They still chart the data. Then they go back to their hypothesis and change it/fix it up a bit. After they have a new (but one that still relates to their old hypothesis) hypothesis, they re-do their experiment.
Ex) "I believe girls have better quiz scores than boys because they have better short term memory"
If your hypothesis is incorrect (ie: the boys do better) then you need to change the hypothesis and test it again--> "I believe girls have better quiz scores because they have better long term memory".
Scientists make observations to help them make a hypothesis or collect data during an experiment.
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.
Scientists make observations.
Yes. That's the whole point of experiments. If you reckon something will happen, but it doesn't then you have to change your hypothesis. Or your experimental method. Which is why scientists self regulate by publishing claims that other scientists then try to recreate or disprove. Or even just criticise your methods.If your data doesn't support your hypothesis, but you doggedly stick to it anyway, you've created religion.
The scientists might Rethink there Hypothesis because when they collect more data they would know more about what they are doing so they would rethink there hypothesis
Discard or change the hypothesis
I no
If your hypothesis is totally incorrect then it is quite likely that the data will not support it.
Amend or discard the hypothesis
Amend or discard the hypothesis
When scientists evaluate whether their data confirmed or rejected the hypothesis, it is referred to as hypothesis testing. This process involves analyzing the results of experiments or observations to determine if they support or contradict the initial hypothesis formulated before the research. If the data supports the hypothesis, it may lead to further investigation; if it rejects the hypothesis, researchers may revise their understanding or formulate new hypotheses.
Ideally that is how it goes, yes.
Reevaluate your hypothesis, or reject the hypothesis. You should also recheck your data.
Discard or change the hypothesis.
Scientists make observations to help them make a hypothesis or collect data during an experiment.
Ask a question. Collect information. Form a hypothesis. Perform an experiment. Collect data and analyze data. Interpret data. If data support your hypothesis, draw conclusions. If they don't, form a new hypothesis and re-do the process. Publish your results. Repeat experiments.
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.