hypothesis about some population parameter. The goal of hypothesis testing is to check the viability of the null hypothesis in the light of experimental data. Based on the data, the null hypothesis either will or will not be rejected as a viable possibility.
Be able to reject the null hypothesis and accept the research hypothesis