Final answer:
To determine if there is a significant difference in genetic mutation prevalence between two species of fishes, biologists perform a hypothesis test. They compare two sample proportions and use a significance level to interpret the p-value from the test. If the p-value is lower than the significance level, the null hypothesis is rejected, suggesting a significant difference in mutation rates.
Step-by-step explanation:
To ascertain if there is a significant difference in the prevalence of a genetic mutation across two species of fishes, a hypothesis test comparing two proportions is utilized. In the provided scenario, 10.1% of a sample of 120 fishes from species I and 18.2% of a sample of 198 fishes from species II exhibit the mutation. Following data collection, one would typically establish a null hypothesis that there is no difference between the mutation rates in the two populations, and an alternative hypothesis that there is a difference.
A hypothesis test applies a significance level (α) to determine the probability threshold under which the null hypothesis would be rejected in favor of the alternative. Commonly used significance levels include 0.05 (5%) for moderate confidence and 0.01 (1%) for high confidence in the results. The research must employ a statistical method such as the Z-test for comparing proportions, and if the resulting p-value is less than the selected significance level, one would reject the null hypothesis, indicating that there is significant evidence of a difference in mutation prevalence between the two species.