ABSTRACT
As we discussed when we talked about continuous distribution functions, the probability of a specific number under a continuous distribution is zero. Thus, if we conceptualize any estimator, either a nonparametric estimate of the mean or a parametric estimate of a function, the probability that the true value is equal to the estimated value is obviously zero. Thus, we usually talk about estimated values in terms of confidence intervals. As in the case when we discussed the probability of a continuous variable, we define some range of outcomes. However, this time we usually work the other way around, defining a certain confidence level and then stating the values that contain this confidence interval.
