That depends on the result of the experiment. The experiment is a way to test a hypothesis, and it's completely fine if the experiment disproves the hypothesis. Ideally, though, the experiment will support the hypothesis.
The experiment that you will design is done to test the hypothesis.
After forming a hypothesis, the next steps in the scientific method are to design and conduct an experiment to test the hypothesis, collect and analyze data from the experiment, and finally draw conclusions based on the results. If the results support the hypothesis, it may be considered valid; if not, the hypothesis may need to be revised or rejected. Additionally, the findings should be communicated to others for further validation and exploration.
Hypothesis is examined very closely to see what it predicts, and the predictions are then rigorously tested. If the predictions are not supported by the results of experiments, the hypothesis is rejected but if they are confirmed, the hypothesis is supported.
An experiment is performed to generate more data. If the data proves to not support the hypothesis the experiment was still useful. You could reproduce your experiment to see if it is performing the way it should. After you have confirmed the experiment is performing correctly you then could devise another experiment to further test your hypothesis or accept the result and revise your hypothesis.
They should try again. Then check very carefully and see if they did the experiment correctly. They may have to change their hypothesis.
The scientist or student scientist should review the results. Conclusions should be drawn based on the results. Then, the hypothesis is reviewed to make sure the results confirm the hypothesis; if not, revise the hypothesis and rerun the experiment.
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.
That depends on the result of the experiment. The experiment is a way to test a hypothesis, and it's completely fine if the experiment disproves the hypothesis. Ideally, though, the experiment will support the hypothesis.
The experiment that you will design is done to test the hypothesis.
After analyzing test results, the experimenter should draw conclusions based on the data, determine whether the results support the hypothesis, and consider the implications of the findings. It is important to communicate the results clearly and accurately in a report or presentation to share the outcomes of the experiment with others.
After forming a hypothesis, the next steps in the scientific method are to design and conduct an experiment to test the hypothesis, collect and analyze data from the experiment, and finally draw conclusions based on the results. If the results support the hypothesis, it may be considered valid; if not, the hypothesis may need to be revised or rejected. Additionally, the findings should be communicated to others for further validation and exploration.
Hypothesis is examined very closely to see what it predicts, and the predictions are then rigorously tested. If the predictions are not supported by the results of experiments, the hypothesis is rejected but if they are confirmed, the hypothesis is supported.
An experiment is performed to generate more data. If the data proves to not support the hypothesis the experiment was still useful. You could reproduce your experiment to see if it is performing the way it should. After you have confirmed the experiment is performing correctly you then could devise another experiment to further test your hypothesis or accept the result and revise your hypothesis.
The conclusion is based on the data that you got from the experiment (experimental results). To write a conclusion you should tell if your hypothesis was correct or incorrect then support your answer from your data. You should always use Quantitative details from the data.
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.
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.