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Unformatted text preview: an χ 2 value >or = 3.23 if the hypothesis tested is true, is between 30-50%. To make the final decision as to whether the observed results can be explained by the hypothesis, we must decide on the level of significance to use. The most widely used level is 0.05. Thus, if P<0.05 deviations between observed and expected values are ⇒ significant deviations are too large to be accounted for on the basis of ⇒ chance reject the hypothesis of independent assortment. ⇒ if P>0.05 genes are most probably assorting independently. ⇒ One should always be cautious when using the results of a χ 2 test. A hypothesis is never proved or disproved by a χ 2 test. The test simply evaluates the results of an experiment as acceptable or unacceptable with respect to the hypothesis. When a hypothesis is not rejected, this simply means that the experimental data does not provide a statistically compelling argument against the hypothesis. There is still a chance that one would be accepting a false hypothesis. On the other hand, when rejecting a hypothesis at the accepting a false hypothesis....
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This note was uploaded on 02/23/2010 for the course BIOL 223 taught by Professor Smithanddarwiche during the Spring '10 term at American University of Beirut.
- Spring '10