Users are often frustrated when they encounter a sudden decrease in the responsiveness of their personal computers. However, it is often difficult to pinpoint a particular offending process and the resource it is over-consuming, even when such a simple explanation does exist. We present preliminary results from several weeks of PC usage showing that user-perceived unresponsiveness often has such a simple explanation and that simple statistical models often suffice to pinpoint the problem. The statistical models we build use all the performance counters for all running processes. When the user expresses frustration at a given time point, we can use these models to determine which processes are acting most anomalously, and in turn which features of those processes are most anomalous. We present an investigative tool that ranks processes and features according to their degree of anomaly, and allows the user to interactively examine the relevant time series.