Hypothesis is examined very closely to see what it predicts, and the predictions are then rigorously tested. If the predictions are not supported by the results of experiments, the hypothesis is rejected but if they are confirmed, the hypothesis is supported.
Experiment it, brainstorm, use scientific method.
your conclusion should support your hypothesis
Aliens.
if the hypothesis is proven to be correct or incorrect
It means that she or he has to accept that the existing hypothesis appears to be true.
Reject the hypothesis.
It means there is no reason why he should reject it, whether because there is no evidence to the contrary or because an experiment set up to test it affirmed that hypothesis.
Evidence is data from an experiment which is used to verify or reject the original hypothesis in the conclusion. Evidence is gathered through the scientific method.
Some people say you can either accept the null hypothesis or reject it. However, there are statisticians that insist you can either reject it or fail to reject it, but you can't accept it because then you're saying it's true. If you fail to reject it, you're only claiming that the data wasn't strong enough to convince you to choose the alternative hypothesis over the null hypothesis.
Depending on the results of that test, either accept or reject that hypothesis.
if the hypothesis is proven to be correct or incorrect
You should reject the null hypothesis.
Be able to reject the null hypothesis and accept the research hypothesis
Be able to reject the null hypothesis and accept the research hypothesis
Be able to reject the null hypothesis and accept the research hypothesis
There is no truth in science. Truth is only meaningful in math, philosophy, religion and logic. A hypothesis can never be true. You either accept or reject a hypothesis. You accept the null hypothesis if you fail to reject it.
This is used in statistic to know whether to accept or reject a null hypothesis or alternative hypothesis
It means that she or he has to accept that the existing hypothesis appears to be true.
Some researchers say that a hypothesis test can have one of two outcomes: you accept the null hypothesis or you reject the null hypothesis. Many statisticians, however, take issue with the notion of "accepting the null hypothesis." Instead, they say: you reject the null hypothesis or you fail to reject the null hypothesis. Why the distinction between "acceptance" and "failure to reject?" Acceptance implies that the null hypothesis is true. Failure to reject implies that the data are not sufficiently persuasive for us to prefer the alternative hypothesis over the null hypothesis.
At the same level of significance and against the same alternative hypothesis, the two tests are equivalent.