1. (Problem 2) Why is the relation between genotype and phenotype frequently com

Question

1. (Problem 2) Why is the relation between genotype and phenotype frequently complex for quantitative characteristics?
   
   Multiple genes are involved.
   The alleles are usually recessive.
   The environment often influences the phenotype.
   Answers A and B are both correct.
   Answers A and C are both correct.

2.    (Problem 6) How is the standard deviation related to the variance?
   
   The standard deviation is the difference between the mean and the variance.
   The standard deviation is the square of the variance.
   The standard deviation is the square root of the variance.
   The standard deviation is the square root of the difference between the mean and the variance.
   The standard deviation is the square of the difference between the mean and the variance.

3.    (Problem 7) What information does the correlation coefficient provide about the association between two variables?
   
   How strongly two variables are associated
   The difference in the mean values of two variables
   The magnitude of the difference between two variables
   The difference in standard deviation between two variables
   The extent to which each variable deviates from its mean

4.    (Problem 10) Narrow-sense heritability is due to what type of genetic variance?
   
   Additive
   Environmental
   Genic interaction
   Dominance
   Genetic by environment interaction

Explanation / Answer

Q1)  Why is the relation between genotype and phenotype frequently complex for quantitative characteristics?

Answer- E- Answers A and C are both correct.

Explanation-

Quantitative characteristics are polygenic ( that is many genes control a single characteristics) , so many genotypes are possible, and also many quantitative characteristics are influenced by environmental factors. so the phenotype is determined by complex interactions of many genotypes and environmental factors.

Q2)  How is the standard deviation related to the variance?

Answer- C - The standard deviation is the square root of the variance.

Explanation- standard deviation of a random variable, statistical population or probability distribution is the square root of its variance.

variance combines all the values in a data set to produce a measure of spread. The variance ( issymbolized by S2) and standard deviation (the square root of the variance, symbolized by S) are the most commonly used measures of dispersion. Variance is used to measure how a data set is dispersed. It is calculated as the average squared deviation of each number from the mean of a data set.

Example-

suppose there is data set = (1,2,3)

For the numbers 1, 2, and 3 the mean is = [ 1+2+3] / 3= 6/3= 2 and the variance is 0.667.

[(1 - 2)2 + (2 - 2)2 + (3 - 2)2] / 3 = 0.667

[squaring deviation from the mean] / number of observations = variance

Variance (S2) = average squared deviation of values from mean

To calculating variance squaring of deviations required , as a result there units vary they do not have the same unit of measurement as the original observations. For example, lengths measured in metres (m) have a variance measured in metres squared (m2).

By taking square root of the variance it gives us the unit used in the original scale and that is the standard deviation.

Standard deviation (S) = square root of the variance.

Q 3)  What information does the correlation coefficient provide about the association between two variables?
Answer- A- How strrongly two varibales are associated .

Explanation- A correlation coefficient measures the degree or the strength of the relationship between two variables.

example - suppose the price of a particular thing increases than the demand decreases, and vice versa, If the change in one variable occurs due to change in other, then the variables are called correlated. It shows there strength of assoication.

Q4) Narrow sence heritability is due to what type of genetic variance?

Answer- a) Additive.

Explanation- 'narrow sense heritability' (h2) is defined as the proportion of trait variance that is due to additive genetic factors.

h2 = Var (A) /Var (P)

additive variance, Var(A), is the variance due to the average effects (additive effects) of the alleles. As each parent passes a single allele per locus to each offspring, parent-offspring resemblance depends on the average effect of single alleles. So Additive variance is the genetic component of variance responsible for parent-offspring resemblance. The additive genetic portion of the phenotypic variance is known as Narrow-sense heritability .

Additive variance is important for selection. If a selective pressure like, improving a livestock is required, the response of the trait is directly related to the narrow-sense heritability. This mean the trait in the next generation depends on the difference of the mean of the selected parents, from the mean of the population from which the selected parents were taken. The observed response to selection helps in calculating the narrow-sense heritability , it is used in artificial selection or breeding.

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