With the recent advance of process technology shrinking, process parameter variation has become one of the major issues in SoC designs, especially for timing convergence. Recently, Statistical Static Timing Analysis (SSTA) has been proposed as a promising solution to consider the process parameter variation but it has not been widely used yet. For estimating the delay yield, designers have to know and understand the accuracy of SSTA. However, the accuracy has not been thoroughly studied from a practical point of view. This paper proposes two metrics to measure the pessimism/optimism of SSTA; the first corresponds to yield estimation error, and the second examines delay estimation error. We apply the metrics for a problem which has been widely discussed in SSTA community, that is, normal-distribution approximation of max operation. We also apply the proposed metrics for benchmark circuits and discuss about a potential problem originating from normal-distribution approximation. Our metrics indicate that the appropriateness of the approximation depends on not only given input distributions but also the target yield of the product, which is an important message for SSTA users.