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Chi-Square Test. We have discussed predicting allele, genotype, and phenotype frequency using the Hardy-Weinberg equation But how much of a “deviation” is actually significant? One way is to use a chi-square ( χ 2 ) test
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We have discussed predicting allele, genotype, and phenotype frequency using the Hardy-Weinberg equation • But how much of a “deviation” is actually significant? • One way is to use a chi-square (χ2) test • Essentially, if data deviates from predicted values too much, the χ2 statistic will exceed a certain value
χ2 = • When this is computed, it is compared to established χ2 which have been calculated based solely on chance • The values are based on the degrees of freedom • If it is exceeded, we reject the hypothesis
Example The number of expected flowers of red, pink, and white phenotypes is listed below, along with the observed values. We hypothesize that the observed values are within statistical norms. Do a chi-square test to confirm or deny the hypothesis
Answer • Use the equation: χ2 = = = 0.875 The critical value is 5.991, so the hypothesis is not rejected.