Classification systems are all different. They vary is specificity.
Answer:
R (capital letter) is the dominant allele so the phenotype is the same
Explanation:
As in printing a book, if there is a slight defect in the mutation, it will be copied to every other mutation, just like a grammatical error in a book.
Imagine you are surveying a population of a mountain range where the inhabitants live in the valleys with no inhabitants on the large mountains between. If your sample area is the valleys, and you use this to estimate the population across the entire mountain range, <u>you overestimate the actual population size</u>
<u />
Explanation:
- An estimate that turns out to be incorrect will be an overestimate if the estimate exceeded the actual result, and an underestimate if the estimate fell short of the actual result.
- The mean of the sampling distribution of a statistic is sometimes referred to as the expected value of the statistic. Therefore the sample mean is an unbiased estimate of μ.
- Any given sample mean may underestimate or overestimate μ, but there is no systematic tendency for sample means to either under or overestimate μ.
- Bias is the tendency of a statistic to overestimate or underestimate a parameter. Bias can seep into your results for a slew of reasons including sampling or measurement errors, or unrepresentative samples
Answer:
Incomplete dominance is when the phenotypes of the two parents blend together to create a new phenotype for their offspring.
Explanation:
a white flower and a red flower producing pink flowers. Codominance is when the two parent phenotypes are expressed together in the offspring.
