Rejecting null hypothesis means that rumour of a fact is been experimented in d lab and the reseacher later discovered that hypothesis pseudo i.e fack fact but not a theory
The null hypothesis will not reject - it is a hypothesis and is not capable of rejecting anything. The critical region consists of the values of the test statistic where YOU will reject the null hypothesis in favour of the expressed alternative hypothesis.
The null hypothesis of the independent samples t-test is verbalized by either accepting or rejecting it due to the value of the t-test. If the value is less than 0.05 it is accepted and greater than 0.05 is rejecting it.
We have two types of hypothesis i.e., Null Hypothesis and Alternative Hypothesis. we take null hypothesis as the same statement given in the problem. Alternative hypothesis is the statement that is complementary to null hypothesis. When our calculated value is less than the tabulated value, we accept null hypothesis otherwise we reject null hypothesis.
If we reject the null hypothesis, we conclude that the alternative hypothesis which is the alpha risk is true. The null hypothesis is used in statistics.
0.05 level of significance indicates that there is a 5% chance (0.05) that, under the null hypothesis, the observation could have occurred by chance. The 0.01 level indicates that there is a much smaller likelihood of the event occurring purely by chance - much stronger evidence for rejecting the null hypothesis in favour of the alternative hypothesis.
Rejecting a true null hypothesis.
Increasing alpha from .01 to .05 will increase the probability of rejecting the null hypothesis when it is true.
Yes, usually.
sample size
An alpha error is another name in statistics for a type I error, rejecting the null hypothesis when the null hypothesis is true.
The null hypothesis will not reject - it is a hypothesis and is not capable of rejecting anything. The critical region consists of the values of the test statistic where YOU will reject the null hypothesis in favour of the expressed alternative hypothesis.
No. Rejecting the Null Hypothesis means that there is a high degree of probability that it is not correct. This degree of probability is the critical level that you choose for the test statistic. However, there is still a small probability that the null hypothesis was correct.
Rejecting a true null hypothesis.
This will reduce the type 1 error. Since type 1 error is rejecting the null hypothesis when it is true, decreasing alpha (or p value) decreases the risk of rejecting the null hypothesis.
I believe you have to design a null hypothesis that is very precise in order to avoid false positives ( rejecting the null hypothesis when it is actually true). Tricky question though!
Probability of rejecting a true null hypothesis; that is, the alpha value or risk you are willing to take probabilistically speaking.
The process is called hypothesis testing. If you are inquiring on how to prove or disprove a claim, search for the article on wikipedia.