Dr. Ara B. Dopsis and Dr. C. Ellie Gans are performing g...

Question

Dr. Ara B. Dopsis and Dr. C. Ellie Gans are performing genetic crosses on daisy plants. They self-fertilize a blue-flowered daisy and grow 100 progeny plants that consist of 55 blue-flowered plants, 22 purple-flowered plants, and 23 white-flowered plants. Dr. Dopsis believes this is the result of segregation of two alleles at one locus and that the progeny ratio is 1:2:1. Dr. Gans thinks the progeny phenotypes are the result of two epistatic genes and that the ratio is 9:3:4.
The two scientists ask you to resolve their conflict by performing chi-square analysis on the data for both proposed genetic mechanisms. For each proposed mechanism, fill in the values requested on the form the researchers have provided for your analysis.

Use the form below to calculate chi square for the 9:3:4 hypothesis of Dr. Gans. <>

Accepted Answer

Hi, everyone. Let's take a look at this practice problem together. A chi square test is used to examine a genetic cross with a total of 200 offspring. What may be concluded if the estimated chi square value is 5.89 and the P value is 0.15. The answer options are a, at the 5% level. There is a large deviation from the expected ratios B at the 1% level. There is a large deviation from the expected ratios. C there is no significant deviation from the expected ratios and D for a conclusion, more details are required. So recall what the purpose of a chi square test is a chi square test checks. If observed outcome is close enough to the expected outcome, using the chi square value, you can determine what your P value is and recall that the P value stands for probability value. In this question, the P value is 0.015. And if we write that as a percentage, that is 1.5%. But what does the P value tell us about the problem? The P value helps us to choose whether we accept or reject the null hypothesis and recall that the null hypothesis states that there is no difference between the expected and observed outcomes. So when A P value is greater than 0.05 or greater than 5%,, we accept the null hypothesis, meaning we accept that there is no difference between the outcomes. When A P value is less than 0.05, we reject the null hypothesis. A P value less than 0.05 is considered statistically significant. So when we reject the no hypothesis, it means that we're seeing there is a difference between the observed and expected outcomes. Now, having reviewed all of that, we can eliminate option C, we've established that there is a difference between the, the expected ratios. Now, option B seats at the 1% level or A P value of 0.01, there is a large difference. We cannot reject the null hypothesis at the 1% level because R P value is 1.5% which is not less than 1%. So option B is also incorrect. However, we can state that at the 5% level, there is a difference and we reject the null hypothesis. Our P value of 1.5% is less than the 5% level. There is enough data and information to determine that option A is the correct answer. So we can eliminate option D, the correct answer is option a, at the 5% level, there is a large deviation from the expected ratios. All right, everyone. I hope you found this helpful and I'll see you soon for the next practice problem.

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