You obtain objective evidence to support it by undertaking experiments designed to test the veracity of the hypothesis.
when results from the experiments repeatedly fail to support the hypothesis.
False- The hypothesis is your prediction of what you expect to happen. If the data does not agree with your hypothesis you simply explain why your hypothesis did not come true and possibly investigate variable which would allow your hypothesis to come true.
To determine if the data support the hypothesis, one must analyze the findings in relation to the predicted outcomes. If the results consistently align with the hypothesis and demonstrate statistically significant correlations or differences, then the data can be considered supportive. Conversely, if the results contradict the hypothesis or show no significant relationship, the data would not support the hypothesis. In summary, the support hinges on the alignment of the data with the expected predictions of the hypothesis.
Propose another hypothesis; the hypothesis is revised and another experiment is conducted.
Hypothesis.
An experiment might not support a hypothesis even if the hypothesis is correct because if the conclusion
If your hypothesis is totally incorrect then it is quite likely that the data will not support it.
when results from the experiments repeatedly fail to support the hypothesis.
Amend or discard the hypothesis
Discard or change the hypothesis.
Amend or discard the hypothesis
come up with new hypothesis
Change or abandon your hypothesis.
so you have to put in did it help you explain your hypothesis
Revise or discard your hypothesis.
If your data does not support your hypothesis, it means that there is not enough evidence to conclude that your hypothesis is true. In such cases, you may need to reconsider your hypothesis, collect additional data, or revise your experimental approach. It is important to acknowledge and learn from results that do not support your initial hypothesis in order to refine your research and understanding.
False- The hypothesis is your prediction of what you expect to happen. If the data does not agree with your hypothesis you simply explain why your hypothesis did not come true and possibly investigate variable which would allow your hypothesis to come true.