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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.
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 term hypothesis is used in science and statistics. I have included two links related to the these terms.In statistics, the null and alternative hypothesis are mathematical statements used in statistical decision making. An example of a null hypothesis is the mean of the population from which a sample was obtained is equal to 10. The mean of the data is sufficiently different from 10 can be used to reject the null hypothesis.As used in science, hypothesis is the initial idea suggested by observation or preliminary experimentation. See related links.
The add vantage of the null hypothesis testing is when used to determine errors in tolerances the null hypothesis will always land you on the side of safety. This is often used when the importance of quantity or quality is extremely important. The case of filling medicine in to a capsule would require a very close tolerance, the null hypothesise could set an undefined error, however this is much safer than a wide tolerance which could result in a dangerous outcome.
what is an example of a hypothses about compensation?