when results from the experiments repeatedly fail to support the hypothesis.
The results can support their hypothesis by comparing the results, or setting them out in a table or graph. Conclusions can also be written to simplify the process.
Then explain why it was wrong
draw conclusions
draw conclusions
when results from the experiments repeatedly fail to support the hypothesis.
The results can support their hypothesis by comparing the results, or setting them out in a table or graph. Conclusions can also be written to simplify the process.
The results of his experiments did not support his hypothesis.
Then explain why it was wrong
draw conclusions
draw conclusions
draw conclusions
draw conclusions
draw conclusions
end the experiment and throw away the datarepeat the experiment until the hypothesis is supportedchange the hypothesisargue that the results were
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.
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.