with the null hypothesis, then do not reject the ..
Test the null hypothesis that the new ball does not improve a bowler's average at the 5% level of significance.
What does it mean to have a null hypothesis accepted?
The pvalue is p = 0.236. This is not below the .05 standard, so we do not reject the null hypothesis. Thus it is possible that the true value of the population mean is 72. The 95% confidence interval suggests the mean could be anywhere between 67.78 and 73.06.
We are now ready to accept or reject the null hypothesis. If the t_{calc} > t_{tab}, we reject the null hypothesis. In our case, t_{calc}=5.88 > t_{tab}=2.45, so we reject the null hypothesis, and say that our sample mean is indeed larger than the accepted limit, and not due to random chance, so we can say that the soil is indeed contaminated.
What does it mean to have a null hypothesis accepted
Compare your answer from step 5 with the α value given in the question. Support or reject the null hypothesis? If step 5 is less than α, reject the null hypothesis, otherwise do not reject it. In this case, .582 (5.82%) is not less than our α, so we do not reject the null hypothesis.
Compare your answer from step 4 with the α value given in the question. Should you support or reject the null hypothesis?
If step 7 is less than or equal to α, reject the null hypothesis, otherwise do not reject it.
This does not mean that the null hypothesis is ..
A small pvalue favors the alternative hypothesis. A small pvalue means the observed data would not be very likely to occur if we believe the null hypothesis is true. So we believe in our data and disbelieve the null hypothesis. An easy (hopefully!) way to grasp this is to consider the situation where a professor states that you are just a 70% student. You doubt this statement and want to show that you are better that a 70% student. If you took a random sample of 10 of your previous exams and calculated the mean percentage of these 10 tests, which mean would be less likely to occur if in fact you were a 70% student (the null hypothesis): a sample mean of 72% or one of 90%? Obviously the 90% would be less likely and therefore would have a small probability (i.e. pvalue).
A small pvalue favors the alternative hypothesis. A small pvalue means the observed data would not be very likely to occur if we believe the null hypothesis is true. So we believe in our data and disbelieve the null hypothesis. An easy (hopefully!) way to grasp this is to consider the situation where a professor states that you are just a 70% student. You doubt this statement and want to show that you are better that a 70% student. If you took a random sample of 10 of your previous exams and calculated the mean percentage of these 10 tests, which mean would be less likely to occur if in fact you were a 70% student (the null hypothesis): a sample mean of 72% or one of 90%? Obviously the 90% would be less likely and therefore would have a small probability (i.e. pvalue).
that not rejecting the null doesn't mean ..

to reject a null hypothesis it does not mean that ..
what does it mean to accept a null hypothesis?  Yahoo …

do not reject the null hypothesis
Do you reject or not reject the null hypothesis Meaning of effect ..

What does hypothesis mean reject  scholarly search
What does hypothesis mean reject ..
Failure to reject the null hypothesis does NOT MEAN ..
When the data indicate that one cannot reject the null hypothesis, does it mean that one can accept the null hypothesis? For example, when the pvalue computed from the data is 0.12, one fails to reject the null hypothesis at = 0.05. Can we say that the data support the null hypothesis?
What does it mean when null hypothesis accepted
If the test statistic is less extreme than the critical value, do not reject the null hypothesis. In our example concerning the mean grade point average, suppose we take a random sample of n = 15 students majoring in mathematics.
What does null hypothesis mean in statistics  life …
The pvalue is p = 0.236. This is not below the .05 standard, so we do not reject the null hypothesis. Thus it is possible that the true value of the population mean is 72. The 95% confidence interval suggests the mean could be anywhere between 67.78 and 73.06.
interval does not contain the null hypothesis ..
If your P value is less than the chosen significance level then you reject the null hypothesis i.e. accept that your sample gives reasonable evidence to support the alternative hypothesis. It does NOT imply a "meaningful" or "important" difference; that is for you to decide when considering the realworld relevance of your result.
What does it mean when you reject the null hypothesis
Another way your data can fool you is when you don't reject the null hypothesis, even though it's not true. If the true proportion of female chicks is 51%, the null hypothesis of a 50% proportion is not true, but you're unlikely to get a significant difference from the null hypothesis unless you have a huge sample size. Failing to reject the null hypothesis, even though it's not true, is a "false negative" or "Type II error." This is why we never say that our data shows the null hypothesis to be true; all we can say is that we haven't rejected the null hypothesis.
Why Say "Fail to Reject" in a Hypothesis Test?  …
After you do a statistical test, you are either going to reject or accept the null hypothesis. Rejecting the null hypothesis means that you conclude that the null hypothesis is not true; in our chicken sex example, you would conclude that the true proportion of male chicks, if you gave chocolate to an infinite number of chicken mothers, would be less than 50%.