yes
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.
Yes.
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.
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.
A hypothesis will be rejected if it fails the necessary testing required for it to become a scientific theory.
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.
The hypothesis test.
no. you need to have solid proof that it exist.. else it will be rejected.
To determine whether Fleming's hypothesis should be supported or rejected based on an experiment, one would need to analyze the results of the experiment in relation to the hypothesis. If the data from the experiment aligns with the predictions made by Fleming's hypothesis, then it should be supported. However, if the results contradict the hypothesis, it may need to be rejected or revised.
H1 hypothesis is rejected when the p-value associated with the test statistic is less than the significance level (usually 0.05) chosen for the hypothesis test. This indicates that the data provides enough evidence to reject the alternative hypothesis in favor of the null hypothesis.
yes
It tells us that H1,H0 (alternative )hypothesis is selected
no
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.
the reason why a rejected hypothesis can still be of value to a scientist is because that secific hyothesis may not work for your experiment but it could work for a different experiment/theory
When we've proven that the hypothesis is false !