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In a scientific experiment, the following design elements are vital:
1. A falsifiable hypothesis - the question you are trying to answer (the hypothesis) must have a definitive "true" result and a definitive "false" result. For instance, a hypothesis may read "Drug X results in longer remission periods for cancer patients." The null hypothesis to this (the "hypothesis is false" result) is "Drug X does not result in longer remission periods for cancer patients."
2. The study must be statistically valid. When designing an experiment, you need to have enough data to conclude a "true hypothesis" result is real and not just because you got lucky and by chance found data to support a "true hypothesis" result. This will dictate the number of subjects studied as well as a general time frame for the study.
3. The data collection methods must be validated. If you are testing for cancer remission in Breast cancer patients, you would use lymph node biopsies or mammograms to look for evidence of cancer resurgence; you would not use a blood chemistry test as the test wouldn't find the cancer even if it was there.
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