Particle Image Velocimetry has become a desirable tool to investigate turbulent flow fields in different engineering applications, including flames, combustion engines, and turbomachinery. The convergence characteristics of turbulent statistics of these flow fields are of prime importance since they help with the number of images (temporally uncorrelated) to be captured in order for the results to converge to a certain tolerance or with the assessment of the uncertainty of the measurements for a given number of images. The present work employs Stereoscopic Particle Image Velocimetry to examine the turbulent flow field at the inlet of an automotive turbocharger compressor without any recirculating channel. Optical measurements were conducted at five different mass flow rates spanning from choke to surge at a corrected rotational speed of 80 krpm. The velocity fields thus obtained were used to analyze the convergence of the mean (first statistical moment) and variance (second statistical moment) at different operating conditions. The convergence of the mean at a particular location in the flow field depends on the local coefficient of variation (COV). The number of required images for the mean to converge to a particular tolerance was also found to follow roughly a linear trend with respect to COV. While the convergence of the variance, on the other hand, did not appear to show any direct dependence on the coefficient of variation, it takes significantly more images than the mean to converge to the same level of tolerance.