When testing these results using a Chi-Square test, you rejected the null hypothesis that this population is in Hardy-Weinberg Equilibrium with p<0.001. You are interested in understanding what evolutionary mechanism may be most likely responsible for the significant deviations of observed genotype frequencies from Hardy-Weinberg proportions. First, let's describe the pattern of genotypes in relationship to expected genotype frequencies under Hardy-Weinberg. Observed frequency of AA genotype Observed frequency of Aa genotype Observed frequency of aa genotype
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In order to determine whether a population is in Hardy-Weinberg equilibrium, you use a Chi square analysis and find X² = 0.103, d.f. = 2, p=0.95 There is evidence that the population is out of Hardy-Weinberg Equilibrium The population is consistent with Hardy-Weinberg Equilibrium More than two populations are required to test for Hardy-Weinberg Equilibrium The Chi square test cannot be used for this purpose
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Imagine a team of students studying the distribution of genotypes in a population using chi-square analysis. They have calculated the difference between the observed and expected genotype frequencies for a given locus, giving rise to a chi-square statistic of 18.6. If the critical value is 5.99 at 2 degrees of freedom and p value of 0.05, what decision should this team make with respect to their null hypothesis? A. Accept the null hypothesis, and conclude that the population is not evolving. B. Reject the null hypothesis, and conclude that the frequencies are not in Hardy Weinberg equilibrium. C. Reject the experiment as flawed, since the alternate hypothesis was not tested. D. Accept the null hypothesis, since the chi-square value is greater than the critical value.
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To test $H_{0}: \mu=80$ versus $H_{1}: \mu<80,$ a random sample of size $n=22$ is obtained from a population that is known to be normally distributed with $\sigma=11$ (a) If the sample mean is determined to be $\bar{x}=76.9$ compute the test statistic. (b) If the researcher decides to test this hypothesis at the $\alpha=0.02$ level of significance, determine the critical value. (c) Draw a normal curve that depicts the critical region. (d) Will the researcher reject the null hypothesis? Why?
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