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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.
Riley Wolf
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Can you accept and reject the null Hypothesis Why or why not?
Some people say you can either accept the null hypothesis or reject it. However, there are statisticians that insist you can either reject it or fail to reject it, but you can't accept it because then you're saying it's true. If you fail to reject it, you're only claiming that the data wasn't strong enough to convince you to choose the alternative hypothesis over the null hypothesis.
Is scientific investigation expected to be certain?
Absolutely not. Hypothesis testing will never support a hypothesis, only fail to reject it.
Difference between acceptance and rejection region?
Some researchers say that a hypothesis test can have one of two outcomes: you accept the null hypothesis or you reject the null hypothesis. Many statisticians, however, take issue with the notion of "accepting the null hypothesis." Instead, they say: you reject the null hypothesis or you fail to reject the null hypothesis. Why the distinction between "acceptance" and "failure to reject?" Acceptance implies that the null hypothesis is true. Failure to reject implies that the data are not sufficiently persuasive for us to prefer the alternative hypothesis over the null hypothesis.
In what cases one can state the null hypotheses true?
There is no truth in science. Truth is only meaningful in math, philosophy, religion and logic. A hypothesis can never be true. You either accept or reject a hypothesis. You accept the null hypothesis if you fail to reject it.
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)
Type 1 error and type 2 error?
In statistics: type 1 error is when you reject the null hypothesis but it is actually true. Type 2 is when you fail to reject the null hypothesis but it is actually false. Statistical DecisionTrue State of the Null HypothesisH0 TrueH0 FalseReject H0Type I errorCorrectDo not Reject H0CorrectType II error
What is the probability of making a Type II error if the null hypothesis is actually true?
zero. We have a sample from which a statistic is calculated and will challenge our held belief or "status quo" or null hypothesis. Now you present a case where the null hypothesis is true, so the only possible error we could make is to reject the null hypothesis- a type I error. Hypothesis testing generally sets a criteria for the test statistic to reject Ho or fail to reject Ho, so both type 1 and 2 errors are possible.
Reject Ho or do not reject H0?
Rejecting or Failing to reject the Null Hypothesis (Ho) depends of the P-Value. Generally, the P-value (probability( Observation | Ho ) ) is around .05, thus minimizing the Type 1 error rate. If the P-value < Alpha , you would reject the Ho, and instead believe the Ha (Alternative Hypothesis), and if the P-value > Alpha, you would Fail to reject the Ho because there is not enough evidence to believe the Ha.
Is it true that biologists discover problems by observing the world around them?
Yes. Observation leads to the identification of a phenomenon or problem, and scientists would then try to formulate a hypothesis to explain the phenomenon or solve the problem. Then the scientist would devise experiments to test the hypothesis. Should the hypothesis fail, the scientist can formulate the new hypothesis. If the hypothesis holds, more experiments must be done to verify it. Only when a hypothesis is tested by many experiments by many people can it be called a theory.
Does the qualitative observations have to be related to what your hypothesis is?
Original Answer:I would tie it back in and show whether it helped to reject/fail to reject your hypothesis.Different Answer:A hypothesis (Informal definition), is basically a question based on anticipated results. The experiment is created to try to prove or disprove that hypothesis. When conducting an experiment, only three results can occur. That is the hypothesis is confirmed, the hypothesis is incorrect, or the results were inconclusive. Of the three possible answer, the third is the most maddening as it could indicate that something is wrong with your experiment.Sometimes the most fascinating discoveries come from observations that are either inconclusive, or disprove a hypothesis.
Why is hypothesis is discarded as a valid hypothesis?
when results from the experiments repeatedly fail to support the hypothesis.
If your p-value is .7712 do you reject the hypothesis at 10 percent level of statistical significance If so is there a relationship in the test?
u reject if P-Value is < significance level. so since .7712 > .10 u fail to reject! remember this: "if P is high Ho will fly nd if P is low Ho must go" Help by USman Noor
