Question

The Esatina salamanders (Ensatina eschscholtzii), shown above, live along the West Coast of North America from Vancouver to BQ1a. What is the null hypothesis for this study? Q1b. What is the alternative hypothesis for this study? As part of your summQ2c. Use the Hardy-Weinberg equation to calculate the expected genotypic frequency for this population. + And then complete t

Q2f. Based on your Chi-Square value do you accept or reject your null hypothesis? Do you conclude that evolution is occurring

I need help with questions 1 through 2, thank you!

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Answer #1

You have asked two questions here. As per Chegg Q&A Guidelines, I am answering only Question 1.

The salamander is known to exhibit a color difference that is controlled by a single gene called EM gene. The gene has 2 alleles B and R. These alleles are codominant and hence in a heterozygote both the alleles are expressed codominantly. The RR produces red coloration, BB produces a blotchy phenotype dominated by black, brown and orange coloration. The RB produces red patches on the blotchy skin.

The research group studying this population is trying to understand if the population is experiencing any evolutionary force. The evolution arises because of various forces like mutation, natural selection, non-random mating, genetic drift etc. If the evolution were absent, i.e. all of these forces were absent, the population would be said to be in a Hardy-Weinberg equilibrium i.e. allele and genotype frequencies would be conserved across generations without any driving force to select specific variants.

Thus to validate this, we can devise an alternate hypothesis which states that the Hardy-Weinberg equilibrium is violated and hence the null hypothesis will be a negative of this which means that the Hardy-Weinberg equilibrium is maintained.

Thus, the research group can devise an experiment that either validates or rejects the null hypothesis. Based on the data from the experiment an appropriate statistical analysis can be performed which can then be used to state with a certain probability that the null hypothesis is refuted. If it is refuted, they have validated the alternate hypothesis. If the null hypothesis is however validated by the data, the null hypothesis has to be accepted.

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