What happens if you Cannot reject the null hypothesis?

The null hypothesis will never be proven true; you just fail to reject it.
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What happens if the null hypothesis is not rejected?

Failing to reject the null indicates that our sample did not provide sufficient evidence to conclude that the effect exists. However, at the same time, that lack of evidence doesn't prove that the effect does not exist.
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When a null hypothesis Cannot be rejected we conclude that?

If the null hypothesis is not rejected, it means that there is no enough evidence is there to reject that. Hence we cannot reject the null hypothesis. In other words, we can say there is enough evidence to reject the alternate hypothesis.
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What happens when you incorrectly reject the null hypothesis?

A type I error (false-positive) occurs if an investigator rejects a null hypothesis that is actually true in the population; a type II error (false-negative) occurs if the investigator fails to reject a null hypothesis that is actually false in the population.
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What p-value fails to reject the null hypothesis?

A p-value less than 0.05 is typically considered to be statistically significant, in which case the null hypothesis should be rejected. A p-value greater than 0.05 means that deviation from the null hypothesis is not statistically significant, and the null hypothesis is not rejected.
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Why do we say Fail to Reject the Null Hypothesis? Why can't I accept the Null Hypothesis?

What does failure to reject the null hypothesis indicate?

Failing to reject a null hypothesis means there is no sufficient evidence for the expected or the observed effect. Today, if scientists had accepted null hypotheses, the discovery of plant viruses or the rediscovery of many extinct species would not have been possible.
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Does fail to reject mean accept?

If the P-value is greater than the significance level, we say we “fail to reject” the null hypothesis. We never say that we “accept” the null hypothesis. We just say that we don't have enough evidence to reject it. This is equivalent to saying we don't have enough evidence to support the alternative hypothesis.
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What is the failure to reject a null hypothesis that is actually false?

A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false.
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How do you know if you should reject the null hypothesis?

You can reject a null hypothesis when a p-value is less than or equal to your significance level. The p-value represents the measure of the probability that a certain event would have occurred by random chance. You can calculate p-values based on your data by using the assumption that the null hypothesis is true.
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Why do many statisticians prefer the use of fail to reject the null hypothesis?

For example, when we accept the null hypothesis that claims the population mean is $2,000, we have not usually ruled out the possibility that this mean is $2,001 or $1,999. For this reason, some statisticians prefer to say that we “fail to reject” the null hypothesis rather than simply say that we “accept” it.
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What is the conclusion if you fail to reject the null hypothesis?

Option 2) Fail to reject the null hypothesis (H0). This means that you do NOT have enough evidence to support the alternative claim (H1). Another way to think about hypothesis testing is to compare it to the US justice system. A defendant is innocent until proven guilty (Null hypothesis—innocent).
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Why is the null hypothesis always rejected?

We reject the null hypothesis when the data provide strong enough evidence to conclude that it is likely incorrect. This often occurs when the p-value (probability of observing the data given the null hypothesis is true) is below a predetermined significance level.
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Which is possible if you fail to reject a null hypothesis based on a t-test?

Instead, we establish a null hypothesis and look for sample-based evidence to try and reject the null. If we can't reject the null, we do not accept the alternative, we reserve judgement and state that there is insufficient evidence to conclude that the alternative is true.
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How do you write a Failed to reject the null hypothesis?

Here you could say “the null hypothesis was not rejected” or “failed to reject the null hypothesis” because you did not find evidence against the null hypothesis.
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What is the decision rule for rejecting the null hypothesis?

Rejecting or failing to reject the null hypothesis

If our statistical analysis shows that the significance level is below the cut-off value we have set (e.g., either 0.05 or 0.01), we reject the null hypothesis and accept the alternative hypothesis.
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Why can't we prove the null hypothesis?

The reason for this, as I have said, harkens back to David Hume and the philosophy of science, which asserts that we cannot prove the nonexistence of something (unless, of course, it violates one of the laws of nature, such as the notions of perpetual motion machines, travel that is faster than light, or politicians ...
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Is it okay to not reject the null hypothesis?

Failing to reject a null hypothesis is evidence that the null hypothesis is true, but it might not be particularly good evidence, and it certainly doesn't prove the null hypothesis.
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Does rejecting the null mean the alternative is true?

If you reject the null hypothesis, you can say that the alternative hypothesis is supported.
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Why reject null hypothesis when p-value is small?

A small P-value signifies that the evidence in favour of the null hypothesis is weak and that the likelihood of the observed differences due to chance is so small that the null hypothesis is unlikely to be true.
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When the null hypothesis is not rejected, it is?

Answer and Explanation:

Whenever the null hypothesis is not rejected which means the null hypothesis is accepted.
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What occurs when you incorrectly fail to reject the null hypothesis?

A Type II error occurs when you fail to reject the null hypothesis when it is actually false. If you have rejected the null hypothesis, then by definition, you cannot make a Type II error because you have concluded that there is enough evidence to support the alternative hypothesis.
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What is failing to reject the null hypothesis when it falls?

A type II error is a statistical term used within the context of hypothesis testing that describes the error that occurs when one fails to reject a null hypothesis that is actually false. A type II error produces a false negative, also known as an error of omission.
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What happens if not enough evidence to reject the null hypothesis?

It is also called the research hypothesis. The goal of hypothesis testing is to see if there is enough evidence against the null hypothesis. In other words, to see if there is enough evidence to reject the null hypothesis. If there is not enough evidence, then we fail to reject the null hypothesis.
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How to know when to reject a null hypothesis?

Reject the null hypothesis when the p-value is less than or equal to your significance level. Your sample data favor the alternative hypothesis, which suggests that the effect exists in the population. For a mnemonic device, remember—when the p-value is low, the null must go!
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Do you reject or fail to reject at the 0.05 level of significance?

Similarly, if the value of the significance level is set to 0.05 and the calculated significance probability value is 0.03, the set null hypothesis will be rejected, but if the value of the significance level is set to 0.01, the null hypothesis cannot be rejected.
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