Micro-Electro Mechanical System (MEMS) is the micro-scale technology applying on various fields. Traditional testing strategy of MEMS requires physical stimulus, which leads to high cost specified equipment. Also there are a large number of wafer-level measurements for MEMS. A method of estimation calibration coefficient only by electrical stimulus based wafer level measurements is included in the thesis. Moreover, a statistical technique is introduced that can reduce the number of wafer level measurements, meanwhile obtaining an accurate estimate of unmeasured parameters. To improve estimation accuracy, outlier analysis is the effective technique and merged in the test flow. Besides, an algorithm for optimizing test set is included, also providing numerical estimated prediction error.