First, let's understand the terms we are dealing with. The mean of a distribution represents the average or the center of the distribution. On the other hand, the variance measures how far the numbers in the dataset are from the mean, or their average distance from the mean.
In the case of a normal distribution, the mean is located directly in the center of the distribution and describes its location. The variance tells us the spread or dispersion of the data.
If the problem does not provide any specific data to use for guessing, then we consider using a standard normal distribution. A standard normal distribution usually has specific characteristics: a mean of 0 and a variance of 1.
With this in mind, we would guess the mean and the variance of the generating normal distribution as being 0 and 1 respectively; because these are the traits of a standard normal distribution in the absence of any specific provided data.
So, the answer to the question "What would you guess the mean and the variance of the generating normal distribution were?" is A. Mean = 0, Variance = 1. This is because these values are assumed in a standard normal distribution when no other specifics are provided.