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When you reject the Null Hypothesis that means that the Null Hypothesis cannot be correct?
Wiki User
∙ 13y ago
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.
Wiki User
∙ 13y ago
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What does it mean when a scientist fails to reject a hypothesis?
It means that the experiment is consistent with the hypothesis. It adds to the credibility of the hypothesis.
What does state whether your hypothesis was correct or not mean?
It means tell them how your hypothesis was right or not.
What does F equals 1 mean in regards to ANOVA?
F is the test statistic and H0 is the means are equal. A small test statistic such as 1 would mean you would fail to reject the null hypothesis that the means are equal.
What is the null hypothesis of a one-way ANOVA What is the alternate hypothesis?
Null hypothesis of a one-way ANOVA is that the means are equal. Alternate hypothesis a one-way ANOVA is that at least one of the means are different.
If Relationship between statistical significance and rejectingaccepting an hypothesis?
I believe you asked for the relationship between "statistical significance" and hypothesis testing. In hypothesis testing, we state the null and alternative hypothesis, then in the traditional method, we use a test statistic and a significance level, alpha, to decide whether to accept or reject the null hypothesis in favor of the alternative. If our test statistic falls in the reject area (critical region) of the sampling distribution, then we reject the null hypothesis. If not, we accept it. There is the second method, the p-value method, which is similar in that an alpha value has to be selected. Now, the term "statistical significant result", as used in statistics, means a result (mean value, proportion or variance) from a random sample was not likely to be produced by chance. When we reject the null hypothesis in favor of the alternative, we indicate our data supports an alternative hypothesis, so our result is "statistically significant." Let me use an example. Generally workers arrive at work a few minutes more or less than required. Our null hypothesis will be an average lateness of 5 minutes, and our alternative hypothesis will be greater than 5 minutes. Our data shows an average lateness of 12 minutes, and our test statistic, taking into account the variance and sample size, and our chosen alpha level, concludes that we reject the null hypothesis, so the 12 minute average is a significantly significant result because it supported rejection of the hypothesis. The problem is that significant, in common usage, means important or meaningful, not trivial or spurious. The sample used to calculate late time may have been not randomly chosen, more people come to work late in bad weather. The sample is to make inferences on the a general population, but there is no static population in this case, as a company hires and fires employees. So, since our data is flawed, so can our conclusions. Used as a technical term in statistics, statistical significance has a much more rigorous and restricted meaning, which can lead to confusion. See: http://en.wikipedia.org/wiki/Statistical_significance
What does it mean when a scientist fails to reject a hypothesis?
It means that the experiment is consistent with the hypothesis. It adds to the credibility of the hypothesis.
What does it mean if a scientist can't reject a hypothesis?
It means that she or he has to accept that the existing hypothesis appears to be true.
Can you not reject null hypothesis?
you do not need to reject a null hypothesis. If you don not that means "we retain the null hypothesis." we retain the null hypothesis when the p-value is large but you have to compare the p-values with alpha levels of .01,.1, and .05 (most common alpha levels). If p-value is above alpha levels then we fail to reject the null hypothesis. retaining the null hypothesis means that we have evidence that something is going to occur (depending on the question)
What dose it mean if a scientist fails to reject a 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.
What dose it mean if a scientist fail to reject a 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.
What dose it mean if a scientists fails to reject a 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.
What does state whether your hypothesis was correct or not mean?
It means tell them how your hypothesis was right or not.
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.
When should you accept a null hypothesis?
The null hypothesis cannot be accepted. Statistical tests only check whether differences in means are probably due to chance differences in sampling (the reason variance is so important). So if the p-value obtained by the data is larger than the significance level against which you are testing, we only fail to reject the null. If the p-value is lower than the significance level, the null hypothesis is rejected in favor of the alternative hypothesis.
Can a hypothesis become wrong?
Yes. The term means best guess. Data can prove that is not correct.
If a null hypothesis is not rejected at the 0.10 level can it may be rejected at the 0.05 level?
No, because 0.05 is a stricter alpha level than 0.10. 0.05 means you are allowing for 5% error, and 0.10 means 10% error. Therefore if you can not reject it at 0.10 then you can not reject it at either 0.05 or 0.01.
Can a falsifiable hypothesis be tested?
A falsifiable hypothesis is a hypothesis that must be set up so that it is possible to be proven false.
