Step 1: Understanding the Concept:
Heritability (\( h^2 \)) can be estimated using parent-offspring regression or sib analyses.
Precision refers to the statistical standard error of the estimate.
A smaller standard error corresponds to higher precision.
Step 2: Detailed Explanation:
Let us analyze the statistical precision of both statements.
- Statement (I) compares single-parent and mid-parent regressions.
The regression of offspring on one parent estimates \( h^2 / 2 \), meaning \( h^2 = 2 \times b \).
The regression of offspring on the mid-parent (the average of both parents) directly estimates \( h^2 \), meaning \( h^2 = b \).
Since the mid-parent value is an average, its variance is halved (\( V_{\bar{P}} = \frac{1}{2} V_P \)).
This reduction in parental variance lowers the standard error of the regression coefficient.
Thus, mid-parent regression yields *higher* precision (smaller standard error) than single-parent regression, making Statement (I) incorrect.
- Statement (II) compares full-sib and half-sib family estimates.
Full-sibs share \( 50\% \) of their additive genetic variance, whereas half-sibs share only \( 25\% \).
Because the genetic relationship is stronger in full-sibs, the intraclass correlation is larger.
For a given sample size, a larger intraclass correlation coefficient results in a smaller standard error of the heritability estimate.
Thus, heritability estimates from full-sib families are *more* precise (have a lower standard error) than those from half-sib families, making Statement (II) incorrect.
Therefore, both statements are incorrect.
Step 3: Final Answer:
Both Statement (I) and Statement (II) are incorrect, corresponding to option 2.