Experimental data from two cold airflow turbine tests were evaluated. The two tests had different, relatively high gradient flow fields at the turbine exit. The objective of the research was to evaluate data requirements, including the averaging techniques, the number of measurements, and the types of measurements needed, for high gradient flow fields. Guidelines could then be established for future tests that could allow reduction in test time and costs. An enormous amount of data was collected for both tests. These test data were then manipulated in various ways to study the effects of the averaging techniques, the number of measurements, and the types of measurements on the turbine efficiency. The effects were evaluated relative to maintaining a specific accuracy (1%) for the turbine efficiency. Mass and area averaging were applied to each case. A detailed uncertainty analysis of each case was done to evaluate the uncertainty of the efficiency calculations. A new uncertainty analysis technique was developed to include conceptual bias estimates for the spatially averaged values required in the efficiency equations. Conceptual bias estimates were made for each test case, and these estimates can be used as guidelines for similar turbine tests in the future. The evaluations proved that mass averaging and taking measurements around the full 360 degree was crucial for obtaining accurate efficiency calculations in high gradient flow fields. In addition, circumferential averaging of wall-static pressure measurements could be used rather than measuring static pressures across the annulus of the high gradient flow field while still maintaining highly accurate efficiency calculations. These are an important finding in that considerable time and cost savings may be realized due to the decreased test time, probe measurements, and calibration requirements.