a change in the path traversed by the data sent from the client to M-Lab. Due to the variability in network conditions that can affect latency, we use two measurements: the minimum RTT recorded in the session and the uniform average over the entire test.

Aggregation and Comparative Methods
-----------------------------------

In order to assess the general performance of the domestic network, client measurements are aggreggated across higher-level groupings and evaluated based on their median value. Where multiple tests are performed by a client during an evaluation period, the most performant measurement is used in order to mitigate potential bias in samples. Through giving preference to faster measurements, we intentionally bias our pool of data against our hypothesis and assume that less favorable numbers are aberrations. Furthermore, we prefer calculations that accomodate for outlier values, such as false positives that occur in geolocation services when foreign-hosted networks are registered to domestic entities. Finally, we assume the natural shifts in consumer behavior or infrastructure development that may affect measurements, such as the adoption of mobile broadband, are gradual and upward trends. In practice this assumption appears to not only hold, but we are led to question whether the availability of high-speed connectivity 