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Is The probability at which the null hypothesis can be rejected with confidence is known as level of significance?
Wiki User
∙ 10y ago
Yes.
Wiki User
∙ 10y ago
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Why is hypothesis could be rejected?
To reject null hypothesis, because there is a very low probability (below the significance level) that the observed values would have been observed if the hypothesis were true.
What is the significance of a hypothesis?
The significance test is the process used, by researchers, to determine whether the null hypothesis is rejected, in favor of the alternative research hypothesis, or not.
Why is the level of significance always small?
The significance level is always small because significance levels tell you if you can reject the null-hypothesis or if you cannot reject the null-hypothesis in a hypothesis test. The thought behind this is that if your p-value, or the probability of getting a value at least as extreme as the one observed, is smaller than the significance level, then the null hypothesis can be rejected. If the significance level was larger, then statisticians would reject the accuracy of hypotheses without proper reason.
If a test of hypothesis has a type I error probability of 0.01 it means?
It means that, if the null hypothesis is true, there is still a 1% chance that the outcome is so extreme that the null hypothesis is rejected.
Which is better a 005 level of significance or 001 level of significance?
"Better" is subjective. A 0.005 level of significance refers to a statistical test in which there is only a 0.5 percent chance that a result as extreme as that observed (or more extreme) occurs by pure chance. A 0.001 level of significance is even stricter. So with the 0.001 level of significance, there is a much better chance that when you decide to reject the null hypothesis, it did deserve to be rejected. And consequently the probability that you reject the null hypothesis when it was true (Type I error) is smaller. However, all this comes at a cost. As the level of significance increases, the probability of the Type II error also increases. So, with the 0.001 level of significance, there is a greater probability that you fail to reject the null hypothesis because the evidence against it is not strong enough. So "better" then becomes a consideration of the relative costs and benefits of the consequences of the correct decisions and the two types of errors.
Is The probability at which the null hypothesis can be rejected with confidence is known as beta?
no
Why is hypothesis could be rejected?
To reject null hypothesis, because there is a very low probability (below the significance level) that the observed values would have been observed if the hypothesis were true.
What is the significance of a hypothesis?
The significance test is the process used, by researchers, to determine whether the null hypothesis is rejected, in favor of the alternative research hypothesis, or not.
Why is the level of significance always small?
The significance level is always small because significance levels tell you if you can reject the null-hypothesis or if you cannot reject the null-hypothesis in a hypothesis test. The thought behind this is that if your p-value, or the probability of getting a value at least as extreme as the one observed, is smaller than the significance level, then the null hypothesis can be rejected. If the significance level was larger, then statisticians would reject the accuracy of hypotheses without proper reason.
If a test of hypothesis has a type I error probability of 0.01 it means?
It means that, if the null hypothesis is true, there is still a 1% chance that the outcome is so extreme that the null hypothesis is rejected.
Which is better a 005 level of significance or 001 level of significance?
"Better" is subjective. A 0.005 level of significance refers to a statistical test in which there is only a 0.5 percent chance that a result as extreme as that observed (or more extreme) occurs by pure chance. A 0.001 level of significance is even stricter. So with the 0.001 level of significance, there is a much better chance that when you decide to reject the null hypothesis, it did deserve to be rejected. And consequently the probability that you reject the null hypothesis when it was true (Type I error) is smaller. However, all this comes at a cost. As the level of significance increases, the probability of the Type II error also increases. So, with the 0.001 level of significance, there is a greater probability that you fail to reject the null hypothesis because the evidence against it is not strong enough. So "better" then becomes a consideration of the relative costs and benefits of the consequences of the correct decisions and the two types of errors.
What is the mean of a null hypothesis being rejected?
the hypothesis might be correct* * * * *The available evidence suggests that the observations were less likely to have been obtained from random variables that were distributed according to the null hypothesis than under the alternative hypothesis against which the null was tested.
What is the meaning of null hypthesis being rejected?
You may want to prove that a given statistic of a population has a given value. This is the null hypothesis. For this you take a sample from the population and measure the statistic of the sample. If the result has a small probability of being (say p = .025) if the null hypothesis is correct, then the null hypothesis is rejected (for p = .025) in favor of an alternative hypothesis. This can be simply that the null hypothesis is incorrect.
What is Rejected Hypothesis?
It is when you know that your hypothesis is wrong.
What causes a hypothesis to be rejected?
A hypothesis will be rejected if it fails the necessary testing required for it to become a scientific theory.
Is claim would not be rejected at the 0.05 significance level if this sample data were used Assume that a left-tailed hypothesis test would be performed?
98.4
Why can an accepted hypothesis be rejected at a later date?
The answer to the question why is this: It can be rejected at a later date because it is falsifiable in nature if it is a good hypothesis. If you meant to ask HOW it can be rejected, the answer is by way of further experimentation that rules out some or all of the hypothesis as stated.
