Final answer:
Variance (Var(X)) and standard deviation (sd) are concepts applicable to both Discrete Random Variables (DRV) and Continuous Random Variables (CRV), but they are not calculated in the same way for both. DRVs involve summation whereas CRVs require integration over the range of the random variable.
Step-by-step explanation:
The question pertains to whether the variance (Var(X)) and standard deviation (sd) are the same for Discrete Random Variables (DRV) and Continuous Random Variables (CRV). The answer is (b) No. While both DRV and CRV have a concept of variance and standard deviation, they are calculated differently due to the nature of the variables. In DRVs, variance is calculated using the sum of the probabilities of each outcome times the square of its deviation from the mean, while for CRVs, it involves integration over the entire range of the random variable using a probability density function.
Variance and standard deviation for both DRV and CRV are measures of dispersion, indicating how data is spread out around the mean. However, the methods of calculation are adapted to the different types of data they represent - discrete outcomes for DRV and a continuum of values for CRV.