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What happends if you test a hypothesis multiple times and the data doesn't support your prediction?
Wiki User
∙ 11y ago
That means that your prediction was wrong and that you should include your results in the conclusion and try to explain some of the reasons why your prediction was wrong and if it was wrong because you were doing the experiment wrong.
Wiki User
∙ 11y ago
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Did your data support your hypothesis?
so you have to put in did it help you explain your hypothesis
What happens when the data doesn't support the hypothesis?
Change or abandon your hypothesis.
What does it mean to support or refute a hypothesis?
To support a hypothesis means you agree, and may even give supporting evidence.To refute it means you submit evidence that a hypothesis is incorrect , or you make a cogent and persuasive argument against it.
If the data doesn't support your hypothesis what should you do?
Regroup and propose another theory Propose another hypothesis
Does the data support the hypothesis?
You would need to tell us about the data, the hypothesis and so on for us to be able to answer.
What happen if you test a hypothesis multiple times and the data doesn't support your prediction?
I don't know someone help Me out okay
What happens if you test a hypothesis Multiple time and the data doesn't support your prediction?
I don't know someone help Me out okay
What separate a hypothesis from a prediction?
Both terms are sometimes used interchangeably, but "hypothesis" is more specific. It refers to a certain kind of prediction that is based on extensive research. Usually, a hypothesis will also need to explain itself. After experiments have been conducted, the hypothesis will either be supported or not supported by the results. A prediction does not necessarily require the research and support that a hypothesis needs.
If your experiment does not support your hypothesis you should change your data to give support to the hypothesis. true or false?
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.
True or false If your experiment does not support your hypothesis you should change your data to give support to 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.
How can a experiment support or fail to support a hypothesis?
a hypothesis is given to explain a phenomena which has not been explained till then. it can be supported by an experiment if that experiment gets the other results regarding that particular phenomena in agreement with that being predicted by the hypothesis and if any contradictory fact arises or the result doesnt match the prediction then the hypothesis is again thought upon or totally discarded at times
How is a hypothisis important to science?
Science is based on the principle of falsifiability. It is necessary to develop a hypothesis based on the current understanding. You then make a prediction and design tests or experiments which will either disprove the hypothesis or add support in favour of the scientific theory.
Which describes a reason for making a prediction when doing a controlled experiment?
To determine what sort of data table will be most useful APEX;)
Which of the following describes a reason for making a prediction when doing a controlled experiment?
To indicate what specific results will support a hypothesis to anticipate the observations or measurements that will be made apex
If your prediction is proven incorrect you should leave out all observations that don't support your prediction or simply change your prediction?
both
If your prediction is proven incorrect you should leave out all observations that dont support your prediction or simply change your prediction?
False
If you prediction is proven incorrect you should leave out all observations that don't support your prediction or simply change your prediction?
both
