Question

The table below was created for the number and type of experiments Mendel performed. Each number in the second column represents the number of experiments we would expect Mendel to have had with the deviation in the first column. For example, we would expect Mendel to have had 13 experiments in which the deviation was between 0 and 0.5, and two experiments with deviations between -2.0 and -2.5. Each number in the third column represents the actual number of experiments with the deviation in the first column. For example, Mendel recorded 16 experiments in which the deviation was between 0 and 0.5.$\begin{matrix} \text{An Analysis of Mendel's Data}\\ \text{Deviation} & \text{Expected Number of Experiments with This Deviation} & \text{Actual Number of Experiments with This Deviation}\\ \text{-2 to -2.5} & \text{2} & \text{0}\\ \text{-1.5 to -2} & \text{3} & \text{0}\\ \text{-1 to -1.5} & \text{6} & \text{4}\\ \text{-0.5 to -1} & \text{10} & \text{12}\\ \text{-0 to -0.5} & \text{13} & \text{14}\\ \text{0 to 0.5} & \text{13} & \text{16}\\ \text{0.5 to 1} & \text{10} & \text{20}\\ \text{1 to 1.5} & \text{6} & \text{2}\\ \text{1.5 to 2} & \text{3} & \text{1}\\ \text{2 to 2.5} & \text{2} & \text{0}\\ \end{matrix}$Do you think scientists ever throw out results that were quite different from expected? Why might a scientist be tempted to do this?

Solutions

Verified

Ideally, all data must be considered. Unexpected outcomes provide information on the things that are overlooked during the experiment. Scientists are tempted to throw out unexpected results because they want the data to be uniform as possible. Moreover, when scientists already have expectations of the study, it creates a bias in data analysis.

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