You accept an alternative hypothesis when the p-value is greater than the sample a for a confidence level of 95%. The null hypothesis cannot be accepted.
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Be able to reject the null hypothesis and accept the research hypothesis
This is used in statistic to know whether to accept or reject a null hypothesis or alternative hypothesis
At the same level of significance and against the same alternative hypothesis, the two tests are equivalent.
F-test results will determine if the null hypothesis will be rejected or accepted. All test are ran with the assumption that the null hypothesis is true.
Statistical tests compare the observed (or more extreme) values against what would be expected if the null hypothesis were true. If the probability of the observation is high you would retain the null hypothesis, if the probability is low you reject the null hypothesis. The thresholds for high or low probability are usually set arbitrarily at 5%, 1% etc. Strictly speaking, when rejecting the null hypothesis, you do not accept the alternative hypothesis because it is possible that neither are true and it is the model itself that is wrong.