1. A computer-implemented method for detecting anomalies in a performance metric associated with monitored transactions of a distributed computing environment, comprising: capturing, by a sensor instrumented in a monitored application, a plurality of measurement values for a performance metric, where the performance metric is for a transaction executed in part by the monitored application, and the sensor and the monitored application reside on and are executed by a processor of a host computer; calculating, by the anomaly detector, a current distribution parameter from the plurality of measurement values, where the current distribution parameter is indicative of statistical distribution of the plurality of measurement values for the performance metric during the present period of time; retrieving, by the anomaly detector, a baseline distribution parameter for the performance metric, where the baseline distribution parameter is indicative of statistical distribution of measurement value for the performance metric during a preceding period of time, where the preceding period of time precedes the present period of time; detecting, by the anomaly detector, a change in shape of the statistical distribution of the plurality of measurement values for the performance metric during the present period of time by comparing the current distribution parameter to the baseline distribution parameter; determining whether quantity of the plurality of measurement values exceeds a significance threshold; and detecting an anomaly in the performance metric based on the detected change in shape of the statistical distribution only when the quantity of measurement values exceeds the significance threshold, where the anomaly detector is executed by a processor of a monitoring computer residing across a network from the host computer.