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R = Red eyes r = White eyes Rr X Rr Used to confirm whether a set of data follows a specific probability distribution. IE…how likely is it that deviations from expected results are due solely to chance? Uses a sample to test whether a frequency distribution fits the predicted distribution Example: Used to answer the following ques ◦ Can we conclude that the 3:1 ratio is true based on the observation of _____(#) of fruit flies. The chi-square test basically compares the observed (O) and the expected (E) frequencies to determine whether there is a statistically significant difference Observed frequency is the # of flies seen for each phenotype Expected frequency is the # of flies expected for each penotype Example: if cross is a monohybrid one, you would expect a 3:1 phenotypic ratio. Therefore, if you observed 100 flies, 75 of them should have the dominant phenotype, while 25 of them should have the recessive phenotype Use the following equation: Use an already constructed table to see where your Chi-square value falls. Which row you look in depends on the number of degrees of freedom. ◦ The number of degrees of freedom is equal to the number of phenotypic categories minus 1. Monohybrid… Dihybrid… Sex-linked… 2 ways to analyze ◦ if X2 is less than number in box, good fit… ◦ If P value is greater than .05, than good fit Means your data did not happen by chance. A cross between two fruit flies that are heterozygous for red eyes produced the following offspring: ◦ 260 Red eyes ◦ 178 White eyes Calculate X2 for this experiment