Final answer:
The variance of h(x) is the expected value of the squared difference between h(x) and its expected value is b). Standard Deviation.
Step-by-step explanation:
The variance of h(x) is the expected value of the squared difference between h(x) and its expected value. In other words, it measures how far the values of h(x) are spread out from their mean. The formula to calculate variance is:
Variance = Σ (x - µ)² / n
Where
x represents the values of h(x)
'μ represents the mean of h(x)
n represents the sample size.
The standard deviation is the square root of the variance. It gives us a measure of the average amount of dispersion or variation of the values in the data set relative to the mean. In this case, the standard deviation of h(x) would represent how spread out the values of h(x) are from their expected value. Therefore the correct answer is b. Standard Deviation.