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Biology
OpenStudy (anonymous):

Scientist want to set up an experimental procedure to examine the following. In an ecosystem, all producers are killed through a loss of fertility of the soil or through toxic contamination. Why would this issue be difficult to quantitate? In the scientific method, the validity of scientific claims is settled by referring to observations of phenomena. Scientific researchers repeat steps in an orderly fashion to collect data. Based upon data, it may be necessary to test the hypotheses. Why is it important not to assume outcome?

OpenStudy (anonymous):

if you presuppose specific results, you may inadvertently influence the results and fall into the trap of the "confirmation bias"

OpenStudy (anonymous):

formulating a hypothesis is very similar to assume the outcome! A scientist formulates a hypothesis based on his observation. To prove that whether his observation outcomes i.e the hypothesis is valid or not a series of experiments are carried out. The experiments results in data. After the analysis of data, it is concluded whether the assumed outcome or the hypothesis formulated is right of wrong. So it is important to assume outcome and to prove it. And very true written by DERWAICHE not to bias with the experiment. A good knowledge of design of experiments will work out to stop you biasing :)

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